Description:FIELD OF THE INVENTION

[0001] The present invention relates to a decentralized microgrid energy management system with adaptive control and fault isolation that provides continuous and autonomous monitoring, across distributed energy resources, thus enabling stable and resilient operation of localized energy networks without reliance on a centralized control infrastructure.

BACKGROUND OF THE INVENTION

[0002] In recent years, decentralized energy approaches have emerged, enabling local energy generation and consumption through microgrids. However, current microgrid solutions still rely heavily on centralized control logic, which becomes a single point of failure, during communication breakdowns or grid faults.

[0003] Traditional energy distribution is largely dependent on centralized grid systems where a central authority controls generation, distribution, and monitoring of electricity across large geographic areas, creating a pressing need for an autonomous system that enables each local energy controller to independently manage its connected devices, efficiently adapt to real-time demand and supply changes.

[0004] CN118432125A discloses a micro-grid energy storage optimization scheduling method and system based on artificial intelligence, relates to the field of smart grids, and solves the defects of poor real-time performance, difficulty in algorithm parameter adjustment and optimization and insufficient system safety consideration in the existing micro-grid energy storage optimization scheduling method. Comprising an intelligent sensing module, a real-time data transmission module, a dynamic scheduling optimization module, a system safety monitoring module, a prediction analysis module, an intelligent coordination control module, a real-time monitoring and alarm module and a user interaction interface module. Data are processed and transmitted in real time through the real-time data transmission module, so that the real-time performance of the system is improved; optimal scheduling of the micro-grid energy storage system is realized through an optimal scheduling algorithm based on deep reinforcement learning; encrypting, storing and verifying system data through a homomorphic encryption model based on the block chain; according to the invention, the efficiency and performance of the existing microgrid energy storage optimization scheduling method are greatly improved.

[0005] CN112636385A discloses a microgrid control method for multi-energy-flow complementary control. The method comprises the following steps: S1, locally consuming distributed energy of a microgrid; S2, carrying out peak clipping and valley filling of the AC/DC microgrid, and charging and carrying out discharging control through the charging and discharging time periods of a planned curve and the charging and discharging power values corresponding to the charging and discharging time periods according to a planned curve mode; and S3, freely switching between a grid-connected state and an off-grid state of the alternating-current and direct-current microgrid. Coordinated control over sources, networks, loads and storage of substations, data center stations, high-capacity comprehensive energy stations and the like is achieved, the big data mining technology is utilized, the operation strategy is adjusted in real time, the advantages of source, network, load and storage complementation are brought into full play, and the reliability of the microgrid and the comprehensive benefits of a power grid are improved.

[0006] Conventionally, many systems for microgrid energy management have relied on centralized controllers that supervise energy production, storage, and distribution. These existing systems often lack flexibility, and when communication with the central unit is lost, the entire microgrid's operation become unstable or non-functional. Moreover, traditional systems frequently fail to incorporate adaptive energy balancing, real-time fault isolation, and predictive resource optimization, often in environments powered by intermittent renewable sources such as solar or wind.

[0007] In order to overcome the aforementioned drawbacks, there exists a need in the art to develop a system that requires to be capable of enabling each local controller to function independently while remaining coordinated, providing real-time energy optimization and distribution without relying on a centralized infrastructure.

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 system that enables adaptive and autonomous control of distributed energy resources to maintain uninterrupted and efficient energy flow within local energy networks.

[0010] Another object of the present invention is to develop a system that is capable of monitoring and controlling its device to produce, store, or use energy efficiently without a central system.

[0011] Another object of the present invention is to develop a system to manage energy production and direct it to the building or storage for efficient use.

[0012] Another object of the present invention is to develop a system that is capable to find and isolate the problems of the microgrid to keep the microgrid working.

[0013] Another object of the present invention is to develop a system to adjust energy use based on real-time demand and supply to maintain efficiency of the microgrid.

[0014] Another object of the present invention is to develop a system to predict solar power output to plan energy use better for the microgrid.

[0015] Another object of the present invention is to develop a system to allow devices to work alone during network or device failures in the microgrid.

[0016] Another object of the present invention is to develop a system to manage power exchange with the grid for stable operation in connected mode.

[0017] 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

[0018] The present invention relates to a decentralized microgrid energy management system with adaptive control and fault isolation that automatically regulates distributed energy generation, storage, and consumption, thereby ensuring continuous power delivery, optimizing resource usage, and supporting self-sustained energy infrastructure.

[0019] According to an embodiment of the present invention, a decentralized microgrid energy management system with adaptive control and fault isolation, comprising a plurality of local controller communicatively connected to energy devices and a secure network to monitor and control its device, a renewable energy management module linked to renewable sources and local controllers to manage energy production, an energy storage management module connected to batteries and local controllers to decide when to charge or use battery energy, a fault detection and isolation unit inbuilt into local controllers to find and isolate device problems.

[0020] According to another embodiment of the present invention, the system further includes an adaptive energy management unit linked to all controllers and the building’s energy system to adjust energy use based on real-time demand and supply, a voltage stabilizer connected to local controllers and energy devices to keep voltage, a solar forecasting tool linked to the renewable energy module and weather data to predict solar power output, a battery health monitoring tool connected to the storage module, a backup operation protocol inbuilt into local controllers and the fault system to allow devices to work alone and a grid interaction unit connected to the adaptive system and utility grid for stable operation in connected mode.

[0021] 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

[0022] 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 block diagram of a decentralized microgrid energy management system with adaptive control and fault isolation.

DETAILED DESCRIPTION OF THE INVENTION

[0023] 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.

[0024] 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.

[0025] 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.

[0026] The present invention relates to a decentralized microgrid energy management system with adaptive control and fault isolation that monitors and regulates environmental and operational parameters while establishing dynamic control thresholds to maintain system stability, minimize energy losses, and issue real-time alerts for efficient intervention and decision-making.

[0027] Referring to Figure 1, a block diagram of a decentralized microgrid energy management system with adaptive control and fault isolation is illustrated, comprising a plurality of local controller connected to energy devices (solar panels, batteries, appliances), a voltage stabilizer connected to local controllers and energy systems, a renewable energy management module linked to renewable sources (solar panels, wind turbines) and local controllers, a solar forecasting tool linked to the renewable energy module and weather data, an energy storage management module connected to batteries and local controllers, a fault detection and isolation unit inbuilt into local controllers, a backup operation protocol inbuilt into local controllers and the fault system, an adaptive energy management unit linked to all controllers and the building’s energy system, a battery health monitoring tool connected to the storage module and a grid interaction unit connected to the adaptive system and utility grid to manage power exchange with the grid for stable operation in connected mode.

[0028] The system disclosed herein includes multiple local controllers, each linked to energy devices such as solar panels, batteries, and appliances. These controllers are connected through a secure communication network and are responsible for monitoring and managing the operation of their associated devices.

[0029] Each controller independently makes decisions about energy production, storage, and consumption without relying on a central unit, allowing for decentralized energy control. To ensure consistent and stable power delivery, a voltage stabilizer is integrated between each local controller and the connected energy devices. The stabilizer regulates voltage fluctuations, preventing power instability and helping to maintain the reliable operation of the entire microgrid.

[0030] Along with the local controllers, a renewable energy management module is connected to renewable sources such as solar panels and wind turbines. The renewable energy management module oversees the generation of energy from these sources and efficiently distributes it either to the building for immediate use or to storage units for later use.

[0031] To enhance decision-making, a solar forecasting tool is integrated with the renewable energy management module. The solar forecasting tool uses real-time and predicted weather data to estimate future solar power generation. By anticipating the amount of solar energy that will be available, the renewable energy management module plan energy distribution more effectively, optimizing both usage and storage while reducing reliance on non-renewable energy sources.

[0032] The solar forecasting tool disclosed above operates by collecting real-time and historical weather data, including sunlight intensity, cloud cover, temperature, and humidity. The solar forecasting tool uses this data to estimate the amount of solar radiation expected at a specific location. The models, often incorporating machine learning or statistical techniques, analyze the patterns to predict short-term and long-term solar energy generation. These forecasts are then shared with the renewable energy management module to help plan when and how solar power is available, improving energy allocation and storage decisions of the microgrid.

[0033] To monitor the energy allocation and storage decisions of the microgrid, a energy storage management module functions by constantly monitoring the battery charge levels, energy production from renewable sources, and real-time consumption within the building. Based on this information, the module decides optimal charging and discharging times.

[0034] When excess energy is generated (e.g., during peak solar hours), it directs power to the batteries for storage. During low generation or high demand periods, it releases stored energy to maintain uninterrupted power supply, ensuring efficient energy use, and helps the microgrid remain self-sufficient and cost-effective.

[0035] A fault detection and isolation unit is included in the system that operates by continuously monitoring the performance and condition of energy devices through sensors embedded in local controllers. When an abnormal condition or malfunction, such as voltage fluctuation, device failure, or communication loss is detected, the fault detection and isolation unit identifies the faulty component.

[0036] After detecting the faulty component, the fault detection and isolation unit then isolates the affected component from the rest of the microgrid to prevent disruption. Simultaneously, the fault detection and isolation unit sends real-time alerts through the network to inform about maintenance.

[0037] An adaptive energy management unit is included in the system which functions by continuously collecting real-time data from all local controllers and the building’s energy consumption points. It analyzes the current energy demand within the building and compares it with the available energy supply from renewable sources and storage units.

[0038] Based on this analysis, the adaptive energy management unit dynamically adjusts the operation of energy devices such as increasing storage usage during peak demand or reducing consumption when supply is low, maintaining an optimal energy balance and also reducing waste, for uninterrupted energy usage across the microgrid.

[0039] A grid interaction is linked with adaptive energy management unit with the external utility grid, enabling two-way communication and energy transfer. The grid interaction monitors the status of the microgrid and the utility grid to determine when to import electricity during local shortages or export surplus energy when local generation exceeds demand.

[0040] The grid interaction ensures synchronization between the microgrid and the main grid, and manages voltage and frequency stability during the exchange, and transition between islanded and grid-connected modes. As a result, the grid interaction enhances the reliability of the microgrid during operation.

[0041] A battery health monitoring tool is connected to the storage module, which functions by continuously analyzing the condition of the batteries connected to the storage module. The battery health monitoring tool measures key parameters such as voltage, current, temperature, and state of charge (SoC) in real time.

[0042] Using this data, the battery health monitoring tool estimates the state of health (SoH), cycle count, and potential degradation of each battery. When abnormalities or performance drops are detected, the battery health monitoring tool sends alerts to the energy storage management module for corrective action, such as load balancing or battery replacement scheduling.

[0043] A backup operation protocol is configured into local controllers and the fault system functions by enabling each local controller to operate independently when network connectivity or other device components fail. The backup operation protocol is embedded within the local controllers and works alongside the fault detection system.

[0044] When a failure is detected such as loss of communication with the central grid or malfunction of neighboring controllers, the backup operation protocol activates autonomous control logic, allowing the affected controller to continue managing its connected energy devices (e.g., solar panels, batteries, appliances). The backup operation protocol maintains energy balance using pre-set rules and recent data, ensuring uninterrupted power supply and system stability even during partial outages or isolated conditions.

[0045] The present invention works best in the following manner, where the plurality of local controllers are deployed across different energy nodes within the microgrid, each connected to respective solar panels, batteries, and appliances. These local controllers constantly monitor the energy flow using embedded sensors and control energy devices directly without needing the central management hub. Voltage stabilizers connected between the controllers and energy devices regulate voltage fluctuations to ensure stable operation. The renewable energy management module, interfaced with both the local controllers and renewable energy sources continuously assesses generation capacity. The solar forecasting tool linked to the renewable energy management module receives weather data and predicts solar output to optimize energy allocation between immediate use and storage. Based on this prediction and current demand, the module directs energy either to buildings for use or to the storage module. The energy storage management module operates in coordination with battery banks and the local controllers to determine when to charge or discharge batteries. The battery health monitoring tool continuously evaluates battery temperature, charge cycles, and capacity retention, sending diagnostic reports to optimize battery life and performance.

[0046] In continuation, during periods of low generation, stored energy is discharged to maintain building power supply. Fault detection and isolation units are embedded within each local controller and consist of integrated sensors and communication interfaces. These units constantly scan for abnormalities such as current drops or thermal anomalies, and when faults are detected, they isolate the affected component or node without interrupting the entire grid operation. The backup operation protocol within the controller ensures that energy devices function autonomously even when network links fail. The adaptive energy management unit oversees energy balance across the entire microgrid. It communicates with all local controllers and dynamically adjusts consumption and storage commands based on real-time supply-demand conditions. When operating in a connected mode, the grid interaction unit coordinates power exchange between the local network and the main utility grid. This includes exporting surplus energy or drawing external supply when local generation is insufficient, thus maintaining stability and optimal efficiency of the entire microgrid environment.

[0047] 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 microgrid energy management system with adaptive control and fault isolation, comprising:

i) a plurality of local controller communicatively connected to energy devices (solar panels, batteries, appliances) and a secure network to monitor and controls its device to produce, store, or use energy efficiently without a central system;
ii) a renewable energy management module linked to renewable sources (solar panels, wind turbines) and local controllers to manage energy production and directs it to the building or storage for efficient use;
iii) an energy storage management module connected to batteries and local controllers to decide when to charge or use battery energy to save power and keep the building running;
iv) a fault detection and isolation unit inbuilt into local controllers with sensors and network alerts to find and isolate device problems to keep the micro grid working; and
v) an adaptive energy management unit linked to all controllers and the building’s energy system to adjust energy use based on real-time demand and supply to maintain efficiency.

2) The system as claimed in claim 1, wherein a voltage stabilizer is connected to local controllers and energy systems to keep voltage steady to prevent power issues in the microgrid.

3) The system as claimed in claim 1, wherein a solar forecasting tool is linked to the renewable energy module and weather data to predicts solar power output to plan energy use better.

4) The system as claimed in claim 1, wherein a battery health monitoring tool connected to the storage module and batteries to check battery condition to ensure long-term reliability.

5) The system as claimed in claim 1, wherein a backup operation protocol inbuilt into local controllers and the fault system to allow devices to work alone during network or device failures.

6) The system as claimed in claim 1, wherein a grid interaction unit connected to the adaptive system and utility grid to manage power exchange with the grid for stable operation in connected mode.