Description:FIELD OF THE INVENTION

[0001] The present invention relates to a decentralized energy management system for multi-point renewable integration in microgrids that is capable of providing a means to decentralized energy for proficient energy by improving and balancing the supply demand in real time.

BACKGROUND OF THE INVENTION

[0002] Decentralized energy refers to the generation and distribution of power at or near the point of consumption, using localized sources such as solar panels, wind turbines, or small-scale generators, rather than relying solely on centralized power plants. This approach enhances energy resilience, reduces transmission losses, and allows for greater integration of renewable resources, making the energy system more flexible and sustainable. By empowering communities or individual users to produce their own electricity, decentralized energy systems can improve reliability, support grid stability, and promote energy independence while enabling more efficient and environmentally friendly power management.

[0003] Traditionally, decentralized energy systems have involved small-scale generators like individual solar panels, wind turbines, or local diesel generators, providing power primarily for specific households, farms, or communities. While these systems promote local autonomy and reduce dependence on centralized grids, they have notable drawbacks, including limited capacity to meet high energy demands, challenges in maintaining consistent and reliable power supply, and difficulties in integrating multiple small sources into a stable grid due to technical complexities. Additionally, decentralized systems often lack economies of scale, making them more expensive per unit of energy produced, and may face issues with maintenance and regulatory support, ultimately restricting their effectiveness as standalone solutions for broader energy needs. The existing devices do not dynamically optimize real-time energy storage and distribution across multiple sources.

[0004] US20190065432A1 discloses a utilizing function apparatus include at least one processor, and a memory storing instructions that, when executed by the at least one processor, causes the at least one processor to, based on an operation, set one of at least one function temporarily unable to be executed, when it is detected that the utilizing function apparatus is connected to an external device after setting the one function temporarily unable to be executed, acquire information about an area of the memory of the utilizing function apparatus, as first information, when it is detected that the connection with the external device is released, acquire the information about the area of the memory, as second information, and when the acquired first information and second information are different, set the one function back able to be executed.

[0005] WO2020102832A1 The invention relates to a component having a solid structure, manufactured by a laser- or electron beam in an additive manufacturing process, from at least one material selected from a group comprising molybdenum, a molybdenum-based alloy, tungsten, or a tungsten-based alloy, and relates to a component having a solid structure, manufactured by a laser- or electron beam in an additive manufacturing process, from at least one material selected from a group comprising molybdenum, a molybdenum-based alloy, tungsten, a tungsten-based alloy and a molybdenum-tungsten based alloy, said component having one or more alloying element which has or have - in the case of molybdenum and the molybdenum-based alloy a reductive action on MoO2 and/or MoO3 -, in the case of tungsten and the tungsten-based alloy a reductive action on WO2 and/or WO3 , and - in the case of the molybdenum-tungsten based alloy a reductive action on at least one oxide of the group containing MoO2 and/or MoO3 , WO2 and WO3 , at least in the temperature range ≥ 1500 °C, the alloying element or at least one of the alloying elements being present both in at least partially non-oxidised form and oxidised form.

[0006] Conventionally, many system have been developed to manage the resources but the existing management systems lack providing the energy from the multiple renewable source in the real time and they are unable reduce the dependency on the central unit by enabling distributed decision-making in the energy dispatch.

[0007] In order to overcome the aforementioned drawbacks, there exists a need in the art to develop a device that is capable of providing a means to decentralized energy for proficient energy allocation of a greater number of renewable sources and storage units and reducing the dependency to the central unit by enabling distributed decision-making in the energy dispatch.

OBJECTS OF THE INVENTION

[0008] The principal object of the present invention is to overcome the disadvantages of the prior art.

[0009] An object of the present invention is to develop a device that is capable of providing a means to decentralized energy for proficient energy allocation of a greater number of renewable sources and storage units.

[0010] Another object of the present invention is to develop a device that is capable of improving the grid equilibrium by balancing the supply and the demand in real time.

[0011] Another object of the present invention is to develop a device that is capable of enhancing utilization of the storage through improved charging and discharging.

[0012] Yet another object of the present invention is to develop a device that is capable of reducing dependence on centralized control by enabling distributed decision-making in the energy dispatch.

[0013] The foregoing and other objects, features, and advantages of the present invention will become readily apparent upon further review of the following detailed description of the preferred embodiment as illustrated in the accompanying drawings.

SUMMARY OF THE INVENTION

[0014] The present invention relates to a decentralized energy management system for multi-point renewable integration in microgrids that is capable of providing direct energy from multiple point renewable resources and balancing the supply and the demand of energy in real time. Additionally, the device is capable of enhance utilization of the storage energy.

[0015] According to an embodiment of the present invention, a decentralized energy management system for multi-point renewable integration in microgrids comprises of multiple primary energy nodes associated with the system to harvest electricity from wind or solar radiation, the primary energy nodes includes but not limited to wind turbines and solar panels, a primary processor and primary communication module, connected in a network to share data and make direct renewable energy distribution to loads, multiple secondary energy nodes associated with the system to store excess electricity, the secondary energy nodes includes but not limited to battery storage and grid a secondary processor and secondary communication module, connected in the network to share data regarding demand of energy, and distribute energy to loads.

[0016] According to another embodiment of the present invention, the device further includes a load-balancing module provided in each energy node that communicates with other nodes to adjust energy supply and demand, ensuring maximum renewable energy use and stable grid operation, a weather forecasting module associated with the system to monitor weather conditions and predicts energy generation from primary nodes and manages battery charging and discharging to minimize energy waste, the weather forecasting module includes a rain sensor, light dependent resistor, position sensitive detectors, and anemometers, a distributed control protocol encrypted in processers of each energy nodes, which processes generation and consumption data to dynamically allocate energy resources across the micro grid.

[0017] While the invention has been described and shown with particular reference to the preferred embodiment, it will be apparent that variations might be possible that would fall within the scope of the present invention.

BRIEF DESCRIPTION OF THE DRAWINGS

[0018] These and other features, aspects, and advantages of the present invention will become better understood with regard to the following description, appended claims, and accompanying drawings where:
Figure 1 illustrates a flowchart depicting the workflow of a decentralized energy management system for multi-point renewable integration in microgrids.

DETAILED DESCRIPTION OF THE INVENTION

[0019] The following description includes the preferred best mode of one embodiment of the present invention. It will be clear from this description of the invention that the invention is not limited to these illustrated embodiments but that the invention also includes a variety of modifications and embodiments thereto. Therefore, the present description should be seen as illustrative and not limiting. While the invention is susceptible to various modifications and alternative constructions, it should be understood, that there is no intention to limit the invention to the specific form disclosed, but, on the contrary, the invention is to cover all modifications, alternative constructions, and equivalents falling within the spirit and scope of the invention as defined in the claims.

[0020] In any embodiment described herein, the open-ended terms "comprising," "comprises,” and the like (which are synonymous with "including," "having” and "characterized by") may be replaced by the respective partially closed phrases "consisting essentially of," consists essentially of," and the like or the respective closed phrases "consisting of," "consists of, the like.

[0021] As used herein, the singular forms “a,” “an,” and “the” designate both the singular and the plural, unless expressly stated to designate the singular only.

[0022] The present invention relates to a decentralized energy management system for multi-point renewable integration in microgrids that is capable of utilizing the energy from multi-point renewable integrated resources, improving and balancing the supply and demand of the energy in the real time and manage to store the energy for further use.

[0023] Referring to Figure 1, a flowchart depicting the workflow of decentralized energy management system for multi-point renewable integration in microgrids. The system disclosed herein discloses the distribution of the energy to the load by multipoint renewable integration in microgrid while balancing the demand of the energy and utilizing the stored energy.

[0024] When there is energy demand in a microgrid, a microcontroller activates a multiple primary energy nodes to harvest energy. The multiple primary energy node works by integrating various energy-harvesting sources at a single node to optimize energy generation based on availability and environmental conditions. Each "primary node" is equipped with multiple energy harvesting technologies such as solar panels, wind turbines sensors that operate simultaneously.

[0025] The microcontroller check the availability of the renewable energy from wind and solar radiation but not only limited to wind turbines and solar panels.

[0026] The Solar panels harvest energy through the photovoltaic effect, where sunlight is converted directly into electricity using semiconductor materials, silicon. When photons from sunlight strike the surface of a solar cell, they excite electrons in the silicon atoms, freeing them from their atomic bonds. The cell is constructed with two layers of silicon one doped with phosphorus (n-type) to add extra electrons, and the other with boron (p-type) to create "holes" or positive charges forming a p-n junction. This junction creates an electric field that drives the freed electrons toward metal contacts, generating a direct current (DC). The DC electricity is then used immediately or stored.

The wind turbine harvests energy by converting the kinetic energy of moving air (wind) into mechanical energy, and then into electrical energy. As wind flows over the turbine blades, their aerodynamic shape creates a pressure difference higher pressure on one side and lower on the other causing the blades to spin. This rotational motion turns a shaft connected to a gearbox, which increases the rotation speed and drives a generator. Inside the generator, the rotation of magnets around coils of wire (or vice versa) induces an electric current through electromagnetic induction, producing alternating current (AC) electricity. This electricity is then regulated and stored.

[0027] If the renewable energy from the primary nodes is available, a primary processor provided with each of the node connected in the network process the data and share the data about the renewable energy to a primary communication module. This processor collects real-time data from sensors monitoring parameters such as solar irradiance, wind speed. It processes this data locally to analyze performance, predict availability, and optimize energy harvesting. The processor then formats and transmits this data via wireless communication protocols to a central hub or other nodes in distributed energy management network.

[0028] The primary communication module connected with the network distribute of the energy to loads. The primary communication module works by enabling real-time data exchange between nodes, loads, and the central management system. It operates using communication protocols such as, Wi-Fi, to transmit and receive data about energy availability, load demands, storage levels, and grid status. Based on this information, the module interacts with the local energy management system and switches to control when and how much energy is directed to each load. It ensures load prioritization, demand-response actions, and energy routing decisions such as drawing from local sources or redirecting surplus to other nodes by executing control logic either locally or as instructed by a central controller. This ensures efficient, reliable, and balanced energy distribution across the network, minimizing waste and maximizing the use of renewable sources.

[0029] If in case there is an insufficient amount of energy supply from the primary nodes, the microcontroller operatively commands, multiple secondary nodes are associated with the system. The secondary nodes stores energy in battery and grid but they are not only limited to battery storage and grid.

[0030] The battery stores energy through electrochemical reactions that convert electrical energy into chemical potential energy within its cells. During charging, an external power source supplies electricity, causing reduction and oxidation reactions at the electrodes, lithium ions move from the cathode to the anode through an electrolyte, storing energy chemically. When discharging, these chemical reactions reverse, releasing stored energy as electrical current to supply power to the grid or load. In a microgrid, batteries act as energy buffers, absorbing excess renewable generation during periods of high supply and discharging during periods of low generation or high demand, thus maintaining grid stability and balancing supply and load. The process involves precise control of charging/discharging rates, voltage levels, and state-of-charge management to optimize battery lifespan and performance, ensuring efficient energy storage and release aligned with grid requirements.

[0031] While storing the energy, a secondary processor connected in the network, process the availability of storage energy and share the data to a secondary communication module. The secondary processor connected within the network functions as a controller that monitors the status of energy in batteries by continuously collecting data on parameters like state of charge, voltage, current, and temperature through communication interfaces.

[0032] If the storage energy is available in the secondary node, the microcontroller commands the secondary communication module that is connected with the network to distribute the energy from the storage to the loads. The secondary communication module facilitates the distribution of stored energy from the battery to loads by acting as an interface that manages control signals and data exchange between the energy management system and power conversion. It receives commands like when to discharge or regulate power flow from the processor via protocols such as wireless communication. Based on these commands, the module activates or modulates power electronic devices, such as DC/DC converters or inverters, to efficiently transfer energy from the storage units to the loads. It continuously monitors parameters like current, voltage, and load demand, adjusting the power output dynamically to ensure stable and safe energy delivery. This coordinated operation enables the system to optimize energy supply, maintain grid stability, and prevent overloads, effectively distributing stored energy where and when it is needed most.

[0033] If the energy is insufficient in the secondary nodes as well, then the microcontroller commands to draw the energy from the grid. The electrical grid facilitates energy storage and management by coordinating the flow of electricity between generation sources, storage like batteries. When excess electricity such as from renewable sources like solar or wind is produced, the grid directs this surplus to charge connected energy storage systems, converting and storing it as chemical or electrical energy. During periods of high demand or low generation, the grid discharges stored energy from batteries and other storage units by releasing electricity back into the network to stabilize supply and maintain voltage and frequency within acceptable limits. This process manage the charging and discharging cycles, ensuring seamless energy transfer while maintaining grid stability. Overall, the grid acts as a dynamic platform that balances supply and demand through real-time monitoring and control, enabling efficient energy storage and retrieval to support reliable power delivery

[0034] The load balancing module provided in the grid adjust energy and supply demand ensuring the maximum renewable energy and stable grid operation. The load balancing module functions by continuously monitoring real-time data on energy generation, storage levels, and demand across the grid. It dynamically adjusts power distribution shifting loads, modulating renewable energy inputs, and controlling energy storage discharge to match supply with demand. It employ predictive analytics to forecast fluctuations in renewable sources like solar or wind, enabling proactive adjustments. The module communicates with various system components via communication protocols to coordinate actions such as increasing storage discharge during low renewable output or curtailing non-essential loads during peak demand. By balancing load and generation in this manner, it maximizes the utilization of renewable energy, minimizes reliance on conventional power sources, and maintains grid stability, preventing issues like voltage fluctuations or overloads, thus ensuring a reliable and sustainable energy supply

[0035] Each of the energy nodes has a distributed controlled protocol encrypted in the processors. The distributed controlled protocol processes generation and consumption data to dynamically allocate the energy resources across the micro grid. The distributed control protocol operates by enabling each node within the microgrid such as storage units, and loads to independently collect and process local data on energy generation, consumption, voltage, and frequency using load balancing sensors and communication modules. These nodes exchange real-time data with neighboring units via a distributed communication network, facilitating decentralized decision-making. Each node analyze the shared data to determine optimal actions, such as adjusting power output, charging or discharging storage, or modulating load demand. This process allows the microgrid to dynamically allocate energy resources in response to changing conditions without relying solely on a centralized controller, ensuring efficient, balanced, and resilient operation by collectively optimizing energy flow, preventing overloads, and maximizing renewable energy utilization across the network.

[0036] To predict the energy generation from the primary nodes and manage the charging and discharging, a weather forecasting module is associated with the system. The module monitor the weather conditions and predicts the generation of the energy from the nodes and manages battery charging and discharging to minimize energy waste. The weather forecasting module utilizes meteorological data from sensors, to monitor current atmospheric conditions like sunlight intensity, wind speed, temperature, and cloud cover. It processes this data to generate short-term and long-term forecasts of renewable energy generation potential at different nodes within the system. Based on these predictions, the module dynamically optimizes battery charging and discharging schedules by coordinating with energy management systems, ensuring that excess renewable generation is stored during periods of high output and discharged during low-generation intervals. This proactive approach minimizes energy waste, enhances grid stability, and maximizes renewable energy utilization by aligning energy storage activities with anticipated resource availability, thereby ensuring efficient and sustainable operation of the energy system.

[0037] The weather forecasting module for monitoring the weather conditions include a rain sensor, a light dependent sensor, a positive sensitive detectors and anemometers.

[0038] The rain sensor operates by detecting the presence of water droplets on its surface, typically using a conductive sensing process. When raindrops accumulate, they bridge conductive traces, triggering a signal that indicates rainfall. This information helps the system determine precipitation levels, enabling adjustments in energy management or safety protocols during wet conditions.

[0039] The Light Dependent Resistor (LDR) functions by changing its electrical resistance in response to ambient light intensity. Under bright light conditions, the resistance decreases, allowing more current to flow, while in darkness, resistance increases significantly. By measuring this resistance variation, the system assess sunlight levels, which is crucial for predicting solar energy generation and adjusting operations accordingly.

[0040] The positive sensitive detectors, phototransistors, operate by converting incident light into electrical current. When exposed to light, these sensors generate a proportional current or voltage, enabling precise measurement of light intensity. They are essential for monitoring parameters like sunlight quality and intensity, contributing to accurate weather forecasting.

[0041] Anemometers are devices used to measure wind speed and, in some designs, wind direction. Mechanical anemometers use rotating cups or vanes driven by wind flow to determine speed based on rotational velocity. Ultrasonic anemometers utilize ultrasonic sound waves between transducers; the change in transit time caused by wind flow allows for highly accurate, contactless measurement of wind velocity. These measurements are critical for assessing wind energy potential and ensuring safe, efficient operation of wind turbines within the microgrid.

[0042] The present invention works best in the following manner, the multiple primary energy nodes harvest energy by solar energy and wind turbine. The primary processor and primary communication module, connected in a network to share data and make direct renewable energy distribution to loads. The multiple secondary energy nodes associated with the system store excess electricity, the secondary processor and secondary communication module like battery and grid, connected in the network to share data regarding demand of energy, and distribute energy to loads, in case of insufficient amount of energy supply from primary nodes. The load-balancing module provided in each energy node that communicates with other nodes to adjust energy supply and demand, ensuring maximum renewable energy use and stable grid operation. The weather forecasting module associated with the system includes a rain sensor, light dependent resistor, position sensitive detectors, and anemometers monitor weather conditions and predicts energy generation from primary nodes and manages battery charging and discharging to minimize energy waste. distributed control protocol encrypted in processers of each energy nodes, which processes generation and consumption data to dynamically allocate energy resources across the micro grid.

[0043] Although the field of the invention has been described herein with limited reference to specific embodiments, this description is not meant to be construed in a limiting sense. Various modifications of the disclosed embodiments, as well as alternate embodiments of the invention, will become apparent to persons skilled in the art upon reference to the description of the invention. , Claims:1) A decentralized energy management system for multi-point renewable integration in microgrids, comprising:

i) multiple primary energy nodes associated with the system to harvest electricity from wind or solar radiation, wherein each node are provided with a primary processor and primary communication module, connected in a network to share data and make direct renewable energy distribution to loads;
ii) multiple secondary energy nodes associated with the system, to store excess electricity, wherein a secondary processor and secondary communication module, connected in the network to share data regarding demand of energy, and distribute energy to loads, in case of insufficient amount of energy supply from primary nodes;
iii) a load-balancing module provided in each energy node that communicates with other nodes to adjust energy supply and demand, ensuring maximum renewable energy use and stable grid operation; and
iv) a weather forecasting module associated with the system to monitor weather conditions and predicts energy generation from primary nodes and manages battery charging and discharging to minimize energy waste.

2) The system as claimed in claim 1, wherein the primary energy nodes includes but not limited to wind turbines and solar panels.

3) The system as claimed in claim 1, wherein the secondary energy nodes includes but not limited to battery storage and grid.

4) The system as claimed in claim 1, wherein the weather forecasting module includes a rain sensor, light dependent resistor, position sensitive detectors, and anemometers.

5) The system as claimed in claim 1, wherein a distributed control protocol encrypted in processers of each energy nodes, which processes generation and consumption data to dynamically allocate energy resources across the micro grid.