GPT intelligent interaction system suitable for micro-grid planning

Abstract

The invention relates to the technical field of intelligent power grids, and discloses a GPT intelligent interaction system suitable for micro-grid planning, which comprises a monitoring system, a communication management machine, a micro-grid simulation system and a central controller module, wherein the monitoring system is used for monitoring operation states of a distributed power supply, a load, a switch and the like in the micro-grid simulation system and generating an equipment operation report; and the communication management machine provides an information interaction interface among the monitoring system, the central controller and the micro-grid simulation system. By integrating a GPT intelligent interaction technology, a user can input basic requirements of micro-grid planning through a natural language, and the system can automatically generate a targeted planning scheme and perform optimization. According to the interaction mode based on the natural language, tedious steps in the traditional micro-grid planning process are simplified, the micro-grid design and planning efficiency is greatly improved, the planning period is shortened, and planning personnel can make a micro-grid scheme meeting the requirements more rapidly.

Description

Technical Field

[0001] The present invention relates to the field of smart grid technology, and in particular to a GPT smart interactive system suitable for microgrid planning. Background Art

[0002] With the transformation of the global energy structure, especially the large-scale development of renewable energy, microgrids, as an important energy management system, have gradually become a core component of the power system. Microgrids use distributed power generation, energy storage systems, and flexible load management to operate independently or in parallel with the main grid, improving energy efficiency and system reliability. In particular, when dealing with the volatility and intermittency of renewable energy, microgrids can achieve efficient energy consumption and reduce carbon emissions while ensuring the stability of power supply through intelligent scheduling and optimized control.

[0003] However, the planning, design and optimization process of microgrids is very complex and requires consideration of multiple factors, such as load demand, availability of renewable energy, capacity of energy storage systems, equipment configuration and operation mode, etc. Traditional microgrid planning usually relies on manual analysis and empirical judgment, which is not only time-consuming but also prone to errors. Especially in the face of complex load changes, energy fluctuations and coordinated control of multiple devices, it is often difficult to provide efficient and accurate planning solutions.

[0004] In order to improve the planning and operation efficiency of microgrids, the application of intelligent technology has gradually become the key to solving this problem in recent years. In particular, technologies based on big data, machine learning and artificial intelligence have played an important role in the dispatching, optimization and control of microgrids. For example, by optimizing the load forecasting, equipment status monitoring, energy flow analysis, etc. of microgrids through artificial intelligence algorithms, the response speed and optimization effect of the system can be greatly improved. However, most of the existing microgrid intelligent dispatching systems are limited to certain specific algorithm models and methods, which are difficult to meet the needs of flexible response and intelligent interaction in complex scenarios.

[0005] In addition, with the advancement of information technology, especially the development of natural language processing technology, artificial intelligence models (such as GPT) have been able to provide intelligent interaction methods in many fields. By introducing natural language processing technologies such as GPT into the microgrid planning system, microgrid planners can interact with the system through natural language, further simplifying the planning process and improving the intelligence of the system and user experience.

[0006] Most existing microgrid planning systems rely on fixed algorithms and static models, and cannot achieve flexible adaptation and real-time optimization. Therefore, there is an urgent need for a system that can integrate intelligent interaction, real-time simulation, automatic optimization, and flexible adjustment to improve the planning efficiency, accuracy, and energy efficiency of microgrids, while reducing manual intervention and errors. Summary of the invention

[0007] In view of the shortcomings of the prior art, the present invention provides a GPT intelligent interactive system suitable for microgrid planning, which solves the problems of frequent manual intervention, low efficiency and poor flexibility in the existing microgrid planning.

[0008] To achieve the above objectives, the present invention is implemented through the following technical solutions: A GPT intelligent interactive system suitable for microgrid planning, consisting of a monitoring system, a communication management machine, a microgrid simulation system and a central controller module;

[0009] in:

[0010] The monitoring system is used to monitor the operating status of distributed power sources, loads, switches, etc. in the microgrid simulation system and generate equipment operation reports;

[0011] The communication management machine provides an information interaction interface between the monitoring system, the central controller and the microgrid simulation system, and supports a network port or serial port communication physical interface;

[0012] The microgrid simulation system includes a microgrid simulation model numerical simulation part and a data communication processing part, which are used to perform numerical simulation on each device in the microgrid system, and upload operation data and receive control instructions from the central controller according to the requirements of the microgrid central controller and the monitoring system;

[0013] The central controller realizes coordinated control and stable operation of the microgrid simulation system based on the collected operation data of the microgrid simulation system and according to the embedded control strategy.

[0014] Preferably, the monitoring system includes database, equipment monitoring, event recording and curve reporting functions;

[0015] The equipment monitoring function includes monitoring the operating status of distributed power sources, loads, switches and other equipment in the microgrid simulation system, and generating operating data reports.

[0016] Preferably, the communication management machine supports a network port or a serial port communication physical interface, and uses Modbus TCP protocol or Modbus RTU protocol for data transmission, so as to realize data exchange and communication connection between the monitoring system, the central controller and the microgrid simulation system.

[0017] Preferably, the microgrid simulation system includes a microgrid simulation model numerical simulation part and a data communication processing part;

[0018] The numerical simulation part of the simulation model is built according to the mathematical models of photovoltaic power generation system, energy storage system, charging pile, load, AC / DC converter, switch and distribution network, etc., to realize the numerical simulation of each component of the microgrid;

[0019] The data communication processing part is configured according to the communication point table and uses the modbus_tk module to simulate and realize the simulated operation of the communication slave.

[0020] Preferably, the microgrid simulation system is written based on the Python programming language, and different processes are used to manage the numerical simulation part and the data communication processing part of the microgrid simulation model respectively;

[0021] The numerical simulation part of the simulation model adopts an independent process for calculation and simulation, and the data communication processing part adopts another process for data transmission and processing.

[0022] Preferably, the microgrid simulation model is constructed according to a mathematical model, including the construction of equipment models such as photovoltaic power generation system, energy storage system, charging pile, load, AC / DC converter, switch and distribution network;

[0023] The data communication part uses the modbus_tk module to create a Modbus TCP slave according to the configuration of the communication point table, simulates the communication of photovoltaic power generation systems, energy storage systems, charging piles, loads, AC / DC converters, switches and other equipment, thereby realizing communication simulation between various devices.

[0024] Preferably, the microgrid simulation system operation data is acquired by the central controller communicating with the simulated communication slave in a polling manner to acquire the operation data in real time;

[0025] The control instructions of the microgrid central controller are sent out through a write operation of the central controller to the simulated communication slave.

[0026] Preferably, the control strategy embedded in the central controller includes a grid-connected control strategy and an off-grid control strategy;

[0027] The grid connection control strategy includes tie line power control, local consumption control of new energy and grid connection economic operation control to ensure the smooth connection between the microgrid and the main grid;

[0028] The off-grid control strategy is an off-grid energy balance control strategy, which ensures that the microgrid can maintain a stable power supply after being disconnected from the main grid.

[0029] Preferably, the microgrid simulation system is connected to the central controller via Modbus TCP protocol.

[0030] This communication connection is used to achieve real-time monitoring and data transmission of each component in the microgrid system, ensuring efficient data exchange and control feedback between the simulation system and the central controller.

[0031] The present invention provides a GPT intelligent interactive system suitable for microgrid planning. It has the following beneficial effects:

[0032] 1. The present invention integrates GPT intelligent interaction technology, so that users can input the basic requirements of microgrid planning through natural language, and the system can automatically generate targeted planning solutions and optimize them. This natural language-based interaction method simplifies the cumbersome steps in the traditional microgrid planning process, greatly improves the efficiency of microgrid design and planning, shortens the planning cycle, and enables planners to more quickly develop microgrid solutions that meet the needs.

[0033] 2. The present invention can accurately calculate energy demand and optimal configuration through microgrid simulation and emulation, combined with real-time data and load forecasting. The GPT intelligent interactive system can automatically adjust system parameters and optimize equipment configuration according to user input requirements, and ensure that the energy distribution of the microgrid reaches the maximum efficiency through optimization algorithms. This function effectively improves energy utilization and reduces energy waste.

[0034] 3. The system of the present invention can flexibly adjust the planning scheme of the microgrid according to different user needs and operating conditions. Through the natural language understanding ability of the GPT model, the system can quickly identify and process different input data, adapt to different geographical environments, load demands and energy supply conditions, and realize customized microgrid solutions. This adaptive ability enables the system to play a good role in changing environments and different application scenarios.

[0035] 4. The present invention realizes cross-domain intelligent interaction by integrating the GPT model with the knowledge base in the field of microgrid planning. Users can not only interact with the system based on actual needs, but also obtain comprehensive analysis results based on historical data and expert knowledge through the system. This enables the system to have rich reasoning ability and professional knowledge, and can provide users with more accurate and scientific planning suggestions, enhancing the system's intelligent decision-making ability.

[0036] 5. The traditional microgrid planning of the present invention often relies on manual calculation and empirical judgment, which may lead to human errors and inefficiency. Through the GPT intelligent interactive system, the user's needs are automatically parsed and converted into specific technical requirements, reducing the errors and deviations of manual input and ensuring the scientificity and accuracy of the planning process. At the same time, the system can automatically generate planning reports, reducing the workload of manual processing reports.

[0037] 6. The present invention can not only generate preliminary microgrid planning schemes, but also perform simulation verification in real time to test the performance of the system under different working conditions. Based on simulation analysis, the system can automatically optimize the microgrid scheme, adjust the configuration of each device and energy scheduling to adapt to different load demands and renewable energy fluctuations. This simulation and optimization capability ensures the feasibility and efficiency of the microgrid planning scheme and improves the reliability and adaptability of the system.

[0038] 7. The present invention provides technical support for the intelligent development of microgrids by combining GPT intelligent interaction technology with the planning, scheduling and optimization of microgrids. The automated simulation and optimization functions of the system can continuously adjust and improve strategies during the construction and operation of microgrids, further improve the intelligence level of microgrids, promote the application of renewable energy in microgrids, and promote the popularization and utilization of green energy.

[0039] 8. The present invention adopts modular design and intelligent interaction, so users can flexibly adjust the planning scope and functions of microgrids according to their needs. For example, users can choose different equipment combinations (such as photovoltaic, wind energy, energy storage, etc.) according to specific load requirements and environmental conditions, and quickly integrate new equipment or technologies into the system. This scalability enables the system to adapt to the needs of microgrids of different scales and types, and has broad application prospects. BRIEF DESCRIPTION OF THE DRAWINGS

[0040] Figure 1 is a system flow chart of the present invention;

[0041] Figure 2 is a framework diagram of the present invention;

[0042] Figure 3 This is a microgrid framework diagram of the present invention. DETAILED DESCRIPTION

[0043] The following will be combined with the drawings in the specification of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0044] Please see attached Figure 1 -Attached Figure 3 , an embodiment of the present invention provides a GPT intelligent interaction system suitable for microgrid planning, including:

[0045] 1. Detection system:

[0046] Data collection function

[0047] The monitoring system collects the working status data of the equipment in real time by installing sensors on each device in the microgrid simulation system (such as photovoltaic power generation, energy storage system, load, switch, etc.). Specifically, the data collected by the monitoring system includes but is not limited to the voltage, current, power, frequency, load and other parameters of the equipment. The equipment status information is transmitted to the communication management machine through the acquisition module for further processing and transmission.

[0048] In this embodiment, the sensor uses a high-precision digital sensor, which can collect power data of microgrid equipment in real time and transmit it to the monitoring system through a digital interface (such as Modbus RTU, Modbus TCP, etc.). The collected data includes the instantaneous power, load status, charging / discharging status, etc. of the equipment, ensuring the integrity and real-time nature of the data.

[0049] Equipment status monitoring and analysis

[0050] The monitoring system continuously monitors the equipment in the microgrid and captures the operation changes of the equipment in a timely manner. When the working status of the equipment changes or becomes abnormal, the system can identify and record the relevant data in real time. By monitoring the status of the equipment, the system can detect the operating status of the equipment (such as normal, fault, alarm, etc.).

[0051] In this system, the equipment status monitoring and analysis module processes and analyzes the collected data in real time through built-in algorithms. Based on the comparison between the preset operating parameters of the equipment (such as rated power, rated voltage, etc.) and the actual operating data, the system can determine whether the equipment is in normal working condition and issue an alarm for abnormal equipment. For example, if the load exceeds the predetermined range or the equipment temperature is too high, the system will trigger the alarm mechanism and transmit the relevant information to the central controller through the communication management machine for further processing.

[0052] Fault detection and alarm function

[0053] The monitoring system has a fault detection function, which can generate alarm information and record events when equipment fails or abnormalities occur. These alarm information will be transmitted to the central controller to remind operators to deal with the fault in time to ensure the safe and stable operation of the microgrid.

[0054] By monitoring the status of each device in real time, the monitoring system can determine the type of fault, such as overcurrent, overvoltage, undervoltage, short circuit, etc. The system can also perform intelligent fault detection by setting thresholds (such as overvoltage protection value, current protection value, etc.). For faulty equipment, the system will trigger the alarm mechanism, generate an alarm signal and record related event logs. The alarm information and logs will be sent to the central controller through the communication management machine to ensure that relevant personnel can obtain fault information in a timely manner and take necessary measures.

[0055] Data storage and curve report function

[0056] The monitoring system not only provides real-time monitoring, but also has data storage and curve generation functions. The monitoring system saves the data of equipment operation in the database and can generate real-time monitoring curves and reports according to needs, so that users can view the long-term operation of the equipment, conduct data analysis and optimize decision-making.

[0057] The storage module of the monitoring system stores the collected data in a database in time series, supporting the query and retrospective analysis of historical data. The system can generate operation curves (such as current, voltage, and power change curves) and reports (such as equipment operation status reports, fault statistics reports, etc.) as needed. These curves and reports provide important reference data for microgrid optimization and are helpful for subsequent analysis and adjustment.

[0058] Interface function with communication management machine

[0059] The monitoring system transmits monitoring data to the central controller through the communication management machine. The communication management machine relays the data to the microgrid simulation system through the Modbus protocol to ensure data flow and command transmission between systems. The data transmission process is real-time, efficient and reliable.

[0060] In this embodiment, the communication management machine and the monitoring system exchange data through the Modbus TCP protocol or the Modbus RTU protocol. The monitoring system sends the collected device status data to the communication management machine, and the communication management machine passes the data to the central controller or the microgrid simulation system. During the data transmission process, the communication management machine will also perform necessary protocol conversion on the data to ensure that each module can communicate smoothly.

[0061] Data analysis and feedback mechanism

[0062] The monitoring system has data analysis functions, which can analyze the equipment operation data in real time and provide optimization suggestions to the central controller based on the analysis results. The analysis functions mainly include load forecasting, equipment health assessment, energy consumption forecasting, etc.

[0063] The monitoring system has a built-in data analysis module that uses data mining algorithms to analyze historical and real-time data. By recognizing patterns in equipment operation data, the system can predict load demand and assess the health status of equipment (such as remaining life, failure probability, etc.). These analysis results will be fed back to the central controller to assist the central controller in optimizing the scheduling of the microgrid.

[0064] The monitoring system in this embodiment realizes efficient monitoring and data management of the microgrid system through real-time data collection, equipment status monitoring and analysis, fault detection and alarm, data storage and report generation, and interface functions with the communication management machine. The design of this system ensures that the real-time status of the microgrid equipment can be detected and recorded in a timely manner, providing strong data support for the stable operation and optimized scheduling of the microgrid. In the system, the accuracy of data collection, timely detection and alarm of faults, and status analysis through real-time reports and curves are all key technical features to ensure the efficient operation of the microgrid.

[0065] 2. Communication Management Machine

[0066] In the closed-loop test simulation platform of the microgrid central controller, the communication manager is responsible for data transmission and interaction between different modules within the system, ensuring the smooth flow of information and effective transmission of instructions between the monitoring system, the microgrid simulation system and the central controller. As the core data exchange hub, the communication manager uses standard communication protocols (such as ModbusTCP, Modbus RTU) for connection and data transmission between modules. Its role is to coordinate and manage the information exchange of various components of the microgrid, ensuring the real-time, reliability and compatibility of data, thereby achieving efficient operation and optimized scheduling of the microgrid system.

[0067] Data interface and communication protocol support

[0068] The communication management machine realizes data exchange between modules through Modbus TCP protocol or Modbus RTU protocol. It supports the communication physical interface of network port and serial port, and selects the appropriate communication protocol and interface for data transmission according to the actual needs of the microgrid system.

[0069] The communication management machine in this embodiment supports Modbus TCP and Modbus RTU protocols, and can communicate bidirectionally with the monitoring system, central controller and microgrid simulation system. For network communication, the communication management machine uses the network port interface (Ethernet) to transmit data through the Modbus TCP protocol; for serial communication, the communication management machine uses the Modbus RTU protocol to exchange data through the serial port (RS-232 / RS-485) interface. In this way, the communication management machine can adapt to the communication needs between different devices and modules and achieve wide compatibility of the system.

[0070] Data exchange and real-time guarantee

[0071] The communication management machine is mainly responsible for data transmission and relay functions. The monitoring system transmits the collected equipment data to the central controller in real time through the communication management machine, and the central controller also sends control instructions to the microgrid simulation system through the communication management machine. To ensure the real-time data transmission, the communication management machine adopts priority queue and cache mechanism to effectively avoid delays and losses in data transmission.

[0072] The communication management machine transmits the data (such as current, voltage, power, etc.) from the monitoring system to the central controller in order. During the data transmission process, the priority queue is used to control the processing order of different data packets to ensure that important control data and emergency alarm data can be transmitted first. In addition, the communication management machine has a built-in cache mechanism to handle the situation of excessive instantaneous data volume and ensure the integrity and real-time nature of the information.

[0073] Protocol conversion function

[0074] In a microgrid system, different devices or modules may use different communication protocols. The communication manager is responsible for converting data of different protocols to ensure that the data between the various parts of the system can be correctly parsed and processed. In particular, during data transmission, the communication manager can convert protocols between Modbus TCP and Modbus RTU to ensure the compatibility of the entire system.

[0075] Through the built-in protocol conversion function, the communication manager can convert data between Modbus TCP protocol and Modbus RTU protocol, so that devices using different protocols can work together seamlessly. For example, the monitoring system uses ModbusTCP protocol to exchange data with the communication manager, while the microgrid simulation system may only support Modbus RTU protocol. The communication manager converts the data format from TCP to RTU through its protocol conversion function to ensure the correct transmission and parsing of data.

[0076] Error detection and recovery mechanism

[0077] The communication manager has built-in error detection and recovery functions to ensure the reliability of data transmission. When data loss, errors or timeouts occur during transmission, the communication manager can automatically detect and recover to ensure the stability of system communication.

[0078] In this embodiment, the communication manager ensures the reliability of data transmission through CRC check and timeout retransmission mechanism. During the data transmission process, the communication manager will perform CRC check on each data packet to detect whether an error occurs during the transmission process. If an error is detected, the system will automatically request retransmission of the data. In addition, when the communication manager detects that the device is unresponsive or times out during the transmission process, it will actively re-establish the connection or retry the transmission until the data transmission is successful.

[0079] Data forwarding and scheduling functions

[0080] The communication management machine is not only responsible for simple data transmission, it also has data forwarding and scheduling functions. After receiving the control command from the central controller, the communication management machine needs to forward the command to the microgrid simulation system, and the various devices in the scheduling system perform corresponding operations.

[0081] The communication management machine forwards the control instructions (such as adjusting the charging status of the energy storage system, adjusting the photovoltaic power generation output, etc.) issued by the central controller to the microgrid simulation system through Modbus TCP or RTU protocol. After receiving the instructions, the microgrid simulation system adjusts the device status according to the instructions, and the communication management machine also feeds back the device status information to the central controller to ensure that the system control commands are synchronized with the actual device status.

[0082] Interface expansion and module compatibility

[0083] The communication management machine is also designed with multiple interfaces to support the access and expansion of different devices. For different manufacturers and types of devices in the microgrid system, the communication management machine can ensure seamless integration of the entire system through flexible interface configuration and protocol adaptation.

[0084] The communication management machine is connected to each device through a standardized communication interface (such as Ethernet, RS-232 / RS-485). The system can configure different interface types according to needs, making the communication management machine compatible with different types of devices and sensors. This flexibility makes the microgrid system more convenient during expansion, and more devices or sensors can be added according to actual needs.

[0085] The communication manager in this embodiment ensures efficient and reliable data exchange between the modules of the microgrid system through the support of Modbus TCP protocol and Modbus RTU protocol. Through functions such as protocol conversion, error detection and recovery, and data scheduling, the communication manager ensures the normal operation of the microgrid system, and can adapt according to different protocols and interfaces of the equipment to ensure the compatibility and stability of the system. This module not only provides real-time data forwarding and scheduling functions, but also improves the communication reliability of the system through the built-in error recovery mechanism, providing basic support for the efficient scheduling and optimization of the microgrid.

[0086] 3. Microgrid Simulation System

[0087] In this implementation scheme, the microgrid simulation system is one of the core components of the platform, which is mainly used to simulate the operation of each device in the microgrid system. It simulates the power output, energy consumption and power flow of the equipment, and provides real-time feedback data to the central controller, thereby supporting the optimization decision and strategy adjustment of the central controller. Through simulation, the microgrid simulation system can not only evaluate the operating status of the microgrid under different load and energy supply conditions, but also perform strategy optimization, load scheduling and energy consumption path planning. The efficient operation of the microgrid simulation system is crucial to the stability, energy efficiency and sustainability of the entire microgrid system.

[0088] In this embodiment, the microgrid simulation system is implemented as follows:

[0089] Equipment simulation and modeling capabilities

[0090] The microgrid simulation system uses mathematical modeling to perform numerical simulation on the equipment in the microgrid (such as photovoltaic power generation, energy storage system, charging pile, load, AC / DC converter, etc.), simulating the working state and energy flow of each device under different working conditions. Specifically, the system uses physical models and power flow algorithms to simulate the power output of the equipment, load demand, and the charging and discharging process of the energy storage device.

[0091] The microgrid simulation system is written in Python programming language and uses a modular structure to implement simulation models of different devices. Each device (such as photovoltaic power generation system, energy storage unit) has a corresponding mathematical model, which is simulated through physical laws (such as electric power calculation, energy balance model). During the simulation process, the microgrid simulation system also needs to dynamically adjust the model parameters according to changes in the external environment (such as weather conditions, changes in load demand, etc.) to ensure the accuracy of the simulation results.

[0092] Power flow calculation and load forecasting

[0093] The microgrid simulation system analyzes the power flow in the microgrid through the power flow calculation algorithm and evaluates the energy distribution between different devices. Under different load and power generation conditions, the system can predict the load demand of the microgrid and possible energy imbalance problems, and provide the central controller with an optimized load scheduling solution.

[0094] In this embodiment, the power flow calculation is implemented by a power flow algorithm based on the Newton-Raphson method, which is used to analyze the voltage, power and energy flow of each device in the power grid. When performing power flow calculation, the microgrid simulation system also combines a load forecasting model to predict load demand based on historical data and real-time inputs (such as climate data, load curves, etc.) and evaluate the system response under different load conditions.

[0095] Data communication processing and instruction execution

[0096] The microgrid simulation system realizes two-way data exchange with the communication management machine through the Modbus protocol. The monitoring system and the central controller communicate with the microgrid simulation system through this protocol. The system receives control instructions from the central controller and feeds back the simulation results to the monitoring system and the central controller.

[0097] The microgrid simulation system has a built-in modbus_tk module to process data communication with the communication management machine. After receiving control instructions from the central controller (such as adjusting photovoltaic power generation and adjusting the energy storage system charging and discharging strategy), the microgrid simulation system will adjust the parameters of the simulation model according to the instructions and provide real-time feedback on the equipment operation status. At the same time, the system can also transmit the simulation results to the communication management machine in the form of data packets to ensure timely upload of data.

[0098] Simulation optimization and control strategy adjustment

[0099] The microgrid simulation system supports the central controller to optimize and adjust the microgrid control strategy by analyzing the data during the simulation process. Specifically, the microgrid simulation system provides simulation verification of multiple control strategies based on operating data (such as energy consumption, load fluctuations, etc.), helping the central controller to optimize the strategy, reduce energy loss, and improve system stability.

[0100] During the simulation process, the microgrid simulation system provides simulation results of multiple control strategies according to different scenarios and load fluctuations, including grid-connected control strategy, off-grid control strategy and energy storage optimization scheduling strategy. The system conducts multiple rounds of simulations through optimization algorithms (such as genetic algorithms, particle swarm algorithms, etc.) to evaluate the operation effects of microgrids under different control strategies, thereby providing the central controller with an optimization solution based on the simulation results.

[0101] Modular design and scalability

[0102] The microgrid simulation system adopts a modular design to support the flexible addition of new devices or new control strategies. Through the standardization of interfaces and protocols, the system can easily access devices from different manufacturers, simulate the devices and incorporate them into the overall microgrid simulation model.

[0103] The microgrid simulation system separates the simulation modules of different devices and uses a plug-in architecture to add new device simulation modules. For example, the system can add new photovoltaic or energy storage device models through a simple configuration file and use the corresponding power flow calculation model for simulation. This modular design not only improves the flexibility and scalability of the system, but also facilitates the rapid adaptation of future technological advances.

[0104] The microgrid simulation system in this embodiment accurately simulates various types of equipment and power flow in the microgrid through functions such as device simulation, power flow calculation, load forecasting and optimized scheduling. Real-time data exchange and instruction execution achieved through the Modbus protocol ensure that the system can work effectively with the monitoring system and the central controller. During the simulation process, the system not only provides optimization suggestions for the central controller, but also optimizes the control strategy of the microgrid through multiple simulations, ensuring the efficient operation of the microgrid under different working conditions. The modular design of the system makes it highly scalable and flexible, and can be flexibly configured and adjusted according to different application requirements.

[0105] 4. Central Controller

[0106] In this implementation, the central controller is one of the core modules of the microgrid system, responsible for executing control strategies and coordinating various devices in the microgrid based on feedback data from the monitoring system and the microgrid simulation system. The main function of the central controller is to dispatch and optimize the working status of various energy production and storage devices in the microgrid, ensure the stable operation of the microgrid, maximize energy efficiency, and connect or disconnect with the main grid when necessary.

[0107] In this embodiment, the central controller is implemented as follows:

[0108] Data collection and processing The central controller collects data from the microgrid simulation system through the communication management machine, processes it in real time, and evaluates the operating status of the microgrid. The data includes but is not limited to the power, voltage, frequency and other information of each device.

[0109] The central controller in this embodiment receives data from the communication management machine through the Modbus protocol and processes the received data. For example, the central controller will analyze the power of the energy storage system, the power output of photovoltaic power generation, and the load changes in real time to evaluate the current operation status of the microgrid.

[0110] The central controller is embedded with multiple control strategies, such as grid-connected control strategy and off-grid control strategy. When the microgrid is connected to the grid, the central controller is responsible for coordinating the power exchange between the microgrid and the main grid; when the microgrid is off-grid, the central controller is responsible for energy balance and resource scheduling.

[0111] The central controller executes specific control strategies based on input data. For example, when the system is in a grid-connected state, the central controller adjusts the output of the photovoltaic power generation and energy storage system in the microgrid according to the load demand and the load of the main grid to ensure the power balance between the microgrid and the main grid. When the microgrid is disconnected from the main grid, the central controller executes an off-grid control strategy to maintain the energy balance of the microgrid by adjusting the energy storage system and the load.

[0112] Control instructions are issued according to the dispatching strategy calculated by the central controller. The system sends control instructions to the microgrid simulation system to adjust the working status of equipment (such as photovoltaic power generation, energy storage unit, load, etc.).

[0113] The central controller transmits control instructions to the microgrid simulation system through the Modbus protocol. For example, the control instructions may include adjusting the power output of the photovoltaic system, changing the charging and discharging state of the energy storage system, or changing the load distribution to ensure the optimal operation of the microgrid under different working conditions.

[0114] Closed-loop control and optimization The central controller monitors the system operation status in real time through closed-loop control with the microgrid simulation system, adjusts the control strategy based on feedback, and optimizes energy scheduling.

[0115] In this embodiment, the central controller adjusts the strategy through closed-loop control. For example, when the microgrid simulation system feedbacks system load fluctuations or equipment abnormalities, the central controller will adjust the energy flow direction according to the feedback, optimize the control strategy, and ensure stable operation of the system.

[0116] Fault Detection and Emergency Response The central controller is not only responsible for routine dispatching tasks, but also has fault detection and emergency response functions. When the microgrid simulation system or monitoring system reports equipment failure or abnormality, the central controller can take emergency measures in time.

[0117] When the monitoring system or microgrid simulation system reports a fault or anomaly, the central controller will immediately enable emergency control strategies, such as disconnecting faulty equipment, adjusting loads, or switching backup power sources to ensure the safety of the microgrid system.

[0118] Working principle: First, the monitoring system collects the operating data of each device in the microgrid in real time through sensors, such as voltage, current, power and frequency, and transmits these data to the communication management machine. The communication management machine is responsible for forwarding these data to the central controller through the Modbus protocol, receiving control instructions from the central controller at the same time, and passing them to the microgrid simulation system for execution. According to the instructions issued by the central controller, the microgrid simulation system combines the real-time collected data to perform power flow calculation and equipment simulation, optimize energy scheduling and equipment status, and ensure the stable operation of the microgrid. Through this process, the control strategy embedded in the central controller will be adjusted according to the actual operating status of the microgrid system to achieve load balancing, maximum energy utilization and emergency handling of faults. The system adopts a closed-loop control mechanism. The microgrid simulation system transmits the real-time feedback device data to the central controller, and the central controller adjusts the control strategy according to these feedbacks to ensure the stability and efficient operation of the system. In addition, when the monitoring system or simulation system detects a fault, the central controller will execute an emergency response to ensure the safe and stable operation of the microgrid. The entire system realizes the intelligent optimization and dynamic adjustment of the microgrid through real-time data exchange and feedback adjustment, ensuring its optimal operation under different working conditions.

[0119] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A GPT intelligent interactive system suitable for microgrid planning, characterized in that: It consists of a monitoring system, a communication management machine, a microgrid simulation system and a central controller module; in: The monitoring system is used to monitor the operating status of distributed power sources, loads, switches, etc. in the microgrid simulation system and generate equipment operation reports; The communication management machine provides an information interaction interface between the monitoring system, the central controller and the microgrid simulation system, and supports a network port or serial port communication physical interface; The microgrid simulation system includes a microgrid simulation model numerical simulation part and a data communication processing part, which are used to perform numerical simulation on each device in the microgrid system, and upload operation data and receive control instructions from the central controller according to the requirements of the microgrid central controller and the monitoring system; The central controller realizes coordinated control and stable operation of the microgrid simulation system based on the collected operation data of the microgrid simulation system and according to the embedded control strategy.

2. A GPT intelligent interactive system suitable for microgrid planning according to claim 1, characterized in that: The monitoring system includes database, equipment monitoring, event recording and curve reporting functions; The equipment monitoring function includes monitoring the operating status of distributed power sources, loads, switches and other equipment in the microgrid simulation system, and generating operating data reports.

3. According to claim 1, a GPT intelligent interactive system suitable for microgrid planning is characterized in that: The communication management machine supports a communication physical interface of a network port or a serial port, and adopts Modbus TCP protocol or Modbus RTU protocol for data transmission, and is used to realize data exchange and communication connection between the monitoring system, the central controller and the microgrid simulation system.

4. A GPT intelligent interactive system suitable for microgrid planning according to claim 1, characterized in that: The microgrid simulation system includes a microgrid simulation model numerical simulation part and a data communication processing part; The numerical simulation part of the simulation model is built according to the mathematical models of photovoltaic power generation system, energy storage system, charging pile, load, AC / DC converter, switch and distribution network, etc., to realize the numerical simulation of each component of the microgrid; The data communication processing part is configured according to the communication point table and uses the modbus_tk module to simulate and realize the simulated operation of the communication slave.

5. A GPT intelligent interactive system suitable for microgrid planning according to claim 1, characterized in that: The microgrid simulation system is written based on Python programming language, and uses different processes to manage the numerical simulation part and the data communication processing part of the microgrid simulation model respectively; The numerical simulation part of the simulation model adopts an independent process for calculation and simulation, and the data communication processing part adopts another process for data transmission and processing.

6. A GPT intelligent interactive system suitable for microgrid planning according to claim 1, characterized in that: The microgrid simulation model is built according to a mathematical model, including the construction of equipment models such as photovoltaic power generation system, energy storage system, charging pile, load, AC / DC converter, switch and distribution network; The data communication part uses the modbus_tk module to create a Modbus TCP slave according to the configuration of the communication point table, simulates the communication of photovoltaic power generation systems, energy storage systems, charging piles, loads, AC / DC converters, switches and other equipment, thereby realizing communication simulation between various devices.

7. A GPT intelligent interactive system suitable for microgrid planning according to claim 1, characterized in that: The acquisition of the operation data of the microgrid simulation system is performed by the central controller communicating with the simulated communication slave in a polling manner to obtain the operation data in real time; The control instructions of the microgrid central controller are sent out through a write operation of the central controller to the simulated communication slave.

8. A GPT intelligent interactive system suitable for microgrid planning according to claim 1, characterized in that: The control strategy embedded in the central controller includes a grid-connected control strategy and an off-grid control strategy; The grid connection control strategy includes tie line power control, local consumption control of new energy and grid connection economic operation control to ensure the smooth connection between the microgrid and the main grid; The off-grid control strategy is an off-grid energy balance control strategy, which ensures that the microgrid can maintain a stable power supply after being disconnected from the main grid.

9. A GPT intelligent interactive system suitable for microgrid planning according to claim 1, characterized in that: The microgrid simulation system is connected to the central controller through the Modbus TCP protocol; This communication connection is used to achieve real-time monitoring and data transmission of each component in the microgrid system, ensuring efficient data exchange and control feedback between the simulation system and the central controller.

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