DESC:FORM 2
THE PATENTS ACT, 1970
(39 of 1970)
&
THE PATENTS RULES, 2003
COMPLETE SPECIFICATION
(Section 10 and Rule 13)

TITLE OF THE INVENTION
SYSTEM AND METHOD FOR PEAK SHAVING

APPLICANT:
Servotech Power Systems Ltd., an Indian company of the address 806, 8th Floor, Crown Heights, Near Hotel Crowne Plaza, Sector-10, Rohini, Delhi, North West , Pin 110085 Delhi, India

The following specification particularly describes the invention and the manner in which it is to be performed:

FIELD OF INVENTION
[001] The present disclosure relates to a system and method for energy management. More specifically, the present disclosure relates to a system and method for peak shaving.
BACKGROUND OF INVENTION
[002] Energy consumption varies throughout the day with distinct peaks and valleys. To accommodate this fluctuating demand, utility providers also vary their pricing throughout the day. During times of high electricity demand, “peak” utility rates kick in and when the energy demand goes down, “off-peak” pricing comes into effect.
[003] To manage the energy consumption, the hours of operations of load can be changed depending upon what the utility providers are charging for electricity. Unfortunately, this approach is not really practical. Alternately, older electronic equipment may be updated, for example, incandescent bulbs may be replaced with LEDs to make the system more energy efficient, etc. Solar photovoltaic (PV) panel may be installed to reduce reliance on utility grid. However, as such, solar photovoltaic panel (on its own) is becoming less viable energy management strategy for long-term. Even with a high-quality PV panel that delivers abundant solar power, one still gets hit with demand charges throughout the day.
[004] Many solutions are available to achieve peak shaving. The most common and the easiest is to manually switching off one or more components of the load to reduce the demand. However, this approach requires constant monitoring by a user. It is also inefficient and error prone since the user may not always know which components of the load to switch off in a given situation to reduce the demand. Another approach is to use diesel generators to provide additional energy during the peak demand. However, the diesel generators are expensive to operate and suffer from the same disadvantages as it is a manual process to couple or decouple the diesel generator. The diesel generators are also polluting.
[005] Standalone solar arrays reduce peak demand and hence, reduce peak charges. However, they do not provide guaranteed peak shaving, especially during evening hours or when the solar power is temporarily reduced or is unavailable due to, for example, cloud cover, shading, etc.
[006] None of the present solutions provide an effective solution that draws minimum energy from a utility company/provider and creates minimum carbon emissions and contributes effectively towards generating a self-sustaining ecosystem.
[007] Therefore, there is a need for a technical solution that addresses the above-stated problems.
SUMMARY OF INVENTION
[008] The present disclosure relates to systems and methods for peak shaving. In an embodiment, a system for peak shaving is disclosed. The system includes a plurality of input ports coupled to a plurality of electrical systems. The plurality of electrical systems includes a grid, a renewable energy generator, a storage unit and a load. The system further includes one or more sensors coupled to each input port. The one or more sensors are configured to sense one more electrical parameters of a respective electrical system. The system includes a parameters module. The parameters module, executed by a processor, is configured to obtain the one or more electrical parameters of the plurality of electrical systems at a pre-defined interval. The system also includes a profile module executed by the processor and coupled to the parameters module. The profile module is configured to create a real time profile for each electrical system at the pre-defined interval using the values of the one or more electrical parameters of the electrical system. The system includes an error module, executed by the processor and coupled to the profile module. The error module is configured to generate an error profile for each electrical system based upon the corresponding real-time profile and a corresponding standard profile of the electrical system. Each error profile includes a corresponding error profile power. The system includes a clock module, executed by the processor, configured to compare time of day with peak hours. The system further includes a peak shaving module executed by the processor and coupled to the clock module. The peak shaving module is configured to determine, based upon the error profiles of the plurality of electrical systems, at least one electrical system of the plurality of electrical systems to drive the load, when the time of day overlaps with the peak hours and the load is present. The peak shaving module is configured to send at least one control signal to couple the at least one electrical system to the load. The system further includes at least one control circuit, coupled to a respective electrical system and including at least one power semiconductor switching element. The at least one control circuit is configured to receive the at least one control signal and couple the at least one electrical system to the load to drive the load.
[009] In an embodiment, a method for peak shaving is disclosed. The method includes obtaining values of one or more electrical parameters of a plurality of electrical systems from respective one or more sensors at a pre-defined interval. The plurality of electrical systems includes a grid, a renewable energy generator, a storage unit and a load. The method further includes creating a real time profile for each electrical system of the plurality of electrical systems at the pre-defined interval using the values of the one or more electrical parameters of the electrical system. The method further includes generating an error profile for each electrical system of the plurality of electrical systems based upon the corresponding real time profile and a standard profile of the electrical system. Each error profile includes a corresponding error profile power. The method further includes comparing time of day with peak hours. The method further includes determining, based upon the error profiles of the plurality of electrical systems, at least one electrical system of the plurality of electrical system to drive the load when the time of day overlaps with the peak hours and the load is present. The method further includes sending at least one control signal to at least one control circuit, coupled to a respective electrical system and including at least one power semiconductor switching element, to couple the at least one electrical system to the load to drive the load.
[0010] The foregoing features and other features as well as the advantages of the disclosure will become more apparent from the following detailed description, which proceeds with reference to the accompanying figures.
BREIF DESCRIPTION OF DRAWINGS
[0011] The summary above, as well as the following detailed description of illustrative embodiments, is better understood when read in conjunction with the apportioned drawings. For the purpose of illustrating the present disclosure, exemplary constructions of the disclosure are shown in the drawings. However, the disclosure is not limited to specific methods and instrumentalities disclosed herein. Moreover, those in the art will understand that the drawings are not to scale.
[0012] FIG.1 illustrates a system 100 in which an energy management device 101 may be deployed, in accordance with an embodiment of the present disclosure.
[0013] FIG. 2 illustrates a block diagram of the energy management device 101, in accordance with an embodiment of the present disclosure.
[0014] FIG.3 illustrates a schematic block diagram of an energy management module 209, in accordance with an embodiment of the present disclosure.
[0015] FIG. 4 illustrates a schematic block diagram of at least control circuit 211, in accordance with an embodiment of the present disclosure.
[0016] FIG. 5 illustrates a control circuit 211n of the at least one control circuit 211, in accordance with an embodiment of the present disclosure.
[0017] FIG. 6 depicts a flowchart of a method 600 for energy channelization, in accordance with an embodiment of the present disclosure.
[0018] FIG. 7 depicts a flowchart of a method 700 for calculating at least two fractions of energy to be channelized between two or more electrical systems, in accordance with an embodiment of the present disclosure.
[0019] FIG. 8 depicts a flowchart of a method 800 for peak shaving, in accordance with an embodiment of the present disclosure.
[0020] FIG. 9 depicts a flowchart of a method 900 for determining at least one electrical system to drive a load, in accordance with an embodiment of the present disclosure.
[0021] FIG. 10 depicts a flowchart of a method 1000 for controlling charging and discharging of a storage unit, in accordance with an embodiment of the present disclosure.
[0022] FIG. 11 depicts a flowchart of a method 1100 for creating a charging profile and a discharging profile, in accordance with an embodiment of the present disclosure.
DETAILED DESCRIPTION OF ACCOMPANYING DRAWINGS
[0023] The following description is presented to enable any person skilled in the art to make and use the disclosure. For purposes of explanation, specific nomenclature is set forth to provide a thorough understanding of the present disclosure. Descriptions of specific applications are provided only as examples. Various modifications to the preferred embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other embodiments and applications without departing from the spirit and scope of the disclosure. Thus, the present disclosure is not intended to be limited to the embodiments shown, but is to be accorded the widest scope consistent with the principles and features disclosed herein.
[0024] The embodiments are described below with reference to block diagrams and/or data flow illustrations of methods, apparatus, systems, and computer program products. It should be understood that each block of the block diagrams and/or data flow illustrations, respectively, may be implemented in part by computer program instructions, e.g., as logical steps or operations executing on a processor in a computing system. These computer program instructions may be loaded onto a computer, such as a special purpose computer or other programmable data processing apparatus to produce a specifically-configured machine, such that the instructions which execute on the computer or other programmable data processing apparatus implement the functions specified in the data flow illustrations or blocks.
[0025] These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including computer-readable instructions for implementing the functionality specified in the flowchart block or blocks. The computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer-implemented process such that the instructions that execute on the computer or other programmable apparatus provide operations for implementing the functions specified in the data flow illustrations or blocks.
[0026] Accordingly, blocks of the block diagrams and data flow illustrations support various combinations for performing the specified functions, combinations of operations for performing the specified functions and program instructions for performing the specified functions. It should also be understood that each block of the block diagrams and flowchart illustrations, and combinations of blocks in the block diagrams and flowchart illustrations, can be implemented by special purpose hardware-based computer systems that perform the specified functions or operations, or combinations of special purpose hardware and computer instructions.
[0027] Further, applications, software programs or computer readable instructions may be referred to as components or modules. Applications may be hardwired or hardcoded in hardware or take the form of software executing on a general-purpose computer such that when the software is loaded into and/or executed by the computer, the computer becomes an apparatus for practicing the disclosure, or they are available via a web service. Applications may also be downloaded in whole or in part through the use of a software development kit or a toolkit that enables the creation and implementation of the present disclosure. In this specification, these implementations, or any other form that the disclosure may take, may be referred to as techniques. In general, the order of the steps of disclosed processes may be altered within the scope of the disclosure.
[0028] In the context of the present disclosure, the following terms used in the description below are defined for clarity. The term ‘electrical system’ corresponds to system(s) or device(s) that generate electrical power, provide electrical power, store electrical power and/or consume electrical power. The electrical system includes one or more of a grid, a load, a renewable energy generator and/or an energy storage unit.
[0029] The term ‘peak hours’ corresponds to one or more hours of a day during which maximum energy is drawn from grid to be consumed by the load. The term ‘off-peak hours’ corresponds to hours of the day other than the aforesaid peak hours.
[0030] ‘Peak shaving’ throughout the following description corresponds to a process of reducing the amount of energy drawn from a distribution company (say a grid or a utility provider) during the peak hours of energy demand to reduce the peak demand charges by applying energy shifting, relying on a storage unit or both.
[0031] The term ‘third party’ corresponds to a utility company, a local distribution company or a distribution company. Such terms are interchangeably used throughout the description.
[0032] The term ‘standard profile’ corresponds to log details (or data set) corresponding to one or more electrical parameters in relation to an electrical system. The dataset may be, for example, pre-fed in the system of the present disclosure by a user or provided to the system at the time of initial configuration, etc.
[0033] The term ‘real-time profile’ corresponds to log details (or data set) of real-time values of the one or more electrical parameters in relation to an electrical system. The real time values of the one or more electrical parameters may be recorded upon monitoring the electrical system.
[0034] The term ‘error profile’ corresponds to a data set derived based upon deviation between the values of the one or more electrical parameters of the standard profile and the real-time profile.
[0035] The present disclosure relates to systems and methods for energy management between a plurality of electrical systems. The plurality of electrical systems includes a grid, a renewable energy generator, a storage unit and a load. In accordance with an embodiment of the present disclosure, a system and a method for energy channelization is disclosed. In an embodiment, the system analyses one or more electrical parameters of the plurality of electrical system in real-time and determines a quantum of energy to be channelized between two or more electrical systems of the plurality of electrical systems. In an embodiment, the system facilitates fractional energy channelization between the two or more electrical system. For example, the system may channelize a first fraction of energy from a first electrical system to a second electrical system and a second fraction of energy from the first electrical system to a third electrical system. The system determines the quantum of energy to be channelized based upon one or more factors, such as, state of charge (SOC) of the storage unit, quantum of running load, status of the renewable energy generator and the grid, time of day, etc. and ensures that maximum load is run on renewable energy especially during peak hours (namely, hours when demand of energy from the grid is high or when there is maximum load on the grid). Ability to perform fractional energy channelization allows the system to optimally control performance of the electrical systems, optimize the use of the renewable energy generator and the storage system to drive the load, and deploy power from the renewable energy, the storage unit and the grid more effectively during the operation. For example, unlike conventional systems which cannot perform fractional energy channelization, the system of the present disclosure allows the renewable energy generator to drive the load and charge the storage unit at the same time. Thus, the present disclosure ensures that the consumer draws minimum energy from the grid and creates minimum carbon emissions thereby, effectively contributing towards generating a self-sustaining ecosystem. Owing to the reduction of carbon and other harmful emissions, the present disclosure helps in reduction of greenhouse effect and global warming to a great extent. In an embodiment, the system enables a third party (e.g., the DISCOM) to control the energy channelization.
[0036] In accordance an embodiment of the present disclosure, a system and a method for peak shaving are disclosed. The system analyses one or more electrical parameters of a plurality of electrical systems in real-time and ensures that no energy above a pre-determined load threshold is drawn from the grid during the peak hours. In an embodiment, during the peak hours, the system switches the load from the grid to the renewable energy generator or the storage unit or both. The system may give preference to the renewable energy generator to drive the load when energy from the renewable energy generator is available. The system may switch the load to the storage unit when the state of charge (SOC) of the storage unit is above a pre-programmed SOC threshold. The system constantly monitors the SOC of the storage unit. If the SOC of the storage unit reaches the pre-programmed SOC threshold while the peak hours are ongoing, the system maintains the load from the renewable energy generator if the energy from the renewable energy generator is available, according to an embodiment. The storage unit may be charged in parallel by using the renewable energy generator. If the renewable energy is not available during the peak hours and the SOC of the storage unit reaches the pre-programmed SOC threshold, the system may reduce the load (for example, by disconnecting non-critical components of the load) and switches the load to the grid. Once the off-peak hours are reached, the system switches the load to the renewable energy generator if the power from the renewable energy generator is available or to the grid, according to an embodiment. Further, the charging of the storage unit may be initiated by the system.
[0037] In accordance with an embodiment of the present disclosure, a system and a method for controlling charging and discharging of the storage unit is disclosed. In an embodiment, the system analyses one or more electrical parameters of a plurality of electrical systems and controls charging/discharging of the storage unit according to the SOC of the storage unit and the time of day. In an embodiment, the system charges the storage unit using the renewable energy generator or using the grid during the off-peak hours, when the electricity is comparatively cheaper and there is no burden on the grid. During the peak hours, the system starts driving the load through the storage unit. In an embodiment, during the peak hours, the system exploits the energy from the renewable energy generator to the fullest, thereby optimizing the discharge rate of the storage unit. Further, according to an embodiment, the system ensures that the storage unit is charged only once the SOC of the storage unit reaches the pre-programmed SOC threshold. Thus, the system avoids frequent charging/discharging of the storage unit, which improves the health and the life of the storage unit.
[0038] Though the present disclosure is explained in detail using solar energy that is harnessed using a renewable energy generator in the form of photovoltaic systems (PV), it should be noted that the systems and methods of the present disclosure are compatible with all types of renewable energy generators.
[0039] The systems and methods of the present disclosure provide several advantages over conventional systems. The system is fully automatic and ensures seamless energy flow during different situations with the use of power semiconductor switching elements. The method is also dynamic in nature and is carried out in real-time. Due to this the system is able to respond to real-time changes in the status of the electrical systems. The renewable energy from the renewable energy generator is optimally utilized for driving the load as well as for charging the storage unit. This results in minimum electricity consumption from the grid for the users, thereby reducing their costs. The system ensures uninterrupted power for critical load during blackout and brownout through optimal energy channelization from the renewable energy generator and the storage unit. The system is able to isolate non-critical load during the peak hours, thereby saving on energy. Minimal energy is drawn from the grid, especially during the peak hours. This reduces carbon footprint and global warming, thereby helps in creating a green ecosystem for the society. This reduces the burden on the distribution network, thereby reducing power loss. Optimal charging/discharging of the storage unit ensures its availability during peak hours and prolongs its life.
[0040] In an embodiment, the systems and the methods are user programmable by enabling a user to control the system as per his requirement. In an embodiment, the user may program the system through a user interface on an electronic device (in the form of a personal computer or a dedicated mobile application based on Android or iOS downloadable on a mobile phone).
[0041] Now referring to figures, FIG. 1 illustrates a system 100 including an energy management device 101 for practicing teachings of the present disclosure, as per an embodiment. The system 100 may be deployed within a premise such as, a building, a home, a factory, etc. The energy management device 101 (or the device 101) is coupled to a plurality of electrical systems (hereinafter, electrical systems). The electrical systems may include one or more grids 103 (hereinafter, the grid 103), one or more storage units 105 (hereinafter, the storage unit 105), one or more renewable energy generators 107 (hereinafter, the renewable energy generator 107) and one or more loads 109 (hereinafter the load 109).
[0042] Further, the storage unit 105 may be coupled to a bi-directional converter 111. The bi-directional converter 111 converts DC power from the storage unit 105 to AC power to be supplied to the load 109 and converts AC power from the renewable energy generator 107 or the grid 103 to DC power to be supplied to the storage unit 105. Further, the renewable energy generator 107 may be coupled to an inverter 113 for inverting the DC power obtained from the renewable energy generator 107. In an embodiment, the bi-directional converter 111 and the inverter 113 may be implemented as a single unit.
[0043] The grid 103 may include a power plant, a substation, a power line, etc. The grid 103 may supply power to a premise such as, a building, a home, a factory, etc. having the load 109 consuming the supplied power. Further, the power supplied by the grid 103 may be stored in the storage units 105 through a suitable converter (such as the bi-directional converter 111), or the grid 103 may receive power generated by the renewal energy generator 107 as described herein.
[0044] The load 109 may consume the power generated by the renewable energy generator 107, the power stored in the storage unit 105, and/or the power supplied from the grid 103. Examples of the load 109 include commercial, industrial, and residential equipment, such as home appliances, lights, fans, audio/video devices, computers/servers, heating ventilating and air conditioning (HVAC) equipment, motors, machines, etc.
[0045] The storage unit 105 may be a battery or set of batteries, such as stationary or mobile batteries. For example, stationary batteries may be installed in a building or a home. In certain embodiments, the set of batteries may be distributed throughout a site and coupled to the device 101, and may be disposed in modular battery systems (e.g., racks) for flexibility in energy storage capacity.
[0046] The renewable energy generator 107 generates power by using a natural energy source. The renewable energy generator 107 stores the generated power in the storage unit 105 or supplies the generated power to the load 109 and/or the grid 103. The renewable energy generator 107 may be a solar power generation system, a wind power generation system, a tidal power generation system, or the like, or may be any of other types of power generation systems for generating power by using renewable energies, such as a power generator using solar heat, geothermal heat, or the like. For example, a solar power generator like a photovoltaic (PV) panel, which generates electric power by using sunlight, may be connected to the storage unit 105 installed at the premise. The renewable energy generator 107 may include a plurality of power generating modules connected in parallel. Alternatively, the renewable energy generator 107 may be a large capacity energy system where each of the plurality of power generating modules generates energy.
[0047] The device 101 effectively channelizes energy between the grid 103, the storage unit 105, the renewable energy generator 107 and the load 109 optimizing energy drawn from the grid 103 and creating minimum carbon emissions. For example, the device 101 may enable storage of energy generated by the renewable energy generator 107 in the storage unit 105, or may enable transmission of the energy to the grid 103 and/or the load 109. Furthermore, the device 101 may enable transmitting energy stored in the storage unit 105 to drive the load 109. Further, the device 101 may channelize the energy supplied by the grid 103 to the storage unit 105 to store the energy in the storage unit 105 and/or channelize the energy from the grid 103 to drive the load 109. Further, the device 101 may channelize the energy stored in the storage unit 105 to the grid 103 or to electrical distribution systems of the premise. In an embodiment, the device 101 enables fractional energy channelization between one or more of the grid 103, the storage unit 105, the renewable energy generator 107 and the load 109. For example, the device 101 may channelize a first fraction of the energy generated by the renewable energy generator 107 to the storage unit 105 and a second fraction of the energy generated by the renewable energy generator 107 to the load 109, and so on. Various embodiments of the fractional energy channelization are explained later.
[0048] In an embodiment, the device 101 may enable peak shaving by minimizing energy drawn from the grid 103 during peak hours. In an embodiment, the device 101 may switch the load 109 to the renewable energy generator 107, the storage unit 105 or both during the peak hours to save on the grid power and reduce carbon footprint.
[0049] In accordance with an embodiment, the device 101 may optimize charging of the storage unit 105 to increase the life of the storage unit 105 by avoiding frequent charging and discharging of the storage unit 105. In an embodiment, the storage unit 105 may be charged during off-peak hours and discharged during peak hours. The device 101 may consider state of charging (SOC) of the storage unit 105 to optimize the charging/discharging of the storage unit 105.
[0050] The device 101 may perform the energy channelization, the peak shaving and/or charging/discharging control based upon one or more electrical parameters of the grid 103, the storage unit 105, the renewable energy generator 107 and the load 109 monitored in real-time.
[0051] Further, the device 101 may be coupled to a DISCOM 115. In an embodiment, the device 101 may perform energy channelization based upon a command from the DISCOM 115.
[0052] Though only a single energy management device 101 is shown in FIG. 1, it is possible that more than one energy management devices 101 may be deployed, for example, in large premises such as an industrial area or a housing complex, etc. to monitor the one or more electrical parameters of the electrical systems at different locations within the premises and perform the energy channelization for the entire premises. In an embodiment, one energy management device 101 may function as a central hub and one or more other energy management devices 101 may function as nodes coupled to the central hub. The nodes may send data (including the one or more electrical parameters) to the central hub over a suitable data interface. The central hub then processes the data to facilitate effective energy management (including energy channelization, peak shaving, controlling charging/discharging of the storage unit 105) for the entire premises by sending appropriate commands (via a suitable data interface) to the nodes. In another embodiment, a remote server may function as a central hub and the energy management devices 101 may function as the nodes.
[0053] FIG. 2 illustrates a schematic block diagram of the device 101, in accordance with an embodiment. The device 101 may include a plurality of input ports 201a – 201d (collectively referred to as the input ports 201) coupled to a respective electrical system. For example, the input port 201a is coupled to the grid 103, the input port 201b is coupled to the storage unit 105, the input port 201c is coupled to the renewable energy generator 107, and the input port 201d is coupled to the load 109, as shown. In an embodiment, instead of coupling the electrical systems to a respective input port, the electrical systems may be multiplexed and coupled to the device 101 via a single input port.
[0054] The device 101 may include a plurality of sensor units 203a – 203d (collectively referred to as the sensor units 203) with each sensor unit of the sensor units 203 coupled to a respective input port of the input ports 201. The sensor units 203 measure one or more electrical parameters of the electrical systems. For example, the sensor unit 203a measures one or more electrical parameters of the grid 103. The sensor unit 203b measures one or more electrical parameters of the storage unit 105. The sensor unit 203c measures one or more electrical parameters of the renewable energy generator 107. The sensor unit 203d measures one or more electrical parameters of the load 109. Each sensor unit of the sensor units 203 may include one or more sensors (not shown) to sense the one or more electrical parameters. The sensors may include, without limitation, voltage transducers, current transducers, power sensors. The device 101 may include one or more additional sensors (not shown) such as temperature sensors, irradiation sensors, etc.
[0055] The device 101 may include a memory 205, a processor 207, an energy management module 209 and at least one control circuit 211. The energy management module 209 may be embedded in the memory 205. Various functions of the energy management module 209 may be executed via the processor 207. The processor 207 may be, for example, a microcontroller.
[0056] The energy management module 209 is configured to monitor one or more electrical parameters of the grid 103, one or more electrical parameters of the load 109, one or more electrical parameters of the renewable energy generator 107 and one or more electrical parameters of the storage unit 105. The one or more electrical parameters of the grid 103 may include one or more of, voltage, current, power, etc. The one or more electrical parameters of the load 109 may include one or more of, impedance, voltage, current, etc. The one or more electrical parameters of the storage unit 105 may include one or more of, state of charge (SoC), voltage, current, temperature, etc. The one or more electrical parameters of the renewable energy generator 107 may include one or more of, temperature, voltage, current, irradiation (in case of solar energy), etc. The energy management module 209 may also monitor real time clock data to determine time of the day.
[0057] The energy management module 209 may obtain or receive the one or more electrical parameters of the grid 103, the storage unit 105, the renewable energy generator 107 and the load 109 from respective sensor units (203a – 203d) and the one or more additional sensors. The energy management module 209 may obtain or receive the one or more electrical parameters of the grid 103, the storage unit 105, the renewable energy generator 107 and the load 109 in real time or at a pre-defined interval. The energy management module 209 checks if the time of the day coincides with the peak hours. In an embodiment, the energy management module 209 accordingly processes the aforesaid parameters to determine a customer’s load to further derive peak demand as explained below, and may switch the load 109 from the grid 103 to the storage unit 105 and/or the renewable energy generator 107 during peak hours/demand to save on the grid power and reduce carbon footprint. In an embodiment, the energy management module 209 may process the aforesaid electrical parameters to control charging and discharging operations of the storage unit 105. In an embodiment, the energy management module 209 may process the aforesaid electrical parameters to perform energy channelization.
[0058] The energy management module 209 saves the obtained values of the electrical parameters of the load 109, the grid 103, the storage unit 105 and the renewable energy generator 107 as respective real-time profiles of the load 109, the grid 103, the storage unit 105 and the renewable energy generator 107.
[0059] Further, the energy management module 209 creates a plurality of error profiles using a plurality of standard profiles and the plurality of real-time profiles of the load 109, the grid 103, the storage unit 105 and the renewable energy generator 107, respectively. An exemplary embodiment of calculating the real-time profiles and the error profiles of the grid 103, the storage unit 105, the renewable energy generator 107 and the load 109 is described in conjunction with FIG. 3.
[0060] According to an embodiment, the energy management module 209 determines the quantum of energy to be channelized between two or more of the grid 103, the load 109, the storage unit 105 and the renewable energy generator 107) based upon the error profiles of one or more of the grid 103, the load 109, the storage unit 105 and the renewable energy generator 107. The energy management module 209 may also use the SOC of the storage unit 105 and the time of the day to determine the quantum of energy to be channelized. According to one embodiment, the energy management module 209 is configured to calculate at least two fractions of energy to be channelized between corresponding two or more electrical systems of the electrical systems based upon the error profiles of the two or more electrical systems. For example, based upon the time of the day (e.g., during the peak hours), the energy management module 209 may calculate, based upon the error profiles for the storage unit 105, the renewable energy generator 107 and the load 109, that a first fraction (say 60%) of energy from the renewable energy generator 107 may be channelized to drive the load 109 and the remaining 40% (a second fraction) of energy from the renewable energy generator 107 can be channelized to charge the storage unit 105. In this case, the energy management module 209 channelizes 60% of the energy from the renewable energy generator 107 to the load 109 and 40% of the energy from the renewable energy generator 107 to the storage unit 105. In another example, the energy management module 209 may determine, based upon the error profiles of the grid 103, the renewable energy generator 107 and the load 109 during the off-peak hours, that the storage unit 105 is charged (as determined from the SOC of the storage unit 105) and calculate that 85% (a first fraction) of the energy from the renewable energy generator 107 is be channelized to the load 109 and the remaining 15% (a second fraction) of the energy from the renewable energy generator 107 to the grid 103.
[0061] In an embodiment, the energy management module 209 is configured to calculate the at least two fractions based upon at least two offset error profiles of the two or more electrical systems. The energy management module 209 calculates the two or more offset error profiles using the error profiles of the two or more electrical systems. For example, the energy management module 209 may calculate a first offset error profile using the error profiles of the storage unit 105 and the renewable energy generator 107. The energy management module 209 may calculate a second offset error profile using the error profiles of the load 109 and the renewable energy generator 107. Embodiments of calculating the offset error profiles and how the two or more offset error profiles are used to calculate the at least two fractions, and thereby perform fractional channelization are described later.
[0062] In an embodiment, the energy management module 209 is configured to perform peak shaving based upon the error profiles of the electrical systems during the peak hours. According to an embodiment, during first peak hours (when power from the renewable energy generator 107 is available), the energy management module 209 is configured to switch the load 109 to the renewable energy generator 107 as long as the energy from the renewable energy generator 107 is sufficient to drive the load 109. If the energy from the renewable energy generator 107 is not sufficient to drive the load 109, the energy management module 209 is configured to check whether the storage unit 105 is sufficiently charged (using for example, the SOC of the storage unit 105). When the storage unit 105 is sufficiently charged, the energy management module 209 is configured to switch the load 109 to the renewable energy generator 107 and the storage unit 105. During the first peak hours, the energy management module 209 may switch the load 109 to the grid 103 only when the energy from the renewable energy generator 107 and storage unit 105 are not sufficient to drive the load 109. In this situation, the energy management module 209 may reduce the load 109 by disconnecting the non-critical components of the load 109 to reduce the energy drawn from the grid 103 during the first peak hours. According to an embodiment, during the second peak hours (when the power from the renewable energy generator 107 is not available), the energy management module 209 switches the load 109 to the storage unit 105 when the storage unit 105 is sufficiently charged to drive the load 109. Thus, the energy management module 209 switches the load 109 to the renewable energy generator 107 or the storage unit 105 or both during the peak hours as much as possible, thereby reducing the energy drawn from the grid 103 during the peak hours.
[0063] In an embodiment, the energy management module 209 is configured to control charging and discharging of the storage unit 105 based upon the SOC of the storage unit 105 and the time of day. In an embodiment, the energy management module 209 is configured to create a charging profile to control charging of the storage unit 105 and a discharge profile to control discharging of the storage unit 105. The energy management module 209 is configured to create the charging profile and the discharging profile based upon the SOC of the storage unit 105 and the time of day. In an embodiment, the discharging profile includes a fraction of energy from the storage unit 105 to be transferred to the load 109. Similarly, the charging profile includes another fraction of energy from one of the renewable energy generator 107 or the grid 103 to be transferred to the storage unit 105. Various embodiments of creating the charging and the discharging profiles and determining respective fractions are elaborated later.
[0064] The at least one control circuit 211 is coupled to the plurality of electrical systems. Thus, the at least one control circuit 211 is coupled to the grid 103, the storage unit 105, the renewable energy generator 107 and the load 109. The at least one control circuit 211 is also coupled to the processor 207 and the energy management module 209. In an embodiment, the energy management module 209 is configured to perform energy channelization, peak shaving and charging/discharging control by sending at least one control signal to the at least one control circuit 211 appropriately. The at least one control circuit 211 is configured to receive the at least one control signal. The at least one control circuit 211 is configured to couple one or more of the electrical systems (including the grid 103, the storage unit 105, the renewable energy generator 107 and the load 109) and transfer energy therebetween based upon the at least one control signal to achieve energy channelization, peak shaving and/or charging/discharging control as desired by the energy management module 209. Various embodiments of the at least one control circuit 211 are explained in conjunction with FIGS. 4 and 5.
[0065] In an embodiment, various functions of the energy management module 209 may be performed by an application hosted on a server. The server may be any remote computer system having processing capability engaged by the energy management module 209. This may allow local processing capacity of the energy management device 101 to be reduced and hence, make the energy management device 101 more compact and power efficient. The application server may be accessible over a network. The network may be, without limitation, the Internet, a local area network, a wide area network and/or a wireless network. The device 101 may include one or more suitable network adaptors (and associated hardware and software) to facilitate exchange of appropriate data between the energy management module 209 and the application server using an appropriate communication protocol over the network. In an embodiment, the device 101 includes one or more of Wi-Fi network adaptors, network adaptors corresponding to one or more 3rd Generation Partnership Project (3GPP) standards such as 2G, 3G, 4G, 5G and Narrowband Internet of Things (NB-IoT). In an embodiment, the application server is a cloud-based server and the device 101 includes an IoT gateway. In an embodiment, the energy management module 209 sends the one or more electrical parameters of the grid 103, the storage unit 105, the renewable energy generator 107 and the load 109 to the application server using a suitable protocol, for example, Message Queue Telemetry Transport (MQQT) via the IoT gateway. The application server then performs functions such as, without limitation, creating the error profiles, performing cross-comparison of the error profiles and calculating the at least two fractions for energy channelization.
[0066] In an embodiment, the energy management module 209 may be accessible via a network to a user device. The user device may be a laptop, a handheld device, such as a mobile phone, a cell phone, a smartphone, a personal digital assistant (PDA), a tablet, etc., a wearable device like a smart watch, an NFC device, etc. The user device may include one or more processors, memories, input/output devices, and a network interface, such as a conventional modem. Further, the device 101 may include location detection capability for example, a GPS receiver, assisted GPS, WiFi networks, etc. The user may provide inputs to the energy management module 209 using input devices (such as a keyboard, a mouse, etc.) on the user device. Further, relevant data provided by the energy management module 209 may be displayed on a display of the user device.
[0067] The device 101 may further include an interface (hardware and/or software) for communicating with the DISCOM 115. In an example implementation, the device 101 includes a Supervisory Control And Data Acquisition (SCADA) interface for communicating with the DISCOM 115.
[0068] FIG. 3 illustrates a schematic block diagram of the energy management module 209, in accordance with an embodiment. The energy management module 209 includes an authorization module 301, a clock module 303, a parameters module 305, a profile module 307, a database 309, an error module 311, a cross-comparison module 313, an energy channelization module 315, a peak shaving module 317 and a charging control module 319.
[0069] The authorization module 301 is configured to receive an authorization by the user for allowing a third party (such as the DISCOM 115) for controlling energy channelization. The authorization module 301 is executed by a processor (e.g., the processor 207). The authorization module 301 is configured to prompt the user (for example, by displaying a prompt on the user device) to authorize the third party. The authorization module 301 may prompt the user once the device 101 is installed at a set-up. Once the authorization is received from the user to authorize the third party, the authorization module 301 may be configured to send set-up details of the device 101 to the third party. The set-up details may include details such as type of the storage unit 105, storage capacity of the storage unit 105, type of renewable energy generator 107, maximum requirement by the load 109, etc. In another embodiment, the third party may be permitted to control energy channelization by default without any special authorization given by the user. In such a case, the authorization module 301 may not be required.
[0070] The clock module 303 is configured to determine (for example, in real-time or at a pre-defined interval) if the time of the day overlaps with the peak and/or off-peak hours. The clock module 303 is executed by the processor (e.g., the processor 207). The peak hours may be classified as first peak hours and second peak hours. In an embodiment, the peak hours during which renewable energy is generated by the renewable energy generator 107 are saved as the first peak hours while the peak hours during which no renewable energy is generated by the renewable energy generator 107 are saved as the second peak hours. For example, when the renewable energy generator 107 is a solar power generator, the first peak hours are one or more hours during the day time and the second peak hours are one or more hours during the night time. In an embodiment, the off-peak hours during which renewable energy is generated by the renewable energy generator 107 are saved as the first off-peak hours while the off-peak hours during which no renewable energy is generated by the renewable energy generator 107 are saved as the second off-peak hours.
[0071] The parameters module 305 is configured to receive or obtain the electrical parameters from the sensor units 203. The parameters module 305 is executed by the processor (e.g., the processor 207) and is coupled to the one or more sensors in the sensor units 203. In an embodiment, the electrical parameters of the grid 103 may include one or more of, voltage, current, power, etc. The electrical parameters of the load 109 may include one or more of, impedance, voltage, current, etc. The electrical parameters of the storage unit 105 may include one or more of, state of charge (SoC), voltage, current, temperature, etc. The electrical parameters of the renewable energy generator 107 may include one or more of, temperature, voltage, current, irradiation (in case of solar energy), etc. The parameters module 305 may obtain the electrical parameters in real-time or at the pre-defined interval.
[0072] The profile module 307 is configured to create a real time profile for each electrical system using values of the electrical parameters of the electrical system received by the parameters module 305. The profile module 307 is executed by the processor (e.g., the processor 207). The profile module 307 may be coupled to the parameters module 305 to fetch the electrical parameters and create the respective real-time profiles for each of the grid 103, the storage unit 105, the renewable energy generator 107 and the load 109. In an embodiment, the profile module 307 generates the following four real-time profiles – a real-time grid profile, a real-time renewable energy profile, a real-time load profile and a real-time storage unit profile, by aggregating values of the set of electrical parameters received from respective sensor units 203. The profile module 307 creates the real-time profiles at the pre-defined interval.
[0073] In an embodiment, the real-time grid profile may include real-time grid voltage (denoted by Vgrtg), real-time grid current (denoted by Agrtg), and real-time grid power (denoted by Wgrtg). In an embodiment, the profile module 307 may calculate Wgrtg using Wgrtg = Vgrtg X Agrtg.
[0074] In one embodiment, when the renewable energy generator 107 is a solar power generator, the real-time renewable energy profile may include real-time PV voltage (denoted by Vpvrtpv), real-time PV current (denoted by Apvrtpv), real-time PV power (denoted by Wpvrtpv), and real-time temperature (denoted by Tpvrt). In an embodiment, the profile module 307 may calculate Wpvrtpv using Wpvrtpv = Vpvrtpv X Apvrtpv.
[0075] In an embodiment, the real time load profile may include real-time load voltage (denoted by Vlrtl), real-time load current (denoted by Alrtl), real-time load power (denoted by Wlrtl), and real-time load impedance (denoted by Zlrtl). In an embodiment, the profile module 307 may calculate Wlrtl using Wlrtl = Vlrtl X Alrtl.
[0076] In an embodiment, the real-time storage unit profile may include real-time battery charging voltage (denoted by Vbcrtbc), real-time battery charging current (denoted by Abcrtbc), real-time battery charging power (denoted by Wbcrtbc), real-time battery charging temperature (denoted by Tbcrt), real-time battery discharging voltage (denoted by Vbdrtbd), real-time battery discharging current (denoted by Abdrtbd), real-time battery discharging power (denoted by Wbdrtbd), real-time battery discharging temperature (denoted by Tbdrt), and real-time state of charge (denoted by SOCbrt). In an embodiment, the profile module 307 may calculate Wbcrtbc and Wbdrtbd using Wbcrtbc = Vbcrtbc X Abcrtbc and Wbdrtbd = Vbdrtbd X Abdrtbd, respectively.
[0077] The database 309 may store various inputs (namely, parameters, profiles, etc.) as received from the profile module 307 and/or the parameters module 305. Further, the database 309 may store a plurality of standard profiles. The standard profiles may include standard profiles of the grid 103 (hereon referred as a standard grid profile), the renewable energy generator 107 (hereon referred as a standard renewable energy profile), the load 109 (hereon referred as a standard load profile) and the storage unit 105 (hereon referred as a storage unit profile).
[0078] Each of the standard profiles may include values of standardized electrical parameters. For example, the standard grid profile may include the standardized (or ideal/expected) values of, one or more of, voltage (denoted by Vgsg), current (denoted by Agsg), power (denoted by Wgsg), etc. of the grid 103. The standard load profile may include the standardized (or ideal/expected) values of, one or more of, impedance (denoted by Zlsl), voltage (denoted by Vlsl), current (denoted by Alsl), power (denoted by Wlsl) etc. of the load 109. The standard storage unit profile may include the standardized (or ideal/expected) values of, one or more of, state of charge (denoted by SOCbst), charging voltage (denoted by Vbcsbc), discharging voltage (denoted by Vbdsbd), charging current (denoted by Abcsbc), discharging current (denoted by Abdsbd), charging power (denoted by Wbcsbc), discharging power (denoted by Wbdsbd), charging temperature (denoted by Tbcsbc), discharging temperature (Tbdsbd) etc. of the storage unit 105. The standard renewable energy profile may include the standardized (or ideal/expected) values of, one or more of, temperature (denoted by Tpvspv), voltage (denoted by Vpvspv), current (denoted by Apvspv), power (denoted by Wpvspv), irradiation (in case of solar energy), etc. of the renewable energy generator 107.
[0079] The standardized values of the standard profiles may be fed to the energy management module 209 by the user during system set-up or may be embedded in the energy management module 209 based upon various system requirements such as, without limitation, types, ratings, and characteristics of various devices, appliances, and/or machines forming the load 109, system settings of the renewable energy generator 107, capacity (say, watt-hour), type, system settings of the storage unit 105, etc. provided by manufacturers of various components of the system 100.
[0080] The database 309 may also store data associated with authorization as received by the authorization module 301. The database 309 may further store the aforesaid real time profiles. The database 309 may also store data associated with historical trends relating to various components, the electrical systems and other site conditions including load profile on real time basis or over a period of time, etc. The historical trends may help in anticipation of the peak demand. The database 309 may also store the peak hours and the off-peak hours based upon the data collected from local distribution companies (DISCOMs or grids). Alternately, the database 309 may store the peak hours and the off-peak hours as defined by the user. The peak hours and the off-peak hours may be fed by the user to the energy management module 209.
[0081] In an embodiment, the accumulated real-time load profile data may be analysed (e.g., by the energy management module 209) and historical trends are generated accordingly to anticipate peak demand. Table 1 shows one example of calculating the anticipated peak demand

Days of Month 1 2 3 4 5 6 7 8 9 10 Avg. Trend
Peak-hours (time) Logged data of Load in KWH
Morning 10am-1 pm 3.6 4.2 3.9 4.1 3.8 3.7 4.2 3.9 4.3 4.1 3.98
Evening 7-9pm 4.5 4.9 4.3 5 4.9 4.2 5.1 4.8 5.2 4.9 4.78

[0082] It is evident from the data above that the anticipated energy demand for the load 109 during the peak hours in the morning is around 4 KWH while during the peak hours in the evening the anticipated energy demand is around 4.8 KWH.
[0083] The error module 311 is configured to generate an error profile for each electrical system based upon the corresponding real-profile and the corresponding standard-profile of the electrical system. The error module 311 is configured to compare the real-time profile of each electrical system and the corresponding standard profile. The error module 311 is executed by the processor (e.g., the processor 207). In the depicted embodiment, the error module 311 is configured to compare the real-time profiles and the standard profiles of the grid 103, the storage unit 105, the renewable energy generator 107 and the load 109. The error module 311 may be coupled to the profile module 307 and the database 309 to retrieve the real-time profiles and the standard profiles, respectively. In an embodiment, the error module 311 may retrieve the real-time profiles from the database 309. In an embodiment, the error module 311 maps the real-time profile of each electrical system with its corresponding standard profile.
[0084] In an embodiment, the standardized values of voltage, current, power in the standard grid profile are compared with the corresponding real-time values of voltage, current, power in the real-time grid profile.
[0085] Likewise, the standardized values of impedance, voltage, current, power in the standard load profile may be compared with the corresponding real-time values of impedance, voltage, current, power in the real-time load profile.
[0086] The standardized values of state of state of charge (SoC), voltage, current, power, temperature in the standard storage unit profile may be mapped with the corresponding real-time values of state of charge (SoC), charging voltage, charging current, charging temperature, charging power, discharging voltage, discharging current, discharging temperature, discharging power in the real-time storage unit profile.
[0087] The standardized values of temperature, voltage, current, power, irradiation in the standard renewable energy profile may be mapped with the corresponding real-time values of temperature, voltage, current, power, irradiation in the real-time renewable energy profile.
[0088] Based upon the comparison, the error module 311 is configured to determine errors or deviations between standardized values in the standard profiles and the corresponding real-time values in the real-time profiles and generate error profiles. The error module 311 generates a renewable energy error profile, a storage unit error profile, a grid error profile and a load error profile.
[0089] According to one embodiment, the error module 311 generates the grid error profile as follows:
[0090] Vgerr = (Vgsg + Vgrtg)/2, where Vgerr denotes grid error profile voltage
[0091] Wgerr = Wgsg – Wgrtg, where Wgerr denotes grid error profile power
[0092] Agerr = Wgerr/Vgerr, where Agerr denotes grid error profile current
[0093] According to one embodiment, the error module 311 generates the load error profile as follows:
[0094] Vlerr = (Vlsl + Vlrtl)/2, where Vlerr denotes load error profile voltage
[0095] Wlerr = Wlsl – Wlrtl, where Wlerr denotes load error profile power
[0096] Alerr = Wlerr/Vlerr, where Alerr denotes load error profile current
[0097] Zlerr = Zlsl + Zlrtl, where Zlerr denotes load error profile impedance
[0098] According to one embodiment, the error module 311 generates the renewable energy error profile (when the renewable energy generator 107 is a solar power generator) as follows:
[0099] Vpverr = (Vpvspv + Vpvrtpv)/2, where Vpverr denotes PV error profile voltage
[00100] Wpverr = Wpvspv – Wpvrtpv, where Wpverr denotes PV error profile power
[00101] Apverr = Wpverr/Vpverr, where Apverr denotes PV error profile current
[00102] Tpverr = Tpvrt - Tpvspv, where Tpverr denotes PV error profile temperature
[00103] According to one embodiment, the error module 311 generates the storage unit error profile. In an embodiment, the error module 311 generates separate storage unit error profiles during charging and discharging. In another embodiment, the storage unit error profile for charging and discharging are the same.
[00104] According to one embodiment, the error module 311 generates the storage unit error profile during charging as follows:
[00105] Vbcerr = (Vbcsbc + Vbcrtbc)/2, where Vbcerr denotes battery charging error profile voltage
[00106] Wbcerr = Wbcsbc – Wbcrtbc, where Wbcerr denotes battery charging error profile power
[00107] Abcerr = Wbcerr/Vbcerr, where Abcerr denotes battery charging error profile current
[00108] Tbcerr = Tbcrt - Tbcsbc, where Tbcerr denotes battery charging error profile temperature
[00109] SOCberr = SOCbst – SOCbrt, where SOCberr denotes error profile battery state of charging
[00110] According to one embodiment, the error module 311 generates the storage unit error profile during discharging as follows:
[00111] Vbderr = (Vbdsbd + Vbdrtbd)/2, where Vbderr denotes battery discharging error profile voltage
[00112] Wbderr = Wbdsbd – Wbdrtbd, where Wbderr denotes battery discharging error profile power
[00113] Abderr = Wbderr/Vbderr, where Abderr denotes battery discharging error profile current
[00114] Tbderr = Tbdrt - Tbdsbd, where Tbderr denotes battery discharging error profile temperature
[00115] SOCberr = SOCbst – SOCbrt
[00116] It should be noted that increase in humidity, temperature and decrease in solar irradiation may directly affect charging (and discharging) characteristics of the storage unit 105 (state of charge) and also, the performance of renewable energy generator 107. Hence, in an embodiment, in addition to the parameters outlined above, the error profiles are generated taking into consideration correction factors of various parameters such as temperature, relative humidity and solar irradiation. The correction factors corresponding to temperature, relative humidity and solar irradiation may be provided by manufacturers of the storage unit 105 and the renewable energy generator 107 and may be saved in the database 309. Therefore, the error profiles on which the functionalities are controlled include components of prevailing temperature, relative humidity and solar irradiation.
[00117] The cross-comparison module 313 is in communication with the error module 311 and the database 309. The cross-comparison module 313 is executed by the processor (e.g., the processor 207). The cross-comparison module 313 is configured to perform a cross-comparison of error profile for two or more electrical systems as generated by the error module 311 and calculate at least two offset error profiles using the error profiles of the two or more electrical systems. For example, the cross-comparison module 313 is configured to calculate an offset error profile corresponding to the storage unit 105 and the renewable energy generator 107 (hereinafter referred to as renewable-storage offset error profile). The renewable-storage offset error profile may include one or more of: renewable-storage current offset error value, renewable-storage voltage offset error value, renewable-storage power offset error value and a renewable-storage temperature offset error value. In an embodiment, the renewable-storage offer error profile may be calculated as follows:
[00118] VferrPVBOv = (Vbcerr - Vpverr)/2, where VferrPVBOv denotes a renewable-storage voltage offset error value
[00119] AferrPVBOv = (Abcerr - Apverr)/2, where AferrPVBOv denotes a renewable-storage current offset error value
[00120] TferrPVBOv = (Tbcerr - Tpverr)/2, where TferrPVBOv denotes a renewable-storage temperature offset error value
[00121] WferrPVBOv = (Wbcerr - Wpverr)/2, where WferrPVBOv denotes a renewable-storage power offset error value
[00122] The cross-comparison module 313 may also be configured to calculate an offset error profile corresponding to the load 109 and the renewable energy generator 107 (hereinafter referred to as renewable-load offset error profile). The renewable-load offset error profile may include one or more of: renewable-load current offset error value, renewable-load voltage offset error value, renewable-load power offset error value and a renewable-load temperature offset error value. In an embodiment, the renewable-load offer error profile may be calculated as follows:
[00123] VferrPVLOv = (Vlerr - Vpverr)/2, where VferrPVLOv denotes a renewable-load voltage offset error value
[00124] AferrPVLOv = (Alerr - Apverr)/2, where AferrPVLOv denotes a renewable-load current offset error value
[00125] WferrPVLOv = (Wlerr - Wpverr)/2, where WferrPVLOv denotes a renewable-load power offset error value
[00126] Offset error profiles for other combinations of the grid 103, the storage unit 105, the renewable energy generator 107 and the load 109 can be calculated similarly.
[00127] The energy channelization module 315 is configured to perform energy channelization between two or more electrical systems of the electrical systems (viz. the grid 103, the storage unit 105, the renewable energy generator 107 and the load 109) based upon the respective error profiles (viz. two or more of the grid error profile, the storage unit error profile, the renewable energy error profile and the load error profile). The energy channelization module 315 is executed by the processor (e.g., the processor 207). The energy channelization module 315 may identify the two or more electrical system to channelize energy therebetween based upon one or more of: the error profiles of the electrical systems, real-time SOC of the storage unit 105 and time of day. In one embodiment, the energy channelization module 315 is configured to perform energy channelization between the two or more electrical systems based upon at least two offset error profiles calculated based upon the cross-comparison of the error profiles of the two or more electrical systems. The energy channelization module 315 may be configured to calculate at least two fractions of energy to be channelized between the two or more electrical systems based upon the error profiles of the two or more electrical systems. In an embodiment, the energy channelization module 315 is configured to calculate the at least two fractions based upon the at least two offset error profiles.
[00128] For example, the energy channelization module 315 may determine that energy channelization needs to be performed between the renewable energy generator 107, the storage unit 105 and the load 109. In that case, the energy channelization modules 315 calculates at least two fractions based upon the renewable-storage offset error profile and the renewable-load offset error profile. In one example implementation, the energy channelization module 315 calculates a first fraction of energy to be channelized from the renewable energy generator 107 to the storage unit 105 and a second fraction of energy to be channelized from the renewable energy generator 107 to the load 109 as below:
[00129] First fraction = WferrPVBOv/(WferrPVBOv + WferrPVLOv)
[00130] Second fraction = WferrPVLOv/(WferrPVBOv + WferrPVLOv)
[00131] Further, the energy channelization module 315 is configured to send at least one control signal to the at least one control circuit 211 based upon the at least two fractions to channelize energy between the two or more electrical systems. Considering the aforesaid example, the energy channelization module 315 sends the at least one control signal to the at least one control circuit 211 to enable a transfer of the first fraction of the renewable energy from the renewable energy generator 107 to the storage unit 105 and the second fraction of the renewable energy from the renewable energy generator 107 to the load 109. In an embodiment, each control signal of the at least one control signal is a Pulse Width Modulation (PWM) signal having a duty cycle. The energy channelization module 315 is configured to adjust the duty cycle of each control signal based upon the at least two fractions. The at least one control circuit 211 includes at least one power semiconductor switching element. The duty cycle of the at least one control signal may be adjusted such that the at least one power semiconductor switching element is configured to transmit energy from its input to its output to the respective duty cycle.
[00132] The energy channelization module 315 is in communication with the authorization module 301. In an embodiment, the energy channelization module 315 performs the energy channelization on receiving a command from at least one of the user or the third party (such as the DISCOM 115). In one embodiment, the energy channelization module 315 (or the authorization module 301) may prompt the third party to enable the energy channelization by sending a pop-up (or any other equivalent signal). In another embodiment, the energy channelization module 315 may prompt the third party only during peak hours when the SOC is above a pre-defined SOC threshold. In another embodiment, the energy channelization module 315 may prompt the third party after passage of a pre-defined time after the cross comparison is performed. The pre-defined time corresponds to a time period during which the energy channelization module 315 waits for the user to enable energy channelization.
[00133] According to an embodiment, the energy channelization module 315 send the at least one control signal in response to receiving the command from at least one of the user (via the user’s device) or the third party (via a computing device of the third party). In an embodiment, once the at least two fractions are calculated, the energy channelization module 315 sends a notification (in the form of a pop-up or the like) to the user’s device and also to the computing device of the third party. In one embodiment, the energy channelization module 315 may send the notification to the third party only when the SOC of the storage unit 105 is above the pre-defined SOC threshold. The pre-defined SOC threshold may range between 80% - 90%. In one example, implementation, the pre-defined SOC threshold is 85%. In an embodiment, the energy channelization module 315 may send the notification to the user’s device first and in case, the user does not enable energy channelization within a pre-defined period of time (for example, one minute) then the notification is sent to the third party.
[00134] In an embodiment, the energy channelization may be controlled remotely (e.g., by the application server deployed remotely to the device 101). In this case, the energy channelization module 315 may be configured to send the real-time profile of each electrical system to a remote server via a communication interface (e.g., Wi-Fi, 3G, 4G, 5G, NB-IoT, SCADA, etc.). The remote server may access other data of the system 100 (such as the standard profiles, system settings, etc.) via the communication interface. In an embodiment, the energy channelization module 315 may be configured to send such data to the remote server via the communication interface. The remote server may then generate the error profiles, perform cross-comparison, generate the offset error profiles and calculate the at least two fractions, etc. The energy channelization module 315 is configured to receive the at least two fractions from the remote server via the communication interface.
[00135] According to an embodiment, the third part may also be enabled to control the energy channelization. Thus, the remote server may be associated with the third party. In this case, the energy channelization module 315 (or the authorization module 301) is configured to display a prompt on a user device of the user to authorize the third party to control the energy channelization. The energy channelization module 315 (or the authorization module 301) is configured to receive an authorization from the user to authorize the third party. When the third party is authorized by the user to control energy channelization, i.e., in response to receiving the authorization from the user, the energy channelization module 315 may send all data obtained and processed by the energy channelization module 315 and/or other modules of the energy management module 209 to the third party via an appropriate interface of the device 101 (e.g., the SCADA interface). For example, the energy channelization module 315 may be configured to send one or more of, the values of the one or more electrical parameters of the electrical systems, the real-time profiles of the electrical systems, the standard profiles of the electrical systems to the third party. The third party may then generate the error profiles, calculate the at least two fractions and send the at least two fractions to the energy channelization module 315. In another embodiment, the energy channelization module 315 may generate the error profiles and send the error profiles to the third party. The third party then calculates the at least two fractions as described. The energy channelization module 315 may then send the at least one control signal to the at least one control circuit 211 as described. Thus, the third part may be enabled to control energy channelization between the plurality of electrical systems.
[00136] The peak shaving module 317 is configured to perform peak shaving based upon the error profiles of the electrical systems and the time of day. The peak shaving module 317 is executed by the processor (e.g., the processor 207). In an embodiment, the clock module 303 is configured to compare the time of day with the peak hours to determine whether the time of day overlaps with the peak hours. The peak shaving module 317, coupled to the clock module 303, is configured to determine at least one electrical system of the plurality of electrical systems to drive the load 109 based upon the error profiles of the plurality of electrical systems when the time of the overlaps with the peak hours and when the load 109 is present. For example, the peak shaving module 317 determines the at least one electrical system based upon the error profiles of the grid 103, the storage unit 105, the renewable energy generator 107 and the load 109. Further, the peak shaving module 317 is configured to send at least one control signal to the at least one control circuit 211 to couple the at least one electrical system to the load 109 to drive the load 109. In an embodiment, 100% of the energy from the at least one electrical system is transferred to the load 109 to drive the load 109. In another embodiment, the peak shaving module 317 may be configured to calculate at least one fraction of energy to be transferred from the at least one electrical system to the load 109 based upon the error profiles of the at least one electrical system and the load 109. The peak shaving module 317 calculates the at least one fraction in a similar manner as how the energy channelization module 315 calculates the at least two fractions. According to an embodiment, each control signal of the at least one control signal is a PWM signal having a duty cycle. The peak shaving module 317 is configured to adjust the duty cycle of each control signal is adjusted based upon the at least one fraction. In this case, the at least one control signal is sent to the at least one control circuit 211 so as to transfer the energy from the at least one electrical system to the load 109 as per the at least one fraction. The peak shaving module 317 determines the at least one electrical system for different scenarios based upon the error profiles of the grid 103, the storage unit 105, the renewable energy generator 107 and the load 109 as follows.
[00137] In an embodiment, the clock module 303 is configured to compare the time of day with the first peak hours to determine whether the time of day overlaps with the first peak hours. When the clock module 303 determines that the time of day overlaps with the first peak hours, the peak shaving module 317 is configured to compare the error profile of the renewable energy generator 107 with the error profile of the load 109. In an embodiment, the peak shaving module 317 compares an error profile power of the renewable energy generator 107 (for example, the PV error profile power Wpverr) with an error profile power of the load 109 (for example, the load error profile power Wlerr). The comparison of the error profile power of the renewable energy generator 107 with the error profile load power of the load 109 is done to check whether the energy from the renewable energy generator 107 is sufficient to drive the load 109.
[00138] When the peak shaving module 317 determines that the error profile power of the renewable energy generator 107 is greater than or equal to the error profile power of the load 109 (indicating that the energy from the renewable energy generator 107 is sufficient to drive the load 109), the peak shaving module 317 is configured to determine the renewable energy generator 107 to drive the load 109. Accordingly, the peak shaving module 317 switches the load 109 to the renewable energy generator 107 by sending the at least one control signal to the at least one control circuit 211 to couple the renewable energy generator 107 to the load 109 to drive the load 109.
[00139] When the peak shaving module 317 determines that the error profile power of the renewable energy generator 107 is less than the error profile load power of the load 109 (indicating that the energy from the renewable energy generator 107 is not sufficient to drive the load 109), the peak shaving module 317 is configured to compare an error profile battery SOC (SOCberr) of the storage unit 105 with a pre-defined SOC error threshold. The comparison of the error profile battery SOC (SOCberr) of the storage unit 105 with the pre-defined SOC error threshold is done to determine whether the storage unit 105 is charged. The pre-defined SOC error threshold may be defined by the user based upon requirements and may be saved in the database 309. The pre-defined SOC error threshold may be between 5% - 20%. In an example implementation, the first SOC error threshold is equal to 15%.
[00140] When the peak shaving module 317 determines that the error profile battery SOC (SOCberr) of the storage unit 105 is less than or equal to the pre-defined SOC error threshold (indicating that the storage unit 105 is charged), the peak shaving module 317 is configured to determine the renewable energy generator 107 and the storage unit 105 to drive the load 109. Accordingly, the peak shaving module 317 switches the load 109 to the renewable energy generator 107 and the storage unit 105 by sending the at least one control signal to couple the renewable energy generator 107 and the storage unit 105 to the load 109. Further, the peak shaving module 317 is configured to calculate a first fraction of energy from the renewable energy generator 107 to be transferred to the load 109 and a second fraction of energy from the storage unit 105 to be transferred to the load 109. The calculation of the first fraction and the second fraction can be done in a similar manner as explained.
[00141] When the peak shaving module 317 determines that the error profile battery SOC of the storage unit 105 is greater than the pre-defined SOC error (indicating that the storage unit 105 is not sufficiently charged), the peak shaving module 317 is configured to determine the renewable energy generator 107 and the grid 103 to drive the load 109. Accordingly, the peak shaving module 317 switches the load 109 to the renewable energy generator 107 and the grid 103 by sending the at least one control signal to couple the renewable energy generator 107 and the grid 103 to the load 109. Further, the peak shaving module 317 is configured to calculate a first fraction of energy from the renewable energy generator 107 to be transferred to the load 109 and a second fraction of energy from the grid 103 to be transferred to the load 109. The calculation of the first fraction and the second fraction can be done in a similar manner as explained. In an embodiment, the peak shaving module 317 may be configured to send the at least one other control signal to the at least one control circuit 211 to disconnect non-critical components of the load 109. This is done to reduce the load 109 and thereby, reduce the energy drawn from the grid 103 as much as possible during the first peak hours.
[00142] When the clock module 303 determines that the time of day does not overlap with the first peak hours, the clock module 303 may be configured to compare the time of day with the second peak hours to determine whether the time of day overlaps with the second peak hours.
[00143] When the clock module 303 determines that the time of day overlaps with the second peak hours, the peak shaving module 317 is configured to compare the error profile battery SOC (SOCberr) of the storage unit 105 with the pre-defined SOC error threshold.
[00144] When the peak shaving module 317 determines that the error profile battery SOC (SOCberr) of the storage unit 105 is less than or equal to the pre-defined SOC error threshold (indicating that the storage unit 105 is sufficiently charged to drive the load 109), the peak shaving module 317 is configured to determine storage unit 105 to drive the load 109. Accordingly, the peak shaving module 317 switches the load 109 to the storage unit 105 by sending the at least one control signal to couple the storage unit 105 to the load 109. Further, the peak shaving module 317 calculates a fraction of energy from the storage unit 105 to be transferred to the load 109 based upon the error profiles of the storage unit 105 and the load 109. The calculation of the fraction can be done in a similar manner as explained.
[00145] When the peak shaving module 317 determines that the error profile battery SOC (SOCberr) of the storage unit 105 is greater than the pre-defined SOC error threshold (indicating that the storage unit 105 is not sufficiently charged to drive the load 109), the peak shaving module 317 is configured to determine the grid 103 to drive the load 109. Accordingly, the peak shaving module 317 switches the load 109 to the grid 103 by sending the at least one control signal to couple the grid 103 to the load 109. Further, the peak shaving module 317 may also send the at least one other control signal to the at least one control circuit 211 to disconnect the non-critical components of the load 109 as explained earlier. This is done to reduce the load 109 and thereby, reduce the energy drawn from the grid 103 as much as possible during the second peak hours.
[00146] According to an embodiment, during the off-peak hours, the peak shaving module 317 may be configured to determine either the renewable energy generator 107 (when the energy from the renewable energy generator 107 is available and is sufficient to drive the load 109), or the grid 103 (when the energy from the renewable energy generator 107 is not available), or the renewable energy generator 107 and the grid 103 (when the energy from the renewable energy generator 107 is available but is not sufficient to drive the load 109) to drive the load 109. The peak shaving module 317 may be configured to send the at least one control signal accordingly. Further, the storage unit 105 may be charged from excess energy drawn from the renewable energy generator 107 and/or the grid 103 after driving the load 109. So, the peak shaving module 317 may be configured to send the at least one control signal accordingly. For example, if the load 109 is switched to the renewable energy generator 107 during the non-peak hours, the peak shaving module 317 may be configured to send the at least one control signal to the at least one control circuit 211 such that the at least one control circuit 211 is configured to transfer energy from the renewable energy generator 107 to the load 109 and to the storage unit 105. This may be done in a similar manner as described in conjunction with FIG. 7.
[00147] The charging control module 319 controls charging and discharging of the storage unit 105. According to an embodiment, the charging control module 319 is configured to control charging and discharging of the storage unit 105 based upon error profile SOC of the storage unit 105 and the time of day. The charging control module 319 is executed by the processor (e.g., the processor 207). The charging control module 319 is coupled with the error module 311 and the clock module 303.
[00148] According to an embodiment, the charging control module 319 is configured to create a charging profile to control charging of the storage unit 105 and a discharging profile to control discharging of the storage unit 105. In an embodiment, the charging control module 319 is configured to create the discharging profile based upon the error profile state of charge (i.e., SOCberr) of the storage unit 105 when time of day overlaps with first peak hours or second peak hours (i.e., during the peak hours). The charging control module 319 is also configured to create a charging profile based upon the error profile state of charge when the time of day overlaps with the first off-peak hours or the second off-peak hours. Further, the charging control module 319 is configured to send at least one control signal to the at least one control circuit 211 based upon one of the discharging profile or the charging profile to discharge or charge the storage unit 105, respectively. The at least one control circuit 211 is configured to couple one of the renewable energy generator 107, the grid 103 or the load 109 to the storage unit 105 as per the at least one control signal to charge or discharge the storage unit 105 as per the charging and discharging profile, respectively. In an embodiment, the charging profile includes a fraction of energy from the storage unit 105 to be transferred to the load 109 and the discharging profile includes another fraction of energy from one of the renewable energy generator 107 or the grid 103 to be transferred to the storage unit 105. According to an embodiment, each control signal of the at least one control signal is a PWM signal having a duty cycle. In an embodiment, the charging control module 319 is configure to adjust the duty cycle of each control signal based upon the fraction and the other fraction so that a fraction of energy may be transferred to the storage unit 105 to charge the storage unit 105 or from the storage unit 105 to discharge the storage unit 105. The at least one control circuit 211 is configured to transfer the fractional energy from and to the storage unit 105 based upon the at least one control signal as explained later. The creation of the charging profile and the discharging profile and determination of the corresponding fraction is further elaborated below.
[00149] When the time of day overlaps with the first peak hours, the charging control module 319 is configured to compare the error profile SOC (SOCberr) with a first SOC error threshold. The first SOC error threshold may be between 10% - 20%. In an example implementation, the first SOC error threshold is 15%.
[00150] When the SOCberr is less than or equal to the first SOC error threshold (indicating that the storage unit 105 is sufficiently charged), the charging control module 319 is configured to compare a renewable error power profile (e.g., PV error profile power Wpverr) with a renewable power error threshold. The renewable power error threshold may be defined by the user based upon system requirements, characteristics of the renewable energy generator 107 (type, capacity, etc.), load requirements, etc. In an example implementation, the renewable power error threshold is 1000W.
[00151] When the renewable error power profile is less than or equal to the renewable power error threshold (indicating that more energy from the renewable energy generator 107 is available), the charging control module 319 is configured to determine a first fraction of energy from the storage unit 105 to be transferred to the load 109 and a second fraction of energy from the renewable energy generator 107 to be transferred to the load 109. The charging control module 319 is configured to create the discharging profile having the first fraction and the second fraction. The first fraction may range between 10% - 20% and the second fraction may range between 80% - 90%. In an example implementation, the first fraction is 15% and the second fraction is 85%.
[00152] When the renewable error power profile is greater than the renewable power error threshold (indicating that less energy from the renewable energy generator 107 is available), the charging control module 319 is configured to determine a third fraction of energy from the storage unit 105 to be transferred to the load 109 and a fourth fraction of energy from the renewable energy generator 107 to be transferred to the load 109. The third fraction is greater than the first fraction and the fourth fraction is smaller than the second fraction. The charging control module 319 is configured to create the discharging profile having the third and the fourth fraction. The third fraction may range between 45% - 55% and the fourth fraction may range between 45% - 55%. In an example implementation, the third fraction is 50% and the fourth fraction is 50%.
[00153] In this manner, the charging control module 319 uses the energy from the renewable energy generator 107 along with the energy from the storage unit 105 to drive the load 109 during the peak hours when the energy from the renewable energy generator 107 is available, thereby reducing burden on the storage unit 105 to drive the load 109. Further, the charging control module 319 ensures that less energy is drawn from the storage unit 105 when more energy from the renewable energy generator 107 is available. This leads to the storage unit 105 discharging at a slower rate. Consequently, the storage unit 105 remains charged for a longer duration, thereby reducing the charging frequency of the storage unit 105.
[00154] Thus, the discharging of the storage unit 105 commences during the first peak hours. The charging control module 319 continuously monitors the SOC of the storage unit 105. For example, the charging control module 319 is configured to compare, when the SOCberr is greater than the first SOC error threshold, the SOCberr with a second SOC error threshold. The SOCberr is compared with the second SOC error threshold to determine whether the storage unit 105 is significantly discharged. The second SOC threshold is greater than the first SOC threshold. The second SOC threshold may range between 80% - 90%. In an example implementation, the second SOC threshold is 85%.
[00155] When the SOCberr is greater than or equal to the second SOC error threshold (indicating that the storage unit 105 is significantly discharged during the first peak hours), the charging control module 319 is configured to determine a fifth fraction of energy from the renewable energy generator 107 to be transferred to the storage unit 105 and a sixth fraction of energy from the renewable energy generator 107 to be transferred to the load 109 based upon the renewable power error profile and a load power error profile of the load 109. The charging control module 319 may determine the fifth and the sixth fraction in a similar manner as described in FIGS. 6-7. The charging control module 319 is configured to create the charging profile having the fifth fraction and the sixth fraction. Thus, the charging control module 319 ensures that the storage unit 105 is charged through the renewable energy generator 107 when the storage unit 105 is significantly discharged during the first peak hours.
[00156] When the time of day overlaps with the second peak hours (i.e., when the energy from the renewable energy generator 107 is not available), the charging control module 319 is configured to compare the SOCberr with the first SOC error threshold, the second SOC error threshold and a third SOC error threshold. The third SOC error threshold is greater than the first SOC error threshold and less than the second SOC error threshold. The SOCberr is compared with the first, the second and the third SCO error thresholds to determine SOC status of the storage unit 105. The third SOC error threshold may range between 45% - 55%. In an example implementation, the third SOC error threshold is 50%.
[00157] The charging control module 319 is configured to determine one of a seventh, an eights or nineth fraction of energy from the storage unit 105 to be transferred to the load 109 based upon the comparison. In an embodiment, the charging control module 319 is configured to determine the seventh fraction of energy from the storage unit 105 to be transferred to the load 109 when the SOCberr is less than or equal to the first SOC error threshold (indicating that the storage unit 105 is charged). The charging control module 319 is configured to determine the eighth fraction of energy from the storage unit 105 to be transferred to the load 109 when the SOCberr is greater than the first SOC error threshold and less than or equal to the third SOC error threshold. The charging control module 319 is configured to determine the ninth fraction of energy from the storage unit 105 to be transferred to the load 109, when the SOCberr is greater than the third SOC error threshold and less than or equal to the second SOC error threshold. The seventh fraction is greater than the eighth fraction and the eighth fraction is greater than the ninth fraction. The seventh fraction may range between 80% - 90%. The eighth fraction may range between 45% - 55%. The ninth fraction may range between 10% - 20%. In an example implementation, the seventh fraction, the eighth fraction and the ninth fraction are 85%, 50% and 15%, respectively. The charging control module 319 creates the discharging profile having one of the seventh fraction, the eighth fraction and the ninth fraction. As can be seen, the charging control module 319 ensures that lesser power is drawn from the storage unit 105 when the SOC of the storage unit 105 is lower, thereby extending the duration for which the storage unit 105 remains charged.
[00158] Thus, the discharging of the storage unit 105 commences during the second peak hours. The charging control module 319 continuously monitors the SOC of the storage unit 105 via the comparison of the SOCberr with the first, the second and the third SOC error thresholds. When the SOCberr is greater than the second SOC error threshold (indicating that the storage unit 105 is significantly discharged), the charging control module 319 is configured to determine a tenth fraction of energy from the grid 103 to be transferred to the storage unit 105 and an eleventh fraction of energy from the grid 103 to be transferred to the load 109 based upon a grid error profile of the grid 103 and a load power error profile of the load 109. The charging control module 319 may determine the tenth and the eleventh fraction in a similar manner as described in FIGS. 6-7. The charging control module 319 is configured to create the charging profile having the tenth fraction and the eleventh fraction. Thus, the charging control module 319 ensures that the storage unit 105 is charged through the grid 103 when the storage unit 105 is significantly discharged during the second peak hours.
[00159] When the time of day overlaps with the first off-peak hours, the charging control module 319 is configured to compare the SOCberr with the second SOC error threshold to check whether the storage unit 105 is significantly discharged. When the charging control module 319 determines that the SOCberr is greater than the second SOC error threshold (indicating that the storage unit 105 is significantly discharged), the charging control module 319 is configured determine a twelfth fraction of energy from the renewable energy generator 107 to be transferred to the storage unit 105 and a thirteenth fraction of energy from the renewable energy generator 107 to be transferred to the load 109 based upon the renewable power error profile and the load power error profile. The charging control module 319 may determine the twelfth fraction and the thirteenth fraction in a similar manner as described in FIGS. 6-7. The charging control module 319 is configured to create the charging profile having the twelfth fraction and the thirteenth fraction. Thus, the charging control module 319 begins charging the storage unit 105 using energy from the renewable energy generator 107 when the storage unit 105 is sufficiently discharged. The charging control module 319 continuously monitors the SOC of the storage unit 105. When the storage unit 105 is sufficiently charged, for example, when the SOCberr reaches the first SOC error threshold, the charging control module 319 may stop the charging of the storage unit 105.
[00160] When the time of day overlaps with the second off-peak hours, the charging control module 319 is configured to compare the SOCberr with the second SOC error threshold to check whether the storage unit 105 is significantly discharged. When the charging control module 319 determines that the SOCberr is greater than the second SOC error threshold (indicating that the storage unit 105 is significantly discharged), the charging control module 319 is configured to determine a fourteenth fraction of energy from grid 103 to be transferred to the storage unit 105 and a fifteenth fraction of energy from the grid 103 to be transferred to the load 109 based upon the grid error profile and the load power error profile. The charging control module 319 may determine the fourteenth fraction and the fifteenth fraction in a similar manner as described in FIGS. 6-7. The charging control module 319 is configured to create the charging profile having the fourteenth fraction and the fifteenth fraction. Thus, the charging control module 319 begins charging the storage unit 105 using energy from the grid 103 when the storage unit 105 is sufficiently discharged. The charging control module 319 continuously monitors the SOC of the storage unit 105. When the storage unit 105 is sufficiently charged, for example, when the SOCberr reaches the first SOC error threshold, the charging control module 319 may stop the charging of the storage unit 105.
[00161] Thus, the charging control module 319 facilitates that the storage unit 105 is charged using the renewable energy generator 107 or the grid 103 during the off-peak hours as much as possible, when the electricity is cheaper. The charging control module 319 ensures that the storage unit 105 is not generally charged during the peak hours when the electricity is expensive. The charging control module 319 also facilitates that the storage unit 105 is discharged (i.e., used to drive the load 109) during the peak hours to avoid drawing additional power from the grid 103 (which is expensive in the peak hours). In addition, the charging control module 319 avoids frequent charging by initiating the charging operation only when the storage unit 105 is discharged (as indicated by the SOCberr being greater than the second SOC error threshold). Further, during the discharging of the storage unit 105, the charging control module 319 exploits the energy from the renewable energy generator 107 as much as possible. The charging control module 319 also adjusts energy drawn from the storage unit 105 depending upon available energy from the renewable energy generator 107. This prevents unnecessary discharge of the storage unit 105 and thereby, increasing the time duration between two charging cycles of the storage unit 105. This improves the performance and the life of the storage unit 105.
[00162] FIG. 4 illustrates a schematic block diagram of the at least one control circuit 211 according to an embodiment. For the sake of brevity, other components of the device 101 are omitted. In an embodiment, the at least one control circuit 211 includes a first control circuit 211a, a second control circuit 211b, a third control circuit 211c and the fourth control circuit 211d. The first control circuit 211a includes a control input 211a1, an input 211a2 and an output 211a3. The second control circuit 211b includes a control input 211b1, an input 211b2 and an output 211b3. The third control circuit 211c includes a control input 211c1, an input 211c2 and an output 211c3. The fourth control circuit 211d includes a control input 211d1, an input 211d2 and an output 211b3. Each control circuit of the at least one control circuit 211 includes at least one power semiconductor switching element. The at least one power semiconductor switching element may be an Insulated Gate Bipolar Transistor (IGBT), a power Metal Oxide Semiconductor Field Effect Transistor (MOSFET) or a thyristor. In an example implementation, the at least one power semiconductor switching element includes at least one IGBT. In an embodiment, the at least one control signal includes a first control signal, a second control signal, a third control signal and a fourth control signal.
[00163] The first control circuit 211a is coupled to the grid 103. The input 211a2 is coupled to the grid 103, for example, via the input port 201a. The output 211a3 is coupled to the input 211d2 of the fourth control circuit 211d. The control input 211a1 is coupled to the processor 207 to receive the first control signal.
[00164] The second control circuit 211b is coupled to the renewable energy generator 107. The input 211b2 is coupled to the renewable energy generator 107 via the invertor 113 and the input port 201c. The output 211b3 is coupled to the input 211c2 of the third control circuit 211c. The control input 211b1 is coupled to the processor 207 to receive the second control signal.
[00165] The third control circuit 211c is coupled to the storage unit 105. The input 211c2 is coupled to the storage unit 105 via the bi-directional converter 111 and the input port 201b. The input 211c2 is also coupled to the output 211b3 of the second control circuit 211b. The output 211c3 is coupled to the input 211d2 of the fourth control circuit 211d. The control input 211c1 is coupled to the processor 207 to receive the third control signal.
[00166] The fourth control circuit 211d is coupled to the load 109. The input 211d2 is to the output 211a3 of the first control circuit 211a and the output 211c3 of the third control circuit 211c. The output 211d3 is coupled to the load 109 via the input port 201d. The control input 211d1 is coupled to the processor 207 to receive the fourth control signal.
[00167] The first control circuit 211a, the second control circuit 211b, the third control circuit 211c and the fourth control circuit 211d are configured to allow current to flow in both directions i.e., from a respective input to a respective output and vice versa. An embodiment of how such a configuration can be achieved is explained with respect to FIG. 5.
[00168] In an embodiment, the at least one control circuit 211 may further include a fifth control circuit (not shown) coupled to the non-critical components of the load 109. The fifth control circuit includes an input, an output and a control input. The control input of the fifth control circuit is coupled to the processor 207 to receive the at least one other control signal, say a fifth control signal. The input of the fifth control circuit is coupled to the Node A and the output of the fifth control circuit is coupled to the non-critical components of the load 109. In one example implementation, the fifth control circuit includes at least one Isolated Gate Bipolar Transistor (IGBT). In an embodiment, the fifth control signal is a Pulse Width Modulation (PWM) signal. In this case, the fifth control signal may be the PWM signal with zero duty cycle so as to disconnect the non-critical components of the load 109 as directed by the peak shaving module 317.
[00169] A few examples of how the energy channelization module 315 performs energy channelization by sending the at least one control signal and how the at least one control circuit 211 is configured to channelizes energy in response to the at least one control signal is now explained with reference to FIG. 3.
[00170] Example 1: the energy channelization module 315 determines that the energy is to be channelized from the grid 103 to the load 109 and the storage unit 105. Further, the energy channelization module 315 calculates that 85% (a first fraction) of energy from the grid 103 is to be channelized to the load 109 and 15% (a second fraction) of energy from the grid 103 is to be channelized to the storage unit 105 based upon cross-comparison of the error profiles of the grid 103, the storage unit 105 and the load 109. Based upon the calculated first fraction and the second fraction, the energy channelization module 315 sends the at least one control signal as follows. The first control signal is a PWM signal with 100% duty cycle, the second control signal is a PWM signal with 0% duty cycle, the third control signal is a PWM signal with 0% duty cycle and the fourth control signal is a PWM signal with 85% duty cycle. As a result, the at least one IGBT of the first control circuit 211a is switched ON and 100% energy of the grid 103 flows from the input 211a2 to the output 211a3 and is available at Node A. Since the fourth control signal has the duty cycle of 85%, the at least one IGBT of the fourth control circuit 211d is switched ON and 85% of the energy available at the input 211d2 is transferred to the output 211d3. Thus, 85% of the energy of the grid 103 is channelized to the load 109. Further, since both the second and the third control signals have 0% duty cycle, the at least one IGBTs of the second control circuit 211b and the third control circuit 211c are switched OFF. The 15% energy from the grid 103 is available at Node B from the output 211c3 to the input 211c2 of the third control circuit 211c. A battery management system (not shown) of the storage unit 105 ensures that the storage unit 105 draws this 15% energy of the grid 103 via the bi-directional converter 111. The energy channelization module 315 may cause the processor 207 to disconnect the inverter 113 via a relay (not shown) so that the renewable energy generator 107 does not draw any power from Node B (via the output 211b3 to the input 211b2). Thus, 85% of energy from the grid 103 is channelized to the load 109 and 15% of energy from the grid 103 is channelized to the storage unit 105.
[00171] Example 2: the energy channelization module 315 determines that the energy is to be channelized from the renewable energy generator 107 to the load 109 and the storage unit 105. Further, the energy channelization module 315 calculates that 75% (a first fraction) of energy from the renewable energy generator 107 is to be channelized to the storage unit 105 and 25% (a second fraction) of energy from the renewable energy generator 107 is to be channelized to the load 109 based upon cross-comparison of the error profiles of the renewable energy generator 107, the storage unit 105 and the load 109. Based upon the calculated first fraction and the second fraction, the energy channelization module 315 sends the at least one control signal as follows. The first control signal is a PWM signal with 0% duty cycle, the second control signal is a PWM signal with 100% duty cycle, the third control signal is a PWM signal with 25% duty cycle and the fourth control signal is a PWM signal with 100% duty cycle. As a result, the at least one IGBT of the first control circuit 211a is switched OFF and there is no energy from the grid 103 at Node A. The energy channelization module 315 may cause the processor 207 to disconnect the grid 103 so that there is no reverse flow from the output 211a3 to the input 211a2. The at least one IGBT of the second control circuit 211b is switched ON and 100% of energy from the renewable energy generator 107 is transferred from the input 211b2 to the output 211b3. The at least one IGBT of the third control circuit 211c is switched ON and due to the 25% duty cycle, 25% of energy at Node B is available at Node A. The at least one IGBT of the fourth control circuit 211d is switched ON and 100% of energy from Node A is transferred from the input 211d2 to the output 211d3, thereby to the load 109. The battery management system of the storage unit 105 ensures that the storage unit 105 draws remaining 75% energy from Node B via the bi-directional converter 111. Thus, 75% of energy from the renewable energy generator 107 is channelized to the storage unit 105 and 25% energy from the renewable energy generator 107 is channelized to the load 109.
[00172] It should be appreciated that the above examples are described for illustration purpose only. The at least one control signal with appropriate duty cycle may be sent suitably by the energy channelization module 315 to the at least one control circuit 211 under various other scenarios to achieve optimal energy channelization.
[00173] Various examples of how the peak shaving module 317 performs peak shaving by sending the at least one control signal and how the at least one control circuit 211 is configured to facilitate peak shaving in response to the at least one control signal is now explained with reference to FIG. 3.
[00174] Example 1: the peak shaving module 317 determines the renewable energy generator 107 to drive the load 109 and therefore, the load 109 is to be switched to the renewable energy generator 107. In an embodiment, the peak shaving module 317 may also determine that 100% of the energy from the renewable energy generator 107 is to be transferred to drive the load 109. Based upon this, the peak shaving module 317 sends the at least one control signal as follows. The first control signal is a PWM signal with 0% duty cycle, the second control signal is a PWM signal with 100% duty cycle, the third control signal is a PWM signal with 100% duty cycle and the fourth control signal is a PWM signal with 100% duty cycle. As a result, the at least one IGBT of the first control circuit 211a is switched OFF and no energy is drawn from the grid 103. Further, since the second, the third control and the fourth control signal have 100% duty cycle, the at least one IGBTs of the second control circuit 211b, the third control circuit 211c and the fourth control circuit 211d are switched ON. Thus, the renewable energy generator 107 is coupled to the load 109 via the second control circuit 211b, the third control circuit 211c and the fourth control circuit 211d and 100% of the energy from the renewable energy generator 107 is transferred to the load 109 to drive the load 109.
[00175] Example 2: the peak shaving module 317 determines the storage unit 105 to drive the load 109 and therefore, the load 109 is to be switched to the storage unit 105. In an embodiment, the peak shaving module 317 may also determine that 75% of the energy from the storage unit 105 is to be transferred to drive the load 109. Based upon this, the peak shaving module 317 sends the at least one control signal as follows. The first control signal is a PWM signal with 0% duty cycle, the second control signal is a PWM signal with 0% duty cycle, the third control signal is a PWM signal with 75% duty cycle and the fourth control signal is a PWM signal with 100% duty cycle (or the third control signal is a PWM signal with 100% duty cycle and the fourth control signal is a PWM signal with a 75% duty cycle). As a result, the at least one IGBT of the first control circuit 211a is switched OFF and no energy is drawn from the grid 103. The peak shaving module 317 may disconnect the grid 103 so that there is no reverse flow from the output 211a3 to the input 211a2. The at least one IGBT of the second control circuit 211b is switched OF and no energy from the renewable energy generator 107 is transferred from the input 211b2 to the output 211b3. The at least one IGBT of the third control circuit 211c is switched ON and because of 75% duty cycle of the third control signal, 75% of energy from the storage unit 105 is available at Node A (or 100% of the energy from the storage unit 105 is available at Node B if the third control signal has 100% duty cycle). The at least one IGBT of the fourth control circuit 211d is switched ON and because of 100% duty cycle of the fourth control signal, 100% of energy from Node A is transferred from the input 211d2 to the output 211d3 (or 75% of energy from Node A if the fourth control signal has 75% duty cycle). The peak shaving module 317 may disconnect the inverter 113 via a relay (not shown) so that the renewable energy generator 107 does not draw any power from Node B (via the output 211b3 to the input 211b2). Thus, the storage unit 105 is coupled to the load 109 via the third control circuit 112c and the fourth control circuit 112d and 75% of energy from storage unit 105 is transferred to the load 109 to drive the load 109.
[00176] It should be appreciated that the above examples are described for illustration purpose only. The at least one control signal with appropriate duty cycle may be sent suitably by the peak shaving module 317 to the at least one control circuit 211 under various other scenarios to achieve optimal peak shaving.
[00177] A few examples of how the charging control module 319 sends the at least one control signal based upon the charging profile and the discharging profile and how the at least one control circuit 211 is configured to couple one of the renewable energy generator 107, the grid 103 and the load 109 with the storage unit 105 for charging/discharging of the storage unit 105 in response to the at least one control signal are now explained with reference to FIG. 3.
[00178] Example 1: the charging control module 319 determines, during the first peak hours, that the SOCberr is less than the first SOC error threshold and the renewable error power profile is less than the renewable power error threshold. The charging control module 319 then determines that the first fraction and the second fraction are 50%, as explained in FIG. 3. Based upon the determined third fraction and the fourth fraction, the charging control module 319 sends the at least one control signal as follows. The first control signal is a PWM signal with 0% duty cycle, the second control signal is a PWM signal with 50% duty cycle, the third control signal is a PWM signal with 100% duty cycle and the fourth control signal is a PWM signal with 100% duty cycle. As a result, the at least one IGBT of the first control circuit 211a is switched OFF and no energy is drawn from the grid 103. The charging control module 319 may disconnect the grid 103 so that there is no reverse flow from the output 211a3 to the input 211a2. The at least one IGBT of the second control circuit 211b is switched ON and because of 50% duty cycle, 50% of energy from the renewable energy generator 107 is transferred from the input 211b2 to the output 211b3. The charging control module 319 may communicate with the battery management system of the storage unit 105 that 50% of power from the storage unit 105 is required. The battery management system controls the bi-directional converter 111 to provide the desired power. As a result, 50% of energy from the storage unit 105 is available at Node B. The at least one IGBT of the third control circuit 211c is switched ON and 100% of energy at Node B is available at Node A. The at least one IGBT of the fourth control circuit 211d is switched ON and because of 100% duty cycle of the fourth control signal, 100% of energy from Node A is transferred from the input 211d2 to the output 211d3, thereby to the load 109. Thus, 50% of energy from the renewable energy generator 107 and 50% of energy from the storage unit 105 is transferred to the load 109.
[00179] Example 2: the charging control module 319 determines, during the second off-peak hours, that the SOCberr is greater than the second SOC error threshold. Further, the charging control module 319 may determine that the fourteenth fraction and the fifteenth fraction are 55% and 45%, respectively. Based upon the calculated first fraction and the second fraction, the charging control module 319 sends the at least one control signal as follows. The first control signal is a PWM signal with 100% duty cycle, the second control signal is a PWM signal with 0% duty cycle, the third control signal is a PWM signal with 0% duty cycle and the fourth control signal is a PWM signal with 45% duty cycle. As a result, the at least one IGBT of the first control circuit 211a is switched ON and 100% energy of the grid 103 flows from the input 211a2 to the output 211a3 and is available at Node A. Since the fourth control signal has the duty cycle of 45%, the at least one IGBT of the fourth control circuit 211d is switched ON and 45% of the energy available at the input 211d2 is transferred to the output 211d3. Thus, 45% of the energy of the grid 103 is channelized to the load 109. Further, since both the second and the third control signals have 0% duty cycle, the at least one IGBTs of the second control circuit 211b and the third control circuit 211c are switched OFF. The 55% energy from the grid 103 is available at Node B from the output 211c3 to the input 211c2 of the third control circuit 211c. A battery management system (not shown) of the storage unit 105 ensures that the storage unit 105 draws this 55% energy of the grid 103 via the bi-directional converter 111. The charging control module 319 may disconnect the inverter 113 via a relay (not shown) so that the renewable energy generator 107 does not draw any power from Node B (via the output 211b3 to the input 211b2). Thus, the storage unit 105 is charged with 55% of energy from the grid 103 and the remaining 45% of the energy from the grid 103 is used to drive the load 109.
[00180] It should be appreciated that the above examples are described for illustration purpose only. The at least one control signal with appropriate duty cycle may be sent suitably by the charging control module 319 to the at least one control circuit 211 under various other scenarios to achieve optimal charging and discharging of the storage unit 105.
[00181] According to an embodiment, the first control circuit 211a, the second control circuit 211b, the third control circuit 211c and the fourth control circuit 211d are implemented in a similar fashion. Without loss of generality, any one control circuit of the control circuit 211 may be referred to as a control circuit 211n. FIG. 5 illustrates a schematic circuit diagram of the control circuit 211n according to an embodiment. The first control circuit 211a, the second control circuit 211b, the third control circuit 211c and the fourth control circuit 211d may be implemented using the control circuit 211n. The control circuit 211n includes a control input 211n1, an input 211n2 and an output 211n3. The control input 211n1 is coupled to the processor 207 to receive a corresponding control signal of the at least one control signal. The control circuit 211n includes at least one power semiconductor switching element 503. In the depicted embodiment, the control circuit 211n includes a first IGBT 505 and a second IGBT 509 connected in series with the first IGBT 505. The first IGBT 505 and the second IGBT 509 are connected in series improve voltage capacity of the control circuit 211n. The first IGBT 505 includes a gate terminal 505a, a collector terminal 505b and an emitter terminal 505c. The second IGBT 509 includes a gate terminal 509a, a collector terminal 509b and an emitter terminal 509c. The collector terminal 505b of the first IGBT 505 is coupled to the input 211n2 of the control circuit 211n. The emitter terminal 505c of the first IGBT 505 is coupled to the collector terminal 509b of the second IGBT 509. The emitter terminal 509c of the second IGBT 509 is coupled to the output 211n3 of the control circuit 211n. The control circuit 211n further includes a first diode 507 connected between the collector terminal 505b and the emitter terminal 505c of the first IGBT 505, and a second diode 511 connected between the collector terminal 509b and the emitter terminal 509c of the second IGBT 509 as shown. The first diode 507 and the second diode 511 provide a path for the flow of current in a reverse direction (i.e., from the output 211n3 to the input 211n2).
[00182] The control circuit 211n further includes a driver circuit 501 configured to drive the at least one power semiconductor switching element 503. An input of the driver circuit 501 is coupled to the control input 211n1 of the control circuit 211n. The driver circuit 501 includes at least one output coupled to the at least one power semiconductor switching element 503. In the depicted embodiment, the driver circuit 501 includes a first output 501e1 and a second output 501e2 coupled to the gate terminal 505a of the first IGBT 505 and the gate terminal 509a of the second IGBT 509, respectively. The driver circuit 501 can be any suitable circuit capable of driving the first IGBT 505 and the second IGBT 509. In one example implementation, the driver circuit 501 includes a photo coupler 501a (such as TLP5231 by Texas Instruments) and a buffer amplifier 501b. The photo coupler 501a receives the control signal, converts the control signal to an optical signal and converts the optical signal to an electrical signal. The photo coupler 501a provides isolation and a high common mode transient immunity for driving the first IGBT 505 and the second IGBT 509. The buffer amplifier 501b amplifies electrical signal output by the photo coupler 501a to desired current levels suitable for the first IGBT 505 and the second IGBT 509. In an embodiment, the buffer amplifier 501b includes a P-channel MOSFET and an N-channel MOSFET. The photo coupler 501a drives the gate terminal 505a and the gate terminal 509a via the buffer amplifier 501b. By varying the size of the buffer amplifier 501b, gate current required by various power semiconductor switching elements 503 can be designed. The driver circuit 501 may include additional circuitry for improved functioning of the control circuit 211n. For example, the driver circuit 501 may include a circuit to detect a short-circuit condition and a soft-turn OFF control circuit to soft-turn OFF the first IGBT 505 and the second IGBT 509 when a short-circuit condition is detected.
[00183] It should be appreciated that the control circuit 211n may include more than two IGBTs connected in series. In an embodiment, instead of more than one IGBTs connected in series (as illustrated in FIG. 5), the control circuit 211n may include more than one IGBTs connected in parallel for improved current capacity. Further, in an embodiment, the control circuit 211n may include one or more IGBTs connected in series, which are in turn connected with one or more IGBTs in parallel.
[00184] FIG. 6 of the present disclosure illustrates a flowchart of a method 600 for energy channelization according to an embodiment. Though the steps of the method 600 have been described as performed by specific modules of the energy management module 209, it should be understood that the step may be performed by other modules of the energy management module 209 or by the energy management module 209.
[00185] At step 601, one or more electrical parameters (hereinafter, electrical parameters) of a plurality of electrical systems (hereinafter, electrical systems) are obtained by the parameters module 305. The electrical systems includes the grid 103, the storage unit 105, the renewable energy generator 107 and the load 109. As mentioned above, the electrical parameters of the grid 103 may include one or more of voltage, current, power, etc. The electrical parameters of the load 109 may include one or more of impedance, voltage, current, power, etc. The electrical parameters of the renewable energy generator 107 may include one or more of temperature, voltage, current, power, irradiation (in case of solar energy), etc. The electrical parameters of the storage unit 105 may include one or more of state of charge (SoC), voltage, current, power, temperature, etc. The electrical parameters of the electrical systems may be obtained from respective one or more sensors (such as sensor units 203). The electrical parameters may be obtained in real-time or at a pre-defined interval, for example, every 10 seconds. The user may pre-configure the pre-defined interval (say, ranging from 1 second to 30 seconds) depending upon the requirement for obtaining the electrical parameters.
[00186] In an embodiment, all electrical parameters values used for channelizing energy are received by the parameters module 305. In some embodiments, using the real-time values of some electrical parameters obtained as inputs, the parameters module 305 may derive (or predict) the real-time values of other electrical parameters that are not received. As an exemplary embodiment, such a derivation may be performed using a plurality of look-up tables as stored in the database 309. For example, the parameters module 305 may derive the real-time value of the SOC of the storage unit 105 based upon real-time voltage of the storage unit 105 using a look-up table. The real-time values of voltage may be mapped with pre-fed values of voltage in the look-up table and accordingly the value of SOC corresponding to the voltage is considered as the real-time SOC. It should be noted that each look-up table may be specific to the type of storage unit 105 utilized (say, Lithium-ion battery, lead acid battery, etc.). In another exemplary embodiment, the real-time values of power for an electrical system may be calculated my multiplying real-time values of the current and the voltage of the electrical system.
[00187] At step 603, a real-time profile is created for each electrical system of the plurality of electrical systems by the profile module 307 using the real-time values (or values obtained at the pre-defined interval) of the electrical parameters for the electrical system. Accordingly, a real-time profile for the grid 103 (referred to as a real-time grid profile), a real-time profile for the storage unit 105 (referred to as a real-time storage unit profile), a real-time profile of the renewable energy generator 107 (referred to as a real-time renewable energy profile) and a real-time profile of the load 109 (referred to as a real-time load profile) are generated by the profile module 307. In an embodiment, the real-time profiles are generated at the pre-defined interval.
[00188] At step 605, an error profile is generated for each electrical system of the plurality of electrical systems based upon the corresponding real-time profile and a corresponding standard profile of the electrical system by the error module 311. In an embodiment, the error profile for each electrical system may be generated at the pre-defined interval. Each of the standard profiles relating to the renewable energy generator 107 (referred to as a standard renewable energy profile), the storage unit 105 (referred to as a standard storage unit profile), the grid 103 (referred to as a standard grid profile) and the load 109 (referred to as a standard load profile) may be stored in the database 309. The standardized values of the electrical parameters in the standard profiles may be pre-fed to the energy management module 209 of the present disclosure by a user or may be embedded in the energy management module 209. The standard profiles may be created and stored based upon factors such as system requirements, requirements of the load 109, specifications of the renewable energy generator 107, the storage unit 105, the grid 103, operational requirements, etc. The standard profiles may be created and stored by one of the user or the third party.
[00189] In an embodiment, values of the electrical parameters in the real-time profiles are compared with corresponding standardized values of the electrical parameters in the standard profile and a deviation between the real-time values and the standardized values of the electrical parameters are calculated to generate the error profiles. In an embodiment, the error profiles include the calculated deviations. Accordingly, error profiles of the grid 103 (referred to as a grid error profile), the storage unit 105 (referred to as a storage unit error profile), the renewable energy generator 107 (referred to as a renewable energy error profile) and the load 109 (referred to as a load error profile) are generated.
[00190] As an exemplary embodiment, the standardized values of voltage, current, power, etc. as included in the standard grid profile are compared with the corresponding real-time values of voltage, current, power, etc. as included in the real-time grid profile. On comparison, a deviation of the real-time value of voltage from the standardized voltage is derived. Likewise, deviation of the real-time values of current and power from the standardized values of current and power are derived. An example of the grid error profile, thus generated, is given in Table 2 below.
Electrical parameter Standard grid profile Real-time grid profile Grid error profile
Voltage (V) 230 220 225
Current (Amp) 10 0.2 10.02
Power (W) 2300 44 2256

[00191] Likewise, the standardized values of impedance, voltage, current, power, etc. as included in the standard load profile are compared with the real-time values of impedance, voltage, current, power, etc. as included in the real-time load profile to calculate the deviation values of impedance, voltage, current, power which constitute the load error profile. An example of the load error profile thus generated, is given in Table 3 below.
Electrical Parameter Standard Load Profile Real-time load Profile Load error Profile
Voltage(V) 230 220 225
Current (Amp) 7.6 3.5 4.35
Impedance (O) 30 36 - 6
Power (W) 1748 770 978

[00192] The standardized values of state of state of charge (SoC), voltage, current, power, temperature in the standard storage unit profile may be mapped with the corresponding real-time values of state of charge (SoC), charging voltage, charging current, charging temperature, charging power, discharging voltage, discharging current, discharging temperature, discharging power in the real-time storage unit profile to derive the deviation values of state of charge (SoC), voltage, current, power temperature which constitute the storage unit error profile. An example of the storage unit error profile during charging of the storage unit 105 thus generated is given in Table 4 below. The negative sign for the error profile battery charging current and the error profile battery state of charging may indicate that the storage unit 105 is charging.
Electrical Parameter Standard storage unit Profile Real-time storage unit profile (charging) Storage unit error profile
Voltage (V) 55 54 54.5
Current (Amp) 20 5 15.23
SoC (%) 100% 70% 30%
Temperature (°C) 25° 37° - 12°
Power (W) 1100 270 830

[00193] The standardized (or ideal) values of temperature, voltage, current, power, irradiation as included in the standard renewable energy profile may be mapped with the real-time values of temperature, voltage, current, irradiation as included in the real-time renewable energy profile to calculate the deviation values of temperature, voltage, current, power, irradiation which constitute the renewable energy error profile. An example of the renewable energy error profile thus generated is given in Table 5 below.
Electrical Parameter Standard renewable energy profile Real-time renewable energy profile Renewable energy error profile
Voltage (V) 112.5 110 111.25
Current (Amp) 17.8 16 2.18
Temperature (°C) 25° 37° - 12°
Power (W) 2002.5 1760 242.5

[00194] Various embodiments for calculating the grid error profile, the load error profile, the renewable energy error profile, the storage unit error profile have been described in conjunction with FIG. 3.
[00195] At step 607, at least two fractions of energy to be channelized between corresponding two or more electrical systems of the plurality of electrical systems is calculated based the error profiles of the two or more electrical systems by the energy channelization module 315. For example, the energy channelization module 315 may calculate, based upon the error profiles of the renewable energy generator 107, the storage unit 105 and the load 109, that 65% (a first fraction) of energy from the renewable energy generator 107 is sufficient to drive the load 109 and the remaining 35% (a second fraction) energy of the renewable energy generator 107 can be used to charge the battery. The two or more electrical systems may be identified depending upon one or more of: power values in the error profiles of the electrical systems, the time of the day and the real-time SOC of the storage unit 105. The at least two fractions are then calculated for the identified two or more electrical systems.
[00196] In an embodiment, the at least two fractions may be calculated based upon the error profiles of the two or more electrical systems and the SOC of the storage unit 105. For example, the energy channelization module 315 may determine that the SOC of the storage unit 105 is above a pre-defined SOC threshold (say 90%) indicating that the storage unit 105 is charged to 90% and that no further charging of the storage unit 105 may be needed. The energy channelization module 315 in such a case may, based upon the error profiles of the renewable energy generator 107, the load 109 and the grid 103, calculate that 80% (a first fraction) of energy from the renewable energy generator 107 is to be channelized to the load 109 and 20% (a second fraction) of energy from the renewable energy generator 107 is to be channelized to the grid 103. In an embodiment, the at least two fractions may be calculated based upon the error profiles of the two or more electrical systems, the SOC of the storage unit 105 and the time of the day. According to an embodiment, the at least two fractions are calculated based upon cross-comparison of the error profiles of the two or more electrical systems and the SOC of the storage unit 105. For example, the at least two offset error profiles are calculated based upon the cross-comparison of the two or more electrical systems and the at least two fractions are calculated based upon at least two offset error profiles. The at least two offset error profiles are calculated based upon the error profiles of the two or more electrical systems by the cross-comparison module 313. Embodiments of calculating the at least two fractions for various scenarios are further described in FIG. 7.
[00197] At step 609, at least one control signal is sent by the energy channelization module 315 to at least one control circuit (e.g., the at least one control circuit 211) coupled to a respective electrical system based upon the at least two fractions to channelize energy between the two or more electrical systems. The at least one control circuit 211 is configured to receive the at least one control signal and channelize energy between the two or more electrical systems as the at least two fractions. According to an embodiment, each control signal of the at least one control signal is a PWM signal having a duty cycle. The duty cycle of each control signal is adjusted based upon the at least two fractions. Various embodiments of sending the at least one control signal and how that facilitates fractional channelization of energy between the two or more electrical systems have been described in FIG. 4.
[00198] According to an embodiment, the at least one control signal is sent to the at least one control circuit 211 in response to a command received from at least one of the user (via the user’s device) or the third party (via a respective computing device of the third party). In an embodiment, once the at least one fraction is calculated, the energy channelization module 315 sends a notification (in the form of a pop-up or the like) to the user’s device and also to the computing device of the third party. In one embodiment, the energy channelization module 315 may send the notification to the third party only when the SOC of the storage unit 105 is above the pre-defined SOC threshold. The pre-defined SOC threshold may range between 70% - 95%. In one example, implementation, the pre-defined SOC threshold is 85%.
[00199] In an embodiment, the energy channelization module 315 may send the notification to the user’s device first and in case, the user does not enable energy channelization within a pre-defined period of time (for example, 1 minute) then the notification is sent to the third party.
[00200] In an embodiment, the energy channelization may be controlled remotely. In this case, the real-time profile of each electrical system may be sent to a remote server via a communication interface (e.g., Wi-Fi, 3G, 4G, 5G, NB-IoT, SCADA, etc.). The remote server may access other data of the system 100 (such as the standard profiles, system settings, etc.) via the communication interface. In an embodiment, the energy channelization module 315 may be configured to send such data to the remote server via the communication interface. The remote server may then generate the error profiles, perform cross-comparison, generate the offset error profiles and calculate the at least two fractions, etc. the at least two fractions are received from the remote server by the energy channelization module 315 via the communication interface.
[00201] According to an embodiment, the third part may also be enabled to control the energy channelization. Thus, the remote server may be associated with the third party. In this case, a prompt may be displayed by the energy channelization module 315 (or the authorization module 301) on a user device of the user to authorize the third party to control the energy channelization. The user may be prompted once the device 101 is installed at a set-up. An authorization from the user to authorize the third party may be received by the energy channelization module 315 (or the authorization module 301). When the third party is authorized by the user to control energy channelization, i.e., in response to receiving the authorization from the user, set-up details, obtained and processed by the energy channelization module 315 and/or other modules of the energy management module 209 may be sent by the energy channelization module 315 to the remove server associated with the third party via the communication interface (e.g., the SCADA interface). For example, the energy channelization module 315 may send one or more of, the values of the one or more electrical parameters of the electrical systems, the real-time profiles of the electrical systems, the standard profiles of the electrical systems to the remote server associated with the third party. The set-up details may include details such as type of the storage unit 105, storage capacity of the storage unit 105, type of renewable energy generator 107, maximum requirement by the load 109, etc. The third party may then generate the error profiles, calculate the at least two fractions and send the at least two fractions to the energy channelization module 315. In another embodiment, the energy channelization module 315 may generate the error profiles and send the error profiles to the third party. The third party then calculates the at least two fractions as described. The energy channelization module 315 may then send the at least one control signal to the at least one control circuit 211 as described. Thus, the third part may be enabled to control energy channelization between the plurality of electrical systems.
[00202] FIG. 7 illustrates a flowchart of a method 700 to calculate the at least two fractions of energy to be channelized between the two or more electrical systems of the plurality of electrical systems, according to an embodiment.
[00203] At step 701, the energy channelization module 315 checks whether the time of the day overlaps with hours when the energy from the renewable energy generator 107 is available. When the renewable energy generator 107 is a solar power generator, the hours when the energy from the solar power generator is available are the day-time hours.
[00204] When it is determined at step 701 that the time of the day overlaps with the hours when the energy from the renewable energy generator 107 is available, at step 703, the energy channelization module 315 checks whether the real-time SOC of the storage unit 105 is less than the pre-defined SOC threshold. The real-time SOC of the storage unit 105 being less than the pre-defined SOC threshold indicates that the storage unit 105 may need charging. In another embodiment, the energy channelization module 315 may check whether the battery SOC error profile (SOCberr) of the storage unit 105 is greater than or equal to a pre-defined SOC error threshold.
[00205] When it is determined at step 703 that the real-time SOC of the storage unit 105 is less than the pre-defined SOC threshold, at step 705, the energy channelization module 315 checks whether the load 109 is present, for example, by checking whether the real-time load power (Wlrtl) is greater than zero.
[00206] When it is determined at step 705 that the load 109 is present, at step 707, the energy channelization module 315 calculates at least two fractions based upon renewable-load offset error profile and renewable-storage offset error profile to channelize the energy between the renewable energy generator 107, the storage unit 105 and the load 109. The renewable-load offset error profile is calculated through cross-comparison of the renewable energy error profile and the load error profile. The renewable-storage offset error profile is calculated through cross-comparison of the renewable energy error profile and the storage error profile. The renewable-storage offset error value may include one or more of: renewable-storage current offset error value, renewable-storage voltage offset error value, renewable-storage power offset error value and a renewable-storage temperature offset error value. The renewable-load offset error profile may include one or more of: renewable-load current offset error value, renewable-load voltage offset error value, renewable-load power offset error value and a renewable-load temperature offset error value. An embodiment of calculating the renewable-load offset error profile and the renewable-storage offset error profile is explained in conjunction with FIG. 3. Considering the example values of the error profiles for the renewable energy generator 107, the storage unit 105 and the load 109 described in FIG. 6, the renewable-storage power offset error value (WferrPVBOv) is equal to 293.75W and the renewable-load power offset error value (WferrPVLOv) is equal to 367.75W. A positive value for the renewable-load power offset error value indicates that the energy from the renewable energy generator 107 is more than the energy required to drive the load 109. In one example implementation, the energy channelization module 315 calculates a first fraction of energy to be channelized from the renewable energy generator 107 to the storage unit 105 and a second fraction of energy to be channelized from the renewable energy generator 107 to the load 109 as below:
[00207] First fraction = WferrPVBOv/(WferrPVBOv + WferrPVLOv) = 44.4%
[00208] Second fraction = WferrPVLOv/(WferrPVBOv + WferrPVLOv) = 55.6%
[00209] The first fraction and the second fraction indicate that 44.4% of the energy from the renewable energy generator 107 is to be channelized to the storage unit 105 to charge the storage unit 105 and the 55.6% of the energy from the renewable energy generator 107 is to be channelized to the load 109 to drive the load 109. The method 700 returns to the step 701. This ensures that the real-time profiles and the corresponding error profiles are continuously monitored and energy channelization is automatically controlled appropriately in real-time.
[00210] In another scenario, it may be determined that excess energy from the renewable energy generator 107 may be available even after channelizing energy to the load 109 and the storage unit 105, which can be channelized to the grid 103. In this case, three fractions may be calculated based upon the renewable-load offset error profile, the renewable-storage offset error profile and a renewable-grid offset error profile in a similar manner as explained herein. The three fractions may indicate fractions of energy from the renewable energy generator 107 to be channelized to the storage unit 105, the load 109 and the grid 103.
[00211] In another scenario, it may be possible that the energy from the renewable energy generator 107 may not be sufficient to drive the load 109 as may be determined from the renewable-load power offset error value. In this case, 100% of the energy from the renewable energy generator 107 can be channelized to the load 109 and a first fraction of energy from the grid 103 may be channelized to the load 109 and a second fraction of energy from the grid 103 may be channelized to the storage unit 105. The first fraction and the second fraction may be calculated based upon a grid-load offset error profile and a grid-storage offset error profile in a similar manner as explained above. The grid-load offset error profile and the grid-storage offset error profile may be calculated in a similar manner as explained before.
[00212] When it is determined at step 705 that the load 109 is not present, at step 709, the energy channelization module 315 calculates at least two fractions based upon renewable-grid offset error profile and renewable-storage offset error profile in a similar manner to channelize the energy from the renewable energy generator 107 to the storage unit 105 and the grid 103. The method 700 returns to the step 701.
[00213] When it is determined at step 703 that the real-time SOC of the storage unit 105 is greater than or equal to the pre-defined SOC threshold, at step 711, the energy channelization module 315 checks whether the load 109 is present, for example, by checking whether the real-time load power (Wlrtl) is greater than zero.
[00214] When it is determined at step 711 that the load 109 is present, at step 713, the energy channelization module 315 calculates at least two fractions based upon renewable-load offset error profile and one of renewable-grid offset error profile and storage-load offset error profile as follows. In an embodiment, if the energy from the renewable energy generator 107 is more than the energy required to drive the load 109 based upon the renewable-load power offset error value, the energy channelization module 315 calculates the at least two fractions based upon the renewable-load offset error profile and the renewable-grid offset error profile so as to channelize the energy from the renewable energy generator 107 to the load 109 and the grid 103 in a similar manner as explained earlier. In another embodiment, if the energy from the renewable energy generator 107 is not enough to drive the load 109 based upon the renewable-load power offset error value, the energy channelization module 315 calculates the at least two fractions based upon the renewable-load offset error profile and the storage-load offset error profile in a similar manner as explained earlier so to channelize 100% (a first fraction) of the energy from the renewable energy generator 107 and say, 65% (a second fraction) of energy from the storage unit 105 to the load 109. The storage-load offset error value may include one or more of: storage-load current offset error value, storage-load voltage offset error value, and storage-load power offset error value, and may be calculated in a similar manner as explained earlier. The method 700 returns to step 701.
[00215] When it is determined at step 711 that the load 109 is not present, the energy from the renewable energy generator 107 may be channelized to the grid 103. 100% or a percentage of the energy from the renewable energy generator 107 may be channelized to the grid 103. The method 700 returns to step 701.
[00216] When it is determined at step 701 that the time of the does not overlap with the hours when the energy from the renewable energy generator 107, the energy channelization module 315 may channelize energy between the grid 103, the storage unit 105 and the load 109 depending upon real-time SOC of the storage unit 105 and whether the load 109 is present or not as explained below.
[00217] If the real-time SOC of the storage unit 105 is below the pre-defined SOC threshold and the load 109 is present, the energy channelization module 315 calculates the at least two fractions based upon the grid-load offset error profile and the grid-storage offset error profile as explained earlier to channelize a first fraction of energy from the grid 103 to the load 109 and a second fraction of energy from the grid 103 to the storage unit 105 to charge the storage unit 105. If the real-time SOC of the storage unit 105 is below the pre-defined SOC threshold and the load 109 is absent, the energy channelization module 315 may channelized energy from the grid 103 to the storage unit 105 required to charge the storage unit 105.
[00218] If the real-time SOC of the storage unit 105 is greater than or equal to the pre-defined SOC threshold and the load 109 is present, the energy channelization module 315 may drive the load 109 from the storage unit 105 for example, when the time of the day overlaps with peak hours. If the energy from the storage unit 105 is not enough to drive the load 109 as may be determined from the storage-load offset error profile, the energy channelization module 315 calculates the at least two fractions based upon the storage-load offset error profile and the grid-load offset error profile in a similar manner as explained earlier so as to channelize 100% or a fraction (a first fraction) of the energy from the storage unit 105 to the load 109 and a fraction (a second fraction) of the energy from the grid 103 to the load 109. If the real-time SOC of the storage unit 105 is greater than or equal to the pre-defined SOC threshold and the load 109 is absent, the energy channelization module 315 may take no action.
[00219] Thus, the at least two fractions are calculated based upon the two or more offset error profiles to effectively perform fractional energy channelization between the plurality of electrical systems. The electrical parameters of the electrical systems are continuously monitored. Therefore, any changes in the real-time values of the electrical parameters are reflected in the error profiles of the electrical systems. Consequently, the two or more electrical systems for energy channelization are identified and corresponding at least two fractions are also calculated in real-time. This leads to effective energy channelization without any manual intervention, thereby leading to optimal performance of the system 100.
[00220] FIG. 8 illustrates a flowchart of a method 800 for performing peak shaving, according to one embodiment. Though the steps of the method 800 have been described as performed by specific modules of the energy management module 209, it should be understood that the step may be performed by other modules of the energy management module 209 or by the energy management module 209. One or more steps of the method 800 are similar with corresponding steps of the method 600 and hence, will not be explained in detail again for the sake of brevity.
[00221] At step 801, one or more electrical parameters (hereinafter, electrical parameters) of the plurality of electrical systems (hereinafter, electrical systems) are obtained by the parameters module 305. The plurality of electrical systems includes the grid 103, the storage unit 105, the renewable energy generator 107 and the load 109. The electrical parameters may be obtained in real-time or at the pre-defined interval.
[00222] At step 803, a real-time profile is created for each electrical system of the plurality of electrical systems by the profile module 307 at the pre-defined interval using real-time values (or values obtained at the pre-defined interval) of the electrical parameters for the electrical system. Accordingly, the real-time grid profile, the real-time storage unit profile, the real-time renewable energy profile and the real-time load profile are generated by the profile module 307.
[00223] At step 805, an error profile is generated for each electrical system of the plurality of electrical systems based upon the corresponding real-time profile and a corresponding standard profile of the electrical system by the error module 311. Accordingly, the grid error profile, the storage unit error profile, the renewable energy error profile and the load error profile are generated by the error module 311 as explained earlier.
[00224] At step 807, the time of the day is compared with the peak hours by the clock module 303 to determine whether the time of day overlaps with the peak hours. As explained earlier, the peak hours (including the first peak hours and the second peak hours) may be determined based upon historical trends, may be user defined or may be defined by the third party.
[00225] When it is determined at step 807 that the time of day overlaps with the peak hours, at step 809, at least one electrical system of the plurality of electrical system is determined by the peak shaving module 317 to drive the load 109 based upon the error profiles of the plurality of electrical systems when the load 109 is present. In an embodiment, the peak shaving module 317 may compare the load error profile power (Wlerr) with a load power error threshold. When the load error profile power (Wlerr) is less than or equal to the load power error threshold, the peak shaving module 317 may determine that the load 109 is present. In another embodiment, the peak shaving module 317 may compare the real-time load power (Wlrtl) with a load power threshold. When the real-time load power (Wlrtl) is greater than or equal to the load power threshold, the peak shaving module 317 may determine that the load 109 is present. The load power error threshold and the load power threshold may be set by the user based upon system requirements, load characteristics, historical trends in the load, etc. In an embodiment, the lower power threshold may be equal to zero and the load power error threshold may be equal to the standardized value of the load power.
[00226] At step 811, at least one control signal is sent to at least one control circuit (e.g., the at least one control circuit 211), coupled to a respective electrical system, to couple the at least one electrical system to the load 109 to drive the load 109. The at least one control circuit 211 includes at least one power semiconductor switching element. In an embodiment, the peak shaving module 317 sends the at least one control signal to the at least one control circuit 211. According to an embodiment, each control signal of the at least one control signal is a PWM signal having a duty cycle. The peak shaving module 317 may calculate at least one fraction of energy to be transferred from the at least one electrical system to the load 109 to drive the load 109 based upon the error profiles of the at least one electrical system and the load 109. The calculation of the at least one fraction may be done in a similar manner as explained with respect to FIGS. 6-7. The peak shaving module 317 adjusts the duty cycle of each control signal is adjusted based upon the at least one fraction. Various embodiments of sending the at least one control signal and how that facilitates peak shaving have been explained earlier.
[00227] FIG. 9 illustrates a flowchart of a method 900 for determining the at least one electrical system by the peak shaving module 317 based upon the error profiles of the electrical systems, according to an embodiment.
[00228] At step 901, the clock module 303 compares the time of day with the first peak hours to determine whether the time of the day overlaps with the first peak hours.
[00229] When it is determined at step 901 that the time of day overlaps with the first peak hours, at step 903, the peak shaving module 317 compares the error profile of the renewable energy generator 107 with the error profile of the load 109. In an embodiment, the peak shaving module 317 compares an error profile power of the renewable energy generator 107 (for example, the PV error profile power Wpverr) with an error profile power of the load 109 (for example, the load error profile power Wlerr). The comparison of the Wpverr with the Wlerr is done to check whether the energy from the renewable energy generator 107 is sufficient to drive the load 109.
[00230] When it is determined at step 903 that the error profile power of the renewable energy generator 107 is greater than or equal to the error profile power of the load 109, at step 905, the peak shaving module 317 determines that the renewable energy generator 107 drives the load 109. Accordingly, the peak shaving module 317 switches the load 109 to the renewable energy generator 107 by sending the at least one control signal to the at least one control circuit 211 to couple the renewable energy generator 107 to the load 109 to drive the load 109. The method 900 returns to the step 901.
[00231] When it is determined at the step 903 that the error profile power of the renewable energy generator 107 is less than the error profile power of the load 109, at step 907, the peak shaving module 317 compares an error profile battery SOC (SOCberr) of the storage unit 105 with a pre-defined SOC error threshold. The comparison of the SOCberr with the pre-defined SOC error threshold is done to determine whether the storage unit 105 is charged. The pre-defined SOC error threshold may be defined by the user based upon requirements and may be saved in the database 309. The pre-defined SOC error threshold may be between 10% - 20%. In an example implementation, the pre-defined SOC error threshold is equal to 15%.
[00232] When it is determined at the step 907 that the SOCberr of the storage unit 105 is less than or equal to the pre-defined SOC error threshold, at step 909, the peak shaving module 317 determines the renewable energy generator 107 and the storage unit 105 to drive the load 109. Accordingly, the peak shaving module 317 switches the load 109 to the renewable energy generator 107 and the storage unit 105 by sending the at least one control signal to the at least one control circuit 211 to couple the renewable energy generator 107 and the storage unit 105 to the load 109. Further, the peak shaving module 317 calculates at least one fraction of energy to be transferred from the renewable energy generator 107 and the storage unit 105 to the load 109 based upon the error profiles of the renewable energy generator 107, the storage unit 105 and the load 109. In an embodiment, the peak shaving module 317 calculates a first fraction of energy to be transferred from the renewable energy generator 107 to the load 109 and a second fraction of energy to be transferred from the storage unit 105 to the load 109. The calculation of the first fraction and the second fraction can be done in a similar manner as explained with respect to FIGS 6-7. The method 900 returns to the step 901.
[00233] When it is determined at step 907 that the error profile battery SOC of the storage unit 105 is greater than the pre-defined SOC error, at step 911, the peak shaving module 317 determines the renewable energy generator 107 and the grid 103 to drive the load 109. Accordingly, the peak shaving module 317 switches the load 109 to the renewable energy generator 107 and the grid 103 by sending the at least one control signal to the at least one control circuit 211 to couple the renewable energy generator 107 and the grid 103 to the load 109. Further, the peak shaving module 317 calculates at least one fraction of energy to be transferred from the renewable energy generator 107 and the grid 103 to the load 109 based upon the error profiles of the renewable energy generator 107, the grid 103 and the load 109. In an embodiment, the peak shaving module 317 calculates a first fraction of energy to be transferred from the renewable energy generator 107 to the load 109 and a second fraction of energy to be transferred from the grid 103 to the load 109. The calculation of the first fraction and the second fraction can be done in a similar manner as explained earlier. In an embodiment, the at least one other control signal may be sent to the at least one control circuit 211 to also disconnect the non-critical components of the load 109. This is done to reduce the load 109 and thereby, reduce the energy drawn from the grid 103 as much as possible during the first peak hours. The method 900 returns to the step 901.
[00234] When it is determined at step 901 that the time of day does not overlap with the first peak hours, at step 913, the clock module 303 compares the time of day with the second peak hours to determine whether the time of day overlaps with the second peak hours.
[00235] When it is determined at step 913 that the time of day overlaps with the second peak hours, at step 915, the peak shaving module 317 compares the SOCberr with the pre-defined SOC error threshold.
[00236] When it is determined at the step 915 that the SOCberr is less than or equal to the pre-defined SOC error threshold, at step 917, the peak shaving module 317 determines the storage unit 105 to drive the load 109. Accordingly, the peak shaving module 317 switches the load 109 to the storage unit 105 by sending the at least one control signal to the at least one control circuit 211 to couple the storage unit 105 to the load 109. Further, the peak shaving module 317 calculates a fraction of energy to be transferred from the storage unit 105 to the load 109 based upon the error profiles of the storage unit 105 and the load 109. The calculation of the fraction can be done in a similar manner as explained earlier. The method 900 returns to the step 901.
[00237] When it is determined at step 915 that the SOCberr is greater than the pre-defined SOC error threshold, at step 919, the peak shaving module 317 determines the grid 103 to drive the load 109. Accordingly, the peak shaving module 317 switches the load 109 to the grid 103 by sending the at least one control signal to the at least one control circuit 211 to couple the grid 103 to the load 109. Further, the at least one other control signal may be sent to the at least one control circuit 211 to also disconnect the non-critical components of the load 109 as explained earlier. This is done to reduce the load 109 and thereby, reduce the energy drawn from the grid 103 as much as possible during the second peak hours. The method 900 returns to the step 901.
[00238] According to an embodiment, during the non-peak hours, i.e., when it is determined at step 901 that the time of day does not overlap with the peak hours, the peak shaving module 317 determines that the at least one electrical system is either the renewable energy generator 107 (when the energy from the renewable energy generator 107 is available and is sufficient to drive the load 109), or the grid 103 (when the energy from the renewable energy generator 107 is not available), or both (when the energy from the renewable energy generator 107 is available but is not sufficient to drive the load 109). Further, the storage unit 105 may be charged using from remaining energy from the renewable energy generator 107 and/or the grid 103 after driving the load 109.
[00239] Thus, the peak shaving module 317 performs peak shaving to minimize energy drawn from the grid 103 during the peak hours. Further, as can be seen from aforesaid steps, when energy from the renewable energy generator 107 is available, the peak shaving module 317 gives a preference to the renewable energy generator 107 to drive the load 109 and utilizes the storage unit 105 when the energy from the renewable energy generator 107 is not available or is not sufficient to fully drive the load 109. This not only exploits the renewable energy fully but also saves the charge of the storage unit 105 for scenarios when the renewable energy is not available during the peak hours (e.g. during the second peak hours). This avoids unnecessary discharging of the storage unit 105, thereby improving its life. Further, when energy from the grid 103 is needed during the peak hours to compensate for the shortfall of energy from the renewable energy generator 107 and/or the storage unit 105, the peak shaving module 317 reduces the load 109 by disconnecting the non-critical components of the load 109. This is done to reduce the energy drawn from the grid 103 during the peak hours.
[00240] FIG. 10 illustrates a method 1000 for controlling charging and discharging of the storage unit 105, according to an embodiment of the present disclosure. Though the steps of the method 1000 have been described as performed by specific modules of the energy management module 209, it should be understood that the step may be performed by other modules of the energy management module 209 or by the energy management module 209. One or more steps of the method 1000 are similar with corresponding steps of the method 600 and hence, will not be explained in detail again for the sake of brevity.
[00241] At step 1001, one or more electrical parameters (hereinafter, electrical parameters) of the plurality of electrical systems (hereinafter, electrical systems) are obtained by the parameters module 305. The plurality of electrical systems includes the grid 103, the storage unit 105, the renewable energy generator 107 and the load 109. The electrical parameters may be obtained in real-time or at the pre-defined interval.
[00242] At step 1003, a real-time profile is created for each electrical system of the plurality of electrical systems by the profile module 307 at the pre-defined interval using real-time values (or values obtained at the pre-defined interval) of the electrical parameters for the electrical system. Accordingly, the real-time grid profile, the real-time storage unit profile, the real-time renewable energy profile and the real-time load profile are generated by the profile module 307.
[00243] At step 1005, an error profile is generated for each electrical system based upon the corresponding real-time profile and a corresponding standard profile of the electrical system by the error module 311. Accordingly, the grid error profile, the storage unit error profile, the renewable energy error profile and the load error profile are generated by the error module 311 as explained earlier.
[00244] At step 1007, a discharging profile is created by the charging control module 319 based upon the error profile state of charge (i.e., SOCberr) of the storage unit 105 when time of day overlaps with the first peak hours or the second peak hours. In an embodiment, the discharging profile includes a fraction of energy from storage unit 105 to be transferred to the load 109.
[00245] At step 1009, a charging profile is created by the charging control module 319 based upon the error profile state of charge when the time of day overlaps with the first off-peak hours or the second off-peak hours. In an embodiment, the charging profile includes another fraction of energy from one of the renewable energy generator 107 or the grid 103 to be transferred to the storage unit 105.
[00246] At step 1011, at least one control signal is sent by the charging control module 319 to at least one control circuit (e.g., the at least one control circuit 211) based upon one of the discharging profile or the charging profile to discharge or charge the storage unit, respectively. The at least one control circuit 211 couples one of the renewable energy generator 107, the grid 103 or the load 109 to the storage unit 105 as per the at least one control signal to charge or discharge the storage unit 105 as per the charging and discharging profile, respectively. The creation of the charging profile and the discharging profile and determination of the corresponding fraction is further elaboration in FIG. 11. The at least one control circuit 211 is coupled to a respective electrical system. According to an embodiment, each control signal of the at least one control signal is a PWM signal having a duty cycle. In an embodiment, the duty cycle of each control signal is adjusted based upon the fraction and the other fraction so that a fraction of energy may be transferred to the storage unit 105 to charge the storage unit 105 or from the storage unit 105 to discharge the storage unit 105. The at least one control circuit 211 is configured to transfer the fractional energy from and to the storage unit 105 based upon the at least one control signal in a similar manner as explained earlier.
[00247] FIG. 11 illustrates a method 1100 for creating the charging profile and the discharging profile, according to an embodiment of the present disclosure.
[00248] At step 1101, the clock module 303 compares the time of day with the first peak hours, the second peak hours, the first off-peak hours and the second off-peak hours.
[00249] When the clock module 303 determines, at step 1101, that the time of day overlaps with the first peak hours, at step 1103, the charging control module 319 compares the error profile SOC (SOCberr) with a first SOC error threshold. The comparison of the SOCberr with the first SOC error threshold is made to identify the state of charge of the storage unit 105. The first SOC error threshold may be between 10% - 20%. In an example implementation, the first SOC error threshold is 15%.
[00250] When the charging control module 319 determines, at step 1103, that the SOCberr is less than or equal to the first SOC error threshold (indicating that the storage unit 105 is sufficiently charged), at step 1105, the charging control module 319 compares a renewable error profile power (e.g., PV error profile power Wpverr) with a renewable power error threshold. The comparison of the renewable error profile power with the renewable power error threshold is made to determine how much power is available. The renewable power error threshold may be defined by the user based upon system requirements, characteristics of the renewable energy generator 107 (type, capacity, etc.), load requirements, etc. In an example implementation, the renewable power error threshold is 1000W.
[00251] When the charging control module 319 determines, at step 1105, that the renewable error profile power is less than or equal to the renewable power error threshold (indicating that more energy from the renewable energy generator 107 is available), at step 1107, the charging control module 319 determines a first fraction of energy from the storage unit 105 to be transferred to the load 109 and a second fraction of energy from the renewable energy generator 107 to be transferred to the load 109. The charging control module 319 creates the discharging profile having the first fraction and the second fraction. The first fraction may range between 10% - 20% and the second fraction may range between 80% - 90%. In an example implementation, the first fraction is 15% and the second fraction is 85%.
[00252] When the charging control module 319 determines, at step 1105, that the renewable error profile power is greater than the renewable power error threshold (indicating that less energy from the renewable energy generator 107 is available), at step 1109, the charging control module 319 determines a third fraction of energy from the storage unit 105 to be transferred to the load 109 and a fourth fraction of energy from the renewable energy generator 107 to be transferred to the load 109. The third fraction is greater than the first fraction and the fourth fraction is smaller than the second fraction. The charging control module 319 creates the discharging profile having the third and the fourth fraction. The third fraction may range between 45% - 55% and the fourth fraction may range between 45% - 55%. In an example implementation, the third fraction is 50% and the fourth fraction is 50%.
[00253] It can be seen from above that the charging control module 319 exploits the energy from the renewable energy generator 107 as much as possible. The charging control module 319 also adjusts energy drawn from the storage unit 105 depending upon available energy from the renewable energy generator 107. This prevents unnecessary discharge of the storage unit 105 and thereby, increasing the time duration between two charging cycles of the storage unit 105.
[00254] When the charging control module 319 determines, at step 1103, that the SOCberr is greater than the first SOC error threshold (indicating that the storage unit 105 is not sufficiently charged), at step 1111, the charging control module 319 compares the SOCberr with a second SOC error threshold. The SOCberr is compared with the second SOC error threshold to determine whether the storage unit 105 is discharged. The second SOC threshold is greater than the first SOC threshold. The second SOC threshold may range between 80% - 90%. In an example implementation, the second SOC threshold is 85%.
[00255] When the charging control module 319 determines, at step 1111, that the SOCberr is greater than the second SOC error threshold (indicating that the storage unit 105 is discharged), at step 1113, the charging control module 319 determines a fifth fraction of energy from the renewable energy generator 107 to be transferred to the storage unit 105 and a sixth fraction of energy from the renewable energy generator 107 to be transferred to the load 109 based upon the renewable power error profile and a load power error profile of the load 109. The charging control module 319 may determine the fifth and the sixth fraction in a similar manner as described in FIGS. 6-7. The charging control module 319 creates the charging profile having the fifth fraction and the sixth fraction.
[00256] When the clock module 303 determines, at step 1101, that the time of day overlaps with the second peak hours, at step 1115, the charging control module 319 compares the SOCberr with the first SOC error threshold, the second SOC error threshold and a third SOC error threshold. The third SOC error threshold is greater than the first SOC error threshold and less than the second SOC error threshold. The SOCberr is compared with the first, the second and the third SCO error thresholds to determine SOC status of the storage unit 105. The third SOC error threshold may range between 45% - 55%. In an example implementation, the third SOC error threshold is 50%.
[00257] At step 1117, the charging control module 319 determines one of a seventh, an eights or nineth fraction of energy from the storage unit 105 to be transferred to the load 109 based upon the comparison at step 1115. In an embodiment, the charging control module 319 determines the seventh fraction of energy from the storage unit 105 to be transferred to the load 109 when the SOCberr is less than or equal to the first SOC error threshold (indicating that the storage unit 105 is charged). The charging control module 319 determines the eighth fraction of energy from the storage unit 105 to be transferred to the load 109 when the SOCbess is greater than the first SOC error threshold and less than or equal to the third SOC error threshold. The charging control module 319 determines the ninth fraction of energy from the storage unit 105 to be transferred to the load 109, when the SOCberr is greater than the third SOC error threshold and less than or equal to the second SOC error threshold. The seventh fraction is greater than the eighth fraction and the eighth fraction is greater than the ninth fraction. The seventh fraction may range between 80% - 90%. The eighth fraction may range between 45% - 50%. The ninth fraction may range between 10% - 20%. In an example implementation, the seventh fraction, the eighth fraction and the ninth fraction are 85%, 50% and 15%, respectively. The charging control module 319 creates the discharging profile having one of the seventh fraction, the eighth fraction and the ninth fraction.
[00258] When the charging control module 319 determines, at step 1115, that the SOCberr is greater than the second SOC error threshold, at step 1119, the charging control module 319 determines a tenth fraction of energy from the grid 103 to be transferred to the storage unit 105 and an eleventh fraction of energy from the grid 103 to be transferred to the load 109 based upon a grid error profile of the grid 103 and a load power error profile of the load 109. The charging control module 319 may determine the tenth and the eleventh fraction in a similar manner as described in FIGS. 6-7. The charging control module 319 creates the charging profile having the tenth fraction and the eleventh fraction.
[00259] When the clock module 303 determines, at step 1101, that the time of day overlaps with the first off-peak hours, at step 1121, the charging control module 319 compares the SOCberr with the second SOC error threshold.
[00260] When the charging control module 319 determines, at step 1121, that the SOCberr is greater than the second SOC error threshold, at step 1123, the charging control module 319 determines a twelfth fraction of energy from the renewable energy generator 107 to be transferred to the storage unit 105 and a thirteenth fraction of energy from the renewable energy generator 107 to be transferred to the load 109 based upon the renewable power error profile and the load power error profile. The charging control module 319 may determine the twelfth fraction and the thirteenth fraction in a similar manner as described in FIGS. 6-7. The charging control module 319 creates the charging profile having the twelfth fraction and the thirteenth fraction.
[00261] When charging control module 319 determines, at step 1101, that the time of day overlaps with the second off-peak hours, at step 1125, the charging control module 319 compares the SOCberr with the second SOC error threshold.
[00262] When the charging control module 319 determines, at step 1125, that the SOCberr is greater than the second SOC error threshold, at step 1127, the charging control module 319 determines a fourteenth fraction of energy from grid 103 to be transferred to the storage unit 105 and a fifteenth fraction of energy from the grid 103 to be transferred to the load 109 based upon the grid error profile and the load power error profile. The charging control module 319 may determine the fourteenth fraction and the fifteenth fraction in a similar manner as described in FIGS. 6-7. The charging control module 319 creates the charging profile having the fourteenth fraction and the fifteenth fraction.
[00263] The scope of the invention is only limited by the appended patent claims. More generally, those skilled in the art will readily appreciate that all parameters, dimensions, materials, and configurations described herein are meant to be exemplary and that the actual parameters, dimensions, materials, and/or configurations will depend upon the specific application or applications for which the teachings of the present invention is/are used. ,CLAIMS:WE CLAIM
1. A system (100) for peak shaving comprising:
a. a plurality of input ports (201) coupled to a plurality of electrical systems, wherein the plurality of electrical systems comprises a grid (103), a renewable energy generator (107), a storage unit (105) and a load (109);
b. one or more sensors coupled to each input port (201) and configured to sense one more electrical parameters of a respective electrical system;
c. a parameters module (305), executed by a processor (207) and coupled to the one or more sensors, configured to obtain the one or more electrical parameters of the plurality of electrical systems at a pre-defined interval;
d. a profile module (307), executed by the processor (207) and coupled to the parameters module (305), configured to create a real time profile for each electrical system at the pre-defined interval using the values of the one or more electrical parameters of the electrical system;
e. an error module (311), executed by the processor (207) and coupled to the profile module (307), configured to generate an error profile for each electrical system based upon the corresponding real-time profile and a corresponding standard profile of the electrical system, wherein each error profile comprises a corresponding error profile power;
f. a clock module (303), executed by the processor (207), configured to compare time of day with peak hours;
g. a peak shaving module (317), executed by the processor (207) and coupled to the clock module (303), configured to:
i. determine, based upon the error profiles of the plurality of electrical systems, at least one electrical system of the plurality of electrical systems to drive the load (109), when the time of day overlaps with the peak hours and the load (109) is present; and
ii. send at least one control signal to couple the at least one electrical system to the load (109); and
h. at least one control circuit (211), coupled to a respective electrical system and comprising at least one power semiconductor switching element, configured to receive the at least one control signal and couple the at least one electrical system to the load (109) to drive the load (109).
2. The system (100) as claimed in claim 1, wherein the peak shaving module (317) is configured to:
a. compare the time of day with first peak hours to determine whether the time of the day overlaps with the first peak hours;
b. compare an error profile power of the renewable energy generator (107) with an error profile power of the load (109), when the time of the day overlaps with the first peak hours; and
c. determine the renewable energy generator (107) to drive the load (109) when the error profile power of the renewable energy generator (107) is greater than or equal to the error profile power of the load (109).
3. The system (100) as claimed in claim 2, wherein when the error profile power of the renewable energy generator (107) is less than the error profile power of the load (109), the peak shaving module (317) is configured to:
a. compare an error profile battery SOC of the storage unit (105) with a pre-defined SOC error threshold; and
b. determine the renewable energy generator (107) and the storage unit (105) to drive the load (109) when the error profile battery SOC of the storage unit (105) is less than or equal to the pre-defined SOC error threshold.
4. The system (100) as claimed in claim 3, when the error profile power of the renewable energy generator (107) is less than the error profile power of the load (109) and when the error profile battery SOC of the storage unit (105) is greater than the pre-defined SOC error threshold, the peak shaving module (317) is configured to determine the renewable energy generator (107) and the grid (103) to drive the load (109).
5. The system (100) as claimed in claim 4, wherein the peak shaving module (317) is configured to send at least one other control signal to the at least one control circuit (211) to disconnect a non-critical component of the load (109) from the at least one electrical system.
6. The system (100) as claimed in claim 1, wherein the peak shaving module (317) is configured to:
a. compare the time of day with second peak hours to determine whether the time of day overlaps with the second peak hours;
b. compare an error profile battery SOC of the storage unit (105) with a pre-defined SOC error threshold when the time of day overlaps with the second peak hours; and
c. determine the storage unit (105) to drive the load (109) when the real-time SOC of the storage unit (105) is less than or equal to the pre-defined SOC error threshold.
7. The system (100) as claimed in claim 6, wherein when the error profile battery SOC of the storage unit (105) is greater than the pre-defined SOC error threshold, the peak shaving module (317) is configured to send at least one other control signal to the at least one control circuit (211) to disconnect a non-critical component of the load (109) from the at least one electrical system.
8. The system (100) as claimed in claim 1, wherein the peak shaving module (317) is configured to:
a. compare an error profile power of the load (109) with a load power error threshold; and
b. determine that the load (109) is present when the error profile power of the load (109) is less than or equal to the load power error threshold.
9. The system (100) as claimed in claim 1, wherein the peak shaving module (317) is configured to calculate at least one fraction of energy from the at least one electrical system to be transferred to the load (109) based upon the error profiles of the at least one electrical system and the load (109); wherein the at least one control signal is sent based upon the at least one fraction to transfer the energy from the at least one electrical system to the load (109) as per the at least one fraction.
10. The system (100) as claimed in claim 9, wherein each control signal of the at least one control signal is a PWM signal having a duty cycle, wherein the peak shaving module (317) is configured to adjust the duty cycle of each control signal based upon the at least one fraction.
11. The system (100) as claimed in claim 1, wherein the at least one power semiconductor switching element comprises an Insulated Gate Bipolar Transistor (IGBT) or a power Metal Oxide Semiconductor Field Effect Transistor (MOSFET).
12. A method for peak shaving comprising:
a. obtaining values of one or more electrical parameters of a plurality of electrical systems from respective one or more sensors at a pre-defined interval, wherein the plurality of electrical systems comprises a grid (103), a renewable energy generator (107), a storage unit (105) and a load (109);
b. creating a real time profile for each electrical system of the plurality of electrical systems at the pre-defined interval using the values of the one or more electrical parameters of the electrical system;
c. generating an error profile for each electrical system of the plurality of electrical systems based upon the corresponding real time profile and a standard profile of the electrical system, wherein each error profile comprises a corresponding error profile power;
d. comparing time of day with peak hours;
e. determining, based upon the error profiles of the plurality of electrical systems, at least one electrical system of the plurality of electrical system to drive the load (109) when the time of day overlaps with the peak hours and the load (109) is present; and
f. sending at least one control signal to at least one control circuit (211), coupled to a respective electrical system and comprising at least one power semiconductor switching element, to couple the at least one electrical system to the load (109) to drive the load (109).
13. The method as claimed in claim 12, wherein the step of determining the at least one electrical system comprises:
a. comparing the time of day with first peak hours to determine whether the time of the day overlaps with the first peak hours;
b. comparing an error profile power of the renewable energy generator (107) with an error profile power of the load (109), when the time of the day overlaps with the first peak hours; and
c. determining the renewable energy generator (107) to drive the load (109) when the error profile power of the renewable energy generator (107) is greater than or equal to the error profile power of the load (109).
14. The method as claimed in claim 13, wherein when the error profile power of the renewable energy generator (107) is less than the error profile power of the load (109), the step of determining the at least one electrical system comprises:
a. comparing an error profile battery SOC of the storage unit (105) with a pre-defined SOC error threshold; and
b. determining the renewable energy generator (107) and the storage unit (105) to drive the load (109) when the error profile battery SOC of the storage unit (105) is less than or equal to the pre-defined SOC error threshold.
15. The method as claimed in claim 14, when the error profile power of the renewable energy generator (107) is less than the error profile power of the load (109) and when the error profile battery SOC of the storage unit (105) is greater than the pre-defined SOC error threshold, the step of determining the at least one electrical comprises determining the renewable energy generator (107) and the grid (103) to drive the load (109).
16. The method as claimed in claim 15, wherein the method comprises sending at least one other control signal to the at least one control circuit (211) to disconnect a non-critical component of the load (109) from the at least one electrical system.
17. The method as claimed in claim 12, wherein the step of determining the at least one electrical system comprises:
a. comparing the time of day with second peak hours to determine whether the time of day overlaps with the second peak hours;
b. comparing an error profile battery SOC of the storage unit (105) with a pre-defined SOC error threshold when the time of day overlaps with the second peak hours; and
c. determining the storage unit (105) to drive the load (109) when the real-time SOC of the storage unit (105) is less than or equal to the pre-defined SOC error threshold.
18. The method as claimed in claim 17, wherein when the error profile battery SOC of the storage unit (105) is greater than the pre-defined SOC error threshold, the method comprises sending at least one other control signal to the at least one control circuit (211) coupled to a non-critical component of the load (109) to disconnect the non-critical component of the load (109) from the at least one electrical system.
19. The method as claimed in claim 12, wherein the method comprises:
a. Comparing an error profile power of the load (109) with a load power error threshold; and
b. determining that the load (109) is present when the error profile power of the load (109) is less than or equal to the load power error threshold.
20. The method as claimed in claim 12, wherein the method comprises calculating at least one fraction of energy from the at least one electrical system to be transferred to the load (109) based upon the error profiles of the at least one electrical system and the load (109); wherein the at least one control signal is sent based upon the at least one fraction to transfer the energy from the at least one electrical system to the load (109) as per the at least one fraction.
21. The method as claimed in claim 20, wherein each control signal of the at least one control signal is a PWM signal having a duty cycle, wherein the method comprises adjusting the duty cycle of each control signal based upon the at least one fraction.
22. The method as claimed in claim 12, wherein the at least one power semiconductor switching element comprises an Insulated Gate Bipolar Transistor (IGBT) or a power Metal Oxide Semiconductor Field Effect Transistor (MOSFET).