Description:FORM 2
THE PATENTS ACT, 1970
(39 of 1970)
&
The Patent Rules, 2003
COMPLETE SPECIFICATION
(See sections 10 & rule 13)
1. TITLE OF THE INVENTION
AN ENERGY MANAGEMENT SYSTEM (EMS) FOR THE ELECTRIC VEHICLE CHARGING STATION (EVCS)
2. APPLICANT (S)
NAME NATIONALITY ADDRESS
DIVYASAMPARK IHUB ROORKEE FOR DEVICES MATERIALS AND TECHNOLOGY FOUNDATION IN Indian Institute of Technology Roorkee, Roorkee-247667, Uttarakhand, India.
3. PREAMBLE TO THE DESCRIPTION
COMPLETE SPECIFICATION

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

FIELD OF INVENTION:
[001] The present invention relates to the field of electric vehicle charging station. The present invention in particular relates to an energy management system (EMS) and method for the electric vehicle charging station (EVCS).
DESCRIPTION OF THE RELATED ART:
[002] The rapid advancements in electric vehicle (EV) technology and growing public interest are the reasons that accelerate EV adoption. However, EV charging demands substantial power and causes considerable stress on the electrical grid. Consequently, efficient energy management strategies are necessary to optimize charging power allocation, ensuring grid stability while meeting EV charging demands. Furthermore, integrating renewable energy sources (RES) is vital in mitigating high-power demand on the grid and reducing overall EV charging costs. However, the inherent intermittency in photovoltaic (PV) generation leads to power fluctuations within the grid. Therefore, battery energy storage systems (BESS) are employed to compensate for the said intermittency. Thus, optimal power sharing among these energy resources is essential to prevent inefficient utilization, maintain grid stability and minimize operational costs.
[003] Reference may be made to the following:
[004] Publication No. IN202531002138 relates to a system and method for optimizing electric vehicle (EV) charging stations integrated with microgrids, utilizing a hybrid control approach. The system incorporates real-time data from sensors monitoring both the EV charging station and the microgrid, transmitted to a hybrid controller and an Artificial Intelligence (AI) module through a communication interface.
[005] Publication No. IN202421101244 relates to a modular multilevel converter (MMC)-based DC microgrid for integrating distributed energy resources (DERs) such as solar, wind, and fuel cells to power ultrafast electric vehicle (EV) charging stations.
[006] Publication No. IN202441093994 relates to the growing adoption of electric vehicles (EVs) presents challenges in optimizing charging efficiency and sustainability. Traditional charging systems often lack intelligent management, relying on fixed points with limited communication and real-time monitoring, leading to inefficient energy use, grid strain, and minimal integration of renewable energy. IoT-based hybrid EV charging systems address these issues by combining grid power with renewable sources like solar and wind energy.
[007] Publication No. IN202441089471 relates to an Al-based wireless charging system for electric vehicles, designed to enhance charging efficiency in high-traffic urban environments. The system consists of a wireless power transmitter at the charging station and a wireless power receiver in the electric vehicle.
[008] Patent No. US12083919 relates to system and methods to charge an electric vehicle (EV) and manage grid power consumption.
[009] Publication No. WO2022216249 relates to charging station with a management system for electric vehicles, wherein the station comprises; a main central server that manages the entire system and analyzes the data it receives from the database, web server and mobile application; a database where the information of the vehicle to be charged, user information and energy price information are transferred by the main central server; a Web server that enables communication between the mobile application and the main central server and payment transactions; a mobile application that displays the nearest charging station and information about the charging station to the user, directs the user to the charging station by means of navigation, allows tracking of charging information during charging and allows payment after charging.
[010] Publication No. CN119160025 relates to an autonomous V2G charging station power supply management method, system and device, and a medium, mainly relates to the technical field of power supply management, and is used for solving the problem that the regulation and control main body of the existing autonomous V2G regulation and control scheme is each electric vehicle, and the regulation and control difficulty is large.
[011] Publication No. CN118683386 relates to an intelligent control method and an intelligent management and control terminal device for an electric vehicle, and relates to the technical field of new energy and electric power control, the method comprises the following steps: S1, acquiring a transformer voltage and a transformer current, and calculating a transformer index by using Fourier transform; s2, monitoring the charging station and all electric vehicles in the charging station in real time, sequentially evaluating the upper and lower regulation active power of adjustable resources in the electric vehicles and the charging station, and defining power characteristics; s3, based on the power characteristics of the electric vehicle and the charging station, evaluating the change power required by the electric vehicle; and S4, the charging and discharging terminal is controlled, and changing power is distributed according to the current vehicle information of the electric vehicle.
[012] Publication No. US2024201642 relates to power for non-charging loads located at charging sites, the systems and methods disclosed herein provide for controlling electric vehicle charging stations to provide alternating current (AC) power to the non-charging loads from power stored in their batteries.
[013] Publication No. CN117078032 relates to a mobile battery swap station information management method and system, and relates to the technical field of battery swap, and the method comprises the steps: an information management system obtains the information of a power supply battery of a mobile battery swap station, calculates the average electric energy required by the single battery swap of a battery swap device and the power consumption condition of other devices of the battery swap station, and sends a battery replacement instruction; after receiving the instruction, the information management system communicates with the battery replacement equipment controller to obtain and store various operation state data of the equipment during no-load and load operation; the information management system communicates with the transfer trolley controller to obtain battery information of a new battery replacement station, and the battery replacement station information management system serves as a client to be actively connected with the transfer trolley controller.
[014] Publication No. CN114784837 relates to a charging station energy management system and a management method thereof.
[015] Publication No. WO2022072828 relates to a system and method for providing extreme fast charging of electric vehicles that mimics the typical gas station experience while also supporting local grid energy management using a distributed network of extremely fast charging stations to form a large virtual resource for the grid.
[016] Publication No. CN112350306 relates to a control method for an energy management system of a charging station. The method comprises the following steps: receiving state information sent by a plurality of energy management sub-controllers through an energy management host; calculating an energy buffer area allocated to the current energy management sub-controller according to the charging station power information and the state information sent by the plurality of energy management sub-controllers; sending the energy buffer area to the current energy management sub-controller through the energy management host; and controlling the output power of the current energy management sub-controller to be the required power when the required power of the current electric equipment is the lifting power requirement and the required power is located in the energy buffer area of the corresponding energy management sub-controller.
[017] Publication No. CN211063366 relates to an energy management system for a charging station and relates to the field of charging stations.
[018] Publication No. CN209955801 relates to an operation management system of an electric vehicle charging station. The system comprises a parking lot body, a barrier gate and a building platform are arranged on the parking lot body. Monitors are symmetrically arranged on the two sides of the barrier gate; a barrier gate controller is arranged at one end of the barrier gate; a first display screen is arranged in the middle of the side, close to the barrier gate, of the building platform.
[019] Publication No. CN109787304 relates to a distributed energy management method and system for a solar charging station. The method comprises the steps of calculating the maximum total charging power provided by a solar power station; and calculating the charging power of each charging pile with the optimal charging power by taking the maximum total charging power provided by the solar power station as a limit.
[020] Publication No. WO2018103231 relates to a new energy micro-grid electric vehicle charging station, comprising at least a new energy micro-grid electric vehicle charging station unit module which comprises a power transformation and distribution module, an energy storage module, a distributed new energy power generation unit, a load, a power compensation device, and a micro-grid control management system. The new energy micro-grid electric vehicle charging station unit module is divided into three levels for control management.
[021] Publication No. CN105305588 relates to the photovoltaic power generation and electric automobile charging technology field and relates to a vehicle charging management system. The system mainly comprises a flexible solar cell module, a solar charger, a ground charger, a cell management system and an electric automobile body.
[022] Publication No. JP2015091172 relates to a regional energy management system and a vehicle charging system, enabling an appropriate start of charging a new vehicle in consideration of power price. A regional energy management system includes a center and a vehicle charging system.
[023] Publication No. CN103887830 relates to an electric vehicle charging station charging monitoring system with an energy storage device. The system is characterized in that the electric vehicle charging station charging monitoring system with the energy storage device is formed by a power supply system, an energy storage system, a charging system and a control system, wherein the power supply system is formed by a high-low voltage relay protection device and a transformer, the energy storage system is formed by an energy storage relay converter, an energy storage control device and a power storage battery, the charging system is formed by a plurality of chargers, each of the chargers is formed by an electromagnetic power supply switch, a bridge rectifier, an output filter, a DC relay protection device, a voltage and current sensor and a constant voltage and constant current charging conversion controller, and the control system is formed by a CAN bus, a data acquisition controller and a PC machine.
[024] Publication No. KR20130025201 relates to a centralized electric vehicle charging system and an energy managing method thereof are provided to simultaneously charge a plurality of electric vehicles by using various charging algorithms. Constitution: Charging stations charge batteries of a plurality of electric vehicles (EV1 to EVn). A power system supplies power to the charging stations. A controller controls power supplied to the charging stations based on real-time allowable power information of the power system, charging state information of the battery, and charging request information of each electric vehicle.
[025] Publication No. US2012280653 relates to charging stations, systems for charging and identifying electric vehicles, and methods for detecting and providing charging information of a vehicle. The charging stations include vehicle detectors, charging connectors, and system controllers to estimate the state of charge of a vehicle based on current measurements from the charging connectors and then to output charge status signals if the state of charge is at or above a predetermined energy level and the vehicle is detected as being properly positioned by the vehicle detectors.
[026] Publication No. CN102255343 relates to an electric vehicle charging station management system, which comprises the following parts, namely a winding device, a temperature control device, a charging control device, an energy acquisition conversion device and an energy storage device, wherein the winding device comprises a magnetic core, a primary winding and a secondary winding; the magnetic core is made of a high-frequency magnetic core material; the primary winding and the secondary winding are wound on the magnetic core; the temperature control device transmits an acquired temperature signal to a controller and compares the temperature signal with a preset signal in the controller to control a fan and a motor to operate; the charging control device comprises an acquirer, a comparator, a timer and a switching power supply; the energy acquisition conversion device comprises various kinds of energy acquisition devices which can convert acquired energy into electric energy through corresponding energy conversion devices; the energy storage device comprises a normal energy storage device and a standby energy storage device; and an energy entering channel is arranged between the standby energy storage device and the normal energy storage device. The invention provides an intelligent electric vehicle charging station system which can quickly and conveniently meet the charging requirement of a user and can realize energy conservation to the largest extent.
[027] Publication No. CN119154513 relates to a large-scale energy storage power station operation monitoring management system and management method and relates to the technical field of electric energy storage systems.
[028] Publication No. CN119058464 relates to a hidden and movable intelligent charging management system, which comprises a charging station main body, a charging device, an underground track, a ground exit, a charging intelligent planning module and a charging power prediction module, the charging station main body is connected with commercial power and is used for realizing electric energy supply of the charging device; the charging device moves along the underground track and is connected with the charging station main body through a charging cable buried underground; the underground track is laid under the ground of the parking lot of the charging station; the ground exits are arranged at the parking spaces; and the operation terminal is erected in the charging station.
[029] Publication No. CN118801434 relates to an energy management method and system for a multi-source access charging, replacing and storing integrated station.
[030] Publication No. IN202441091489 relates to an energy storage solution for fast electric vehicle (EV) charging stations designed to optimize energy management, reduce operational costs, and improve grid stability.
[031] Publication No. IN202141048089 relates to electric vehicles (EVs) and plug-in hybrid electric vehicles (PHEVs) to gain traction, charging stations must be designed efficiently to provide fast charging rates. As a result, the traditional grid would be put under more strain, raising the cost of charging. To improve charging station performance, using on-site renewable energy sources like photovoltaic (PV) electricity in addition to the traditional grid is one option.
[032] Patent No. US11807124 relates to an electric vehicle charger control system linked with an EMS including a communication unit which receives allowable power information which is information about available power to charge an electric vehicle from an energy management system (EMS); a management unit which generates charger setting information which is information about charging setting in consideration of at least one of a priority for every charger, a maximum/minimum charging power amount for every charger, a current charging power amount for every charger, and reservation state information of the user, for the plurality of electric vehicle chargers, using the allowable power information; and a control unit which controls the plurality of electric vehicle chargers according to the charger setting information for every charger.
[033] Patent No. US10220719 relates to electrical supply systems including electric vehicle supply equipment (EVSE). The EVSE includes a communication gateway that provides internet accessibility by a user through an EVSE server. In some embodiments, the EVSE allows communication with other smart devices, and/or communication of status of loads coupled to a load center.
[034] Publication No. IN201644041758 relates to a method for managing power in a station for charging electric vehicles (VE), said station including several charging points (Bx), said method helping to predict accurately the consumption of the charging station, with satisfaction of clients.
[035] The article entitled “Energy management system for EV charging infrastructure” by Dr Ganesh Bhutkar, Yogesh Kumar, Subramani R, Ms. E.Jothi, A.S.Valarmathy, Nitin Sherje, S.Tharmar; E3S Web of Conferences 591; November 2024 talks about an energy management system designed for electric vehicle charging infrastructure that balances demand and supply in real time. The proposed system dynamically allocates available power to connected EVs based on their charging demands and the total power available, ensuring optimal utilization of energy resources. By simulating various scenarios, the system demonstrates its capability to prevent overloading, efficiently distribute power, and prioritize critical energy needs. The results of the simulation show that the system can effectively manage power distribution, reduce peak load impact, and enhance the reliability of EV charging networks. This approach offers a scalable and adaptable solution for integrating EVs into the existing power grid, contributing to the development of smart and sustainable transportation systems.
[036] The energy management frameworks discussed above predominantly consider constant charging power for EVs. However, in practical scenarios, the EV charging profile exhibits inherent non-linearity, where the charging current is constant until the EV battery reaches a specific voltage. Subsequently, the charging current is reduced and the EV charges with a constant voltage. This is known as constant current (CC) and constant voltage (CV) charging. Furthermore, conventional energy management approaches often neglect the rate of change in EV charging power. Moreover, the BESS converter exhibits inherent response delays in adjusting power output.
[037] In order to overcome above listed prior art, the present invention aims to provide an energy management system (EMS) and method for the electric vehicle charging station (EVCS). In the present invention, charging power is prioritized based on consumer requests, considering charging power demand and waiting time, which helps in maximizing customer satisfaction even in high-occupancy scenarios. This invention explicitly accounts for these dynamic characteristics, enhancing the realistic and efficient EMS.
OBJECTS OF THE INVENTION:
[038] The principal object of the present invention is to provide an energy management system (EMS) and method for the electric vehicle charging station (EVCS), which may consist of photovoltaic (PV) system, battery energy storage system (BESS), grid and electric vehicle supply equipment (EVSE).
[039] Another object of the present invention is to provide an energy management system (EMS) reduce the operational cost of EV charging station while effectively mitigating strain on the power grid caused by sudden high-power demands from EVs.
[040] Yet another object of the present invention is to provide a viable solution for EV charging at commercial stations, workplaces, and residential areas.
[041] Still another object of the present invention is to provide a system for scheduling devices according to the grid tariff to minimize cost and yield maximum profit with different priority EVs at the EVCS.
[042] Yet another objective is to provide system dynamics such as power ramping in inverter, BESS, and EV charging along with the incorporation of CC-CV charging.
SUMMARY OF THE INVENTION:
[043] The present invention relates to an energy management system (EMS) for the Electric Vehicle charging station (EVCS), which may consist of photovoltaic (PV) system, battery energy storage system (BESS), grid and electric vehicle supply equipment (EVSE).
[044] In an aspect, the invention provides a controller related to EMS for commercial, workplace, and residential EV charging stations. The devices, according to the grid tariff, minimize cost and yield maximum profit with different priority EVs at the EVCS. Considering the system dynamics, such as the EV charging ramp, BESS power ramp and CC-CV charging.
[045] In an aspect, the system does not rely on predefined information about the EVs, such as EV models, arrival time, charging demand, parking time, etc. Further, it is adaptable to any changes in charging demand and parking time during charging.
[046] In an aspect, the invention reduces the operational cost of EV charging station while effectively mitigating strain on the power grid caused by sudden high-power demands from EVs. As a result, the developed controller offers a commercially viable solution for EV charging at commercial stations, workplaces, and residential areas. Moreover, it can also be used to manage other controllable loads.
BREIF DESCRIPTION OF THE INVENTION
[047] It is to be noted, however, that the appended drawings illustrate only typical embodiments of this invention and are therefore not to be considered for limiting of its scope, for the invention may admit to other equally effective embodiments.
[048] Fig. 1 is a schematic diagram of the system considered for EV charging at the public fast charging station.
[049] Fig. 2 is a schematic diagram of EV charging at the workplace/residential.
[050] Fig. 3 represents communication schematics among various devices at the EV charging station during on-site operation.
[051] Fig. 4 highlights Communication process between EVCS and developed controller for EMS.
[052] Fig. 5 shows the program module of the invented controller for EMS and its interface with the energy management algorithm.
[053] Fig. 6 shows the procedure for selecting the optimization horizon for the EV Coordination.
[054] Fig. 7 shows Procedure of energy management and EV coordination optimization.
[055] Fig. 8 illustrates the Implementation of the developed EMS for EVCS.
DETAILED DESCRIPTION OF THE INVENTION:
[056] The present invention provides an energy management system (EMS) for the Electric Vehicle charging station (EVCS), which may consist of photovoltaic (PV) system, battery energy storage system (BESS), grid and electric vehicle supply equipment (EVSE).
[057] The EMS comprises a main processing unit, communication link, data storage unit, and general-purpose input-output (GPIO). The communication link allows the exchange of information about the EVSEs and inverter with EMS to set the power set-points for the respective devices. Using this, EMS is performed in real-time, considering electric vehicle (EV) power requirements, EV arrival and departure times (reservation state information), charging priorities and grid energy tariff without relying on prior information about EVs. The set-points are assigned to EVSE and Inverter (every minute) for efficient cost optimization. Moreover, constant current (CC) – constant voltage (CV) charging, EV charging and BESS power ramps are considered for EV charging operations. The developed EMS is modular and scalable to any configuration of EVCS. The invented controller comprises a Linux-based single-board computer or a desktop with a Windows/Linux operating system or a virtual machine. The user can interact with the developed EMS using an Android or web-based application.
[058] Fig. 1 represents a commercial EV charging station. The EV 1 is connected to the EVSE 2, which can be either AC or DC type. The energy resources at the EVCS include a PV panel 3 and multiple BESS 4 units, configured in series and parallel to meet the required voltage and power ratings. Additionally, the station receives power from the grid 5. The critical non-controllable load 6 may consist of various dynamic light motor loads. An inverter 7 integrates these resources, loads, and the EVSEs. The inverter and charging station are managed by the Charging Station Management System (CSMS) 8 through an EMS controller. The real-time or time-of-use (ToU) grid energy tariff is retrieved from the Energy Exchange 9.
[059] Workplace or residential EV charging, along with energy management, are illustrated in Fig. 2. The controllable load 10, which includes appliances such as washing machines, tube wells, and heating systems, can be managed through the EMS. The EVSE used for residential EV charging is of the AC type 11. The charging station configuration may include as defined above but is not limited to these.
[060] Fig. 3 is an illustration of the communication from the EMS to the EVSE and the inverter. The communication card of the inverter can use the Modbus protocol to read and write the inverter status, grid power, BESS state of charge (SoC) and BESS power. Network Socket 12 facilitates communication among the inverter, EVSEs and EMS. For remote operations, IoT devices with Wi-Fi or cellular networks can replace the Network socket and Ethernet for communication.
[061] A schematic of the invented controller for EMS is presented in Fig. 4. In the case of EVSE, communication with the EV is established through the control pilot (CP) using power line communication (PLC) to set the charging power limit as per SAE J1772 or IEC 61851-1 standards. Further, in some DC EVSE cases, the Battery Management System (BMS) of the EV shares battery and vehicle data with the EVSE using the controller area network (CAN) protocol. This communication follows standards. This collected data is then transmitted to the Charging Station Management System (CSMS) via OCPP using Ethernet or Wi-Fi or a cellular network.
[062] The controller for EMS consists of a main processing unit and communication links, including Ethernet, Wi-Fi, serial communication, general purpose input-output (GPIO) and a data storage unit. However, this is the minimum hardware requirement but not limited to this. Ethernet and serial communication are used to transmit data between the EVSE, inverter, and controllable loads. EV users can interact with EMS through a web-based application.
[063] Regarding workplace or residential EV charging, as shown in Fig. 2, the EMS manages other controllable equipment through a GPIO pin.
[064] The data storage unit plays a crucial role in storing EMS-related information and the database of EV users and devices associated with the EVCS. This database stores data such as EV IDs, EVSE IDs, and EV charging-related information, among other details. However, it is not limited to a single device; it can be stored in the cloud and accessed via the Internet. Additionally, the storage unit also contains energy management algorithms for various operational scenarios. Additionally, it also stores the essential input data, including grid tariffs and PV generation forecasts, energy management decisions and power scheduling history. The energy management decisions can be logged for record-keeping and analysis.
[065] In EVSE with CP (PLC communication), the EVSE measures the charging current and energy consumed in the charging session, which will be shared with the CSMS unit through the OCPP protocol, as shown in Fig. 4. However, the BMS of the EV controls the charging power. Therefore, smart charging is managed by providing a maximum current limit from EMS. Where the BMS of EV draws less than or equal to the current from this current limit. In this type of EVSE, the web-based application provides information such as EV power rating, EV capacity, EV energy demand and parking time.
[066] In some DC-type EVSE, information about the EV, such as current SoC, EV power, EV capacity, etc., is available through CAN communication. Therefore, this information is directly shared with the CSMS unit through OCPP. Moreover, in this type of EVSE, the EV charging current can be set directly through the EMS. Therefore, smart charging becomes efficient and accurate. Hence, user information, such as EV energy demand and parking time, is only shared using the web-based application.
[067] Fig. 5 illustrates various program modules of EMS. These are the Database, PV forecasting module, grid tariff and EV pricing module, and CSMS. The PV generation forecast module uses weather data to forecast PV power, using an application programming interface (API). The grid energy pricing module interacts with energy exchange through API to get real-time or ToU energy tariffs. The EMS gets the inverter and controllable load data through communication as discussed earlier. The EMS executes various energy management algorithms based on different scenarios at the EVCS, as follows:
1. Based on real-time grid energy pricing for commercial charging stations.
2. Based on the ToU tariff for Residential and workplace EV charging.
3. Real-time energy management based on fixed grid energy tariff for residential EV charging.
4. Based on real scenarios, considerations include power charging ramping, constant current constant voltage (CC-CV) charging and power ramping in BESS.
[068] Consequently, the appropriate energy management algorithm is executed based on the preferences set by the EVCS operator.
[069] In the real-time or ToU grid energy tariff, energy management is carried out based on the latest departure time of the EVs at EVCS as shown in Fig. 6. Therefore, the energy demand for all EVs is satisfied. Furthermore, in the case of the new arrival, the energy optimization length is updated according to (1). Hence, the EV coordination optimization time slot is defined as (2). The EV coordination objective in (3) considers the satisfaction of the charging demand of each EV at EVCS and maximizes the revenue of the EVCS. Similarly, based on the decision of EV coordination, energy management objectives should consider the minimization of the operational cost of EVCS, optimum utilization of BESS and meeting of the EV power demand. These optimizations will ensure power balancing among the resources while maintaining operation within the energy and power limits of the devices at the EVCS.

(1)

(2)

(3)

(4)
Subject to:
(i) Power balancing among the loads and resources
i.e. Grid power + PV power + BESS power = EVs load + Controllable loads
(ii) Energy and power limits of devices

where,
k is set of EVSE,
t is the current time instant time instant
time remaining for the latest vehicle to departure
Tem is time slot for energy management
is time slots for EV coordination
Δt is the time step for EV coordination or EMS execution
Δtem is time steps for energy management
[070] In the first stage, the EMS determines the optimal available power at the charging station based on the status of the BESS, PV power generation and the power demand of EVs. Consequently, this available power is allocated among the EVs at the EVCS.
[071] The solution obtained from the above EV coordination and energy management problem, based on the current occupancy time slot TEV, is locally optimal. Although it does not account for grid energy tariff fluctuations and load variations throughout the day, it may result in higher operational costs for the EVCS. Therefore, it is necessary to consider the grid energy tariff variation and load curve in energy management over the day with the current status at EVCS. This will carry out considering the historical load data of the charging station. The current EV data within the time slot TEV replaces the historical average data of the EVCS, as shown in Fig.7. Here, the EV load forecast is the average historical load at the EVCS. This load may further be classified into weekends and weekdays.
[072] Furthermore, in energy management of a 24-hour time slot (Tem) of optimization, the time step for real-time Δt (1-5 minutes) of the optimization problem will be significantly large so that the computational time may surpass the EMS execution time limit. Therefore, energy management and EV coordination are performed with two different time steps. EV coordination is performed in fine temporal resolution (Δt) (1-5 min) such that CC-CV charging characteristics can be included and energy management is performed in course temporal resolution of 5-15 min for Δtem over a day, as shown in Fig. 7. Consequently, the time sample will reduce which in turn going to reduce computational time for real-time operation. This will not only give global optimal EV scheduling but also reduce the computational time of the energy management problem.
[073] Additionally, for the inclusion of realistic scenarios such as CC-CV charging, EV charging power ramp and BESS power ramp, the charging power of the EV and BESS power are updated at each energy management interval Δt as per (5) - (8).
 

(5)

(6)

(7)

(8)
where,
SOC is a state of charge of the EV, `
is the nominal charging power of an EV
is the maximum charging power of an EV
is BESS power
is the maximum change in power from time (t-1) to t for EV
is the maximum change in power from time (t-1) to t for BESS
a0, a1 and a2 are fitting parameters for CC-CV charging
[074] Moreover, in residential EV charging, where the grid energy tariff is fixed, energy management is carried out based on the consensus among the resources and the load. Based on this, the optimum charging set-point is given to the EVSE and inverter. In this algorithm, each resource tries to operate at an optimum point, i.e. grid power import is zero, PV utilization is maximum and BESS tries to maintain specific energy.
[075] In the above-discussed energy management, when power demand exceeds power generation at the charging station, the energy management method reduces the set-point from maximum power. Otherwise, the set-points are set to maximum power in case of more power generation.
[076] Similarly, in surplus power generation, the energy is either stored in the ESS or fed into the grid. The grid feeding depends on the grid energy tariff in the optimization horizon. Furthermore, energy storage in BESS depends on the BESS capacity. The BESS stores the energy when the grid energy tariff is low or surplus PV generation occurs. If BESS is fully charged, PV feeds the excess energy generation into the grid.
[077] Additionally, ramping in BESS power helps in preventing significant fluctuations in EV power output and battery deterioration. This ramping rate value is decided based on the EV load and battery parameters such as battery type, capacity and power rating.
[078] In the case of multiple EVSEs, the power set-points are defined based on consensus. This consensus is determined by the EV charging priority, which is decided by EV energy demand and parking time. Similarly, the EV charging price is also defined based on the EV charging priority and energy demand.
[079] Implementation of the EMS for EVCS
[080] The Implementation of the developed EMS is illustrated in Fig. 8. The CSMS receives information related to the EVSEs and users. Based on this, the total power demand is determined, which is sent to the energy management algorithm. Meanwhile, information related to various resources, such as SoC, power of BESS, inverter operation mode, etc., are received by EMS through the inverter. The information related to the grid energy pricing is obtained through energy exchange. The PV power generation forecasting is obtained from the PV forecasting module. Consequently, based on the objective function of EV coordination and energy management, the optimal power sharing among the resources and optimal set-points for the EVSEs are obtained. This optimal set-point is sent to the CSMS using open smart charging protocol (OSCP), which will be executed to the respective EVSEs at the EVCS through OCPP. Similarly, the optimal set-point for the inverter is executed through the Modbus protocol. This process continues for each EMS execution time.
[081] However, in case of a change in the parking time or the priority of EVs in the due period, the energy management algorithms can handle these uncertainties as the EMS executes considering recent information of the EVCS.
[082] Fig. 9 shows the EV charging with real-time grid energy tariff. The power allocation from Grid, PV, and BESS are depicted for the EV load at the charging stations.
[083] The BESS is utilized when the grid energy tariff is high or low PV power generation whereas in the case of a low grid energy tariff or excessive PV power generation, the BESS stores the energy. Moreover, 50% of BESS energy stores at the end of the day as a reserve for the next-day operation. Moreover, the BESS does not change mode from charging to discharging frequently due to ramping constraints. The charging power to EVs, as shown in Fig. 10, follows the CC-CV charging power profile and power ramping.
[084] Similarly, energy management performed in the fixed grid energy tariff case, shown in Fig.11. It is observed that utilization of BESS is more frequent since the grid energy tariff is fixed. Moreover, SoC of BESS is trying to maintain about half the total capacity.
[085] In this simulation, the weather forecast is obtained using an API. Based on this, real-time PV power generation is obtained from the PV power forecasting model.
[086] During the operation, the power reference is set to each EV based on the EV user's information and power demand. After each set-point, the optimization is performed up to the time horizon but executes for time step Δt. Therefore, in the meantime, if users charge, the energy demand and parking time are also considered.
[087] Numerous modifications and adaptations of the system of the present invention will be apparent to those skilled in the art, and thus it is intended by the appended claims to cover all such modifications and adaptations which fall within the true spirit and scope of this invention.
, Claims:WE CLAIM:
1. A energy management system (EMS) for the electric vehicle charging station (EVCS) comprises-
a) Electric vehicle EV (1) is connected to the electric vehicle supply equipment (EVSE) (2),
b) The energy resources at the electric vehicle charging station (EVCS) characterized in that a PV panel (3) and multiple BESS (4) units, configured in series and parallel to meet the required voltage and power ratings.
c) Grid (5) for providing power to the station.
d) The critical non-controllable load (6) characterizing various dynamic light motor loads.
e) An inverter (7) integrates these resources, loads, and the EVSE wherein the inverter and charging station are managed by the charging station management system (CSMS) (8) through an EMS controller.
f) The real-time or time-of-use (ToU) grid energy tariff is retrieved from the energy exchange (9).
g) The controllable load (10), managed through the EMS.
h) The electric vehicle supply equipment (EVSE) (2), used for residential EV charging is of the AC type (11).
2. The energy management system (EMS) for the electric vehicle charging station (EVCS), as claimed in claim 1, wherein the controller for EMS consists of a main processing unit and communication links, including Ethernet, Wi-Fi, serial communication, general purpose input-output (GPIO) and a data storage unit.
3. The energy management system (EMS) for the electric vehicle charging station (EVCS), as claimed in claim 1, wherein the electric vehicle supply equipment (EVSE) (2) is either AC or DC type.
4. The energy management system (EMS) for the electric vehicle charging station (EVCS), as claimed in claim 1, wherein in the case of electric vehicle supply equipment (EVSE) (2) communication with the EV is established through the control pilot (CP) using power line communication (PLC) to set the charging power limit.
5. The energy management system (EMS) for the electric vehicle charging station (EVCS), as claimed in claim 1, wherein some DC EVSE cases, the Battery Management System (BMS) of the EV shares battery and vehicle data with the EVSE using the controller area network (CAN) protocol and the collected data is then transmitted to the charging station management system (CSMS) via OCPP using Ethernet or Wi-Fi or a cellular network.
6. The energy management system (EMS) for the electric vehicle charging station (EVCS), as claimed in claim 1, wherein the EV coordination is performed in fine temporal resolution (Δt) (1-5 min) such that CC-CV charging characteristics can be included and energy management is performed in course temporal resolution of 5-15 min for Δtem over a day.
7. The energy management system (EMS) for the electric vehicle charging station (EVCS), as claimed in claim 1, wherein the database, PV forecasting module, grid tariff and EV pricing module, and CSMS. The PV generation forecast module uses weather data from meteorology to forecast PV power, using an application programming interface (API). The grid energy pricing module interacts with energy exchange through API to get real-time or ToU energy tariffs.