Regional power grid multi-point layout new energy synchronous machine reactor system planning configuration method

Abstract

The invention relates to the technical field of photovoltaic power generation system operation and maintenance, provides a regional power grid multi-point layout new energy synchronous machine reactor system planning and configuration method, and aims to solve the problems of weak voltage supporting capability and transient overvoltage in a high-proportion new energy power system. The method comprises the steps of obtaining power grid basic data, new energy resource data, power system operation data and synchronous machine parameters, training a neural network model by using the obtained data to obtain a planning configuration model, collecting new energy synchronous machine pile system operation data in real time, substituting the new energy synchronous machine pile system operation data into the model to obtain preliminary planning configuration, and verifying the planning configuration through simulation. The historical data and the simulation characteristic data are optimized through a genetic algorithm until a planning configuration scheme meeting the transient overvoltage configuration requirement is found, the stability of a power grid is improved, new energy utilization is optimized, and intelligent planning configuration is achieved.

Description

Technical Field

[0001] The present invention relates to the field of photovoltaic power generation system operation and maintenance technology, and in particular to a planning and configuration method for a new energy synchronous machine pile system with a multi-point layout in a regional power grid. Background Art

[0002] The multi-point layout of the new energy synchronous machine system in the regional power grid aims to improve the stability of the regional power grid. By deploying new energy synchronous machines (MGP) at multiple nodes in the regional power grid, it can effectively regulate the power grid flow and minimize network losses. As the interface between new energy and the power grid, MGP can achieve electrical isolation between the new energy field and the power grid, prevent adverse disturbances on one side from propagating to the other side, and provide sufficient inertia support and reactive power support, providing a strong guarantee for the stable operation of the power grid. The multi-point layout method can maximize the advantages of MGP and meet the requirements of optimal site selection and capacity configuration of regional power grid energy storage systems.

[0003] The planning and configuration steps of the multi-point layout of the new energy synchronous machine system in the regional power grid are to conduct system analysis and evaluation according to the load characteristics of the regional power grid, the distribution of new energy resources and the existing power grid structure, determine the potential deployment points of the new energy synchronous machine (MGP), and use advanced power system simulation technology to simulate the grid operation status under different deployment schemes, evaluate the improvement effect of each scheme on the grid stability, and optimize the selection of the best MGP layout point and its capacity configuration based on the simulation results, so as to effectively absorb new energy and minimize the impact on the power grid. Finally, formulate an implementation plan and program, which includes equipment selection, installation and commissioning, grid-connected testing and subsequent operation and maintenance strategies, so that the entire system can be smoothly integrated into and improve the overall performance of the regional power grid.

[0004] In the process of planning and configuring a new energy synchronous machine reactor system with multiple points in a regional power grid, there are the following technical pain points: the voltage support capacity of some high-proportion new energy power systems at the sending end is weak, and the transient overvoltage problem is serious. The transient overvoltage will cause voltage fluctuations and flicker problems in the power grid. For this reason, the present invention provides a planning and configuration method for a new energy synchronous machine reactor system with multiple points in a regional power grid. Summary of the invention

[0005] In view of the shortcomings of the existing technology, the present invention provides a planning and configuration method and an extraction method for a regional power grid multi-point layout of new energy synchronous machine pile system to solve the problem of weak voltage support capacity and serious transient overvoltage in some sending-end high-proportion new energy power systems. Transient overvoltage will cause voltage fluctuations and flicker problems in the power grid.

[0006] In order to solve the above technical problems, the specific technical solutions of the present invention are as follows:

[0007] The present invention provides a method for planning and configuring a new energy synchronous machine and reactor system for a regional power grid with multiple points, comprising:

[0008] Step S101, obtaining regional power grid basic data, new energy resource data, power system operation data and new energy synchronous machine parameters;

[0009] Step S102, based on the regional power grid basic data, the regional power grid basic data, the new energy resource data, the power system operation data and the new energy synchronous machine parameters are used to train the neural network model to obtain a regional power grid multi-point layout new energy synchronous machine system planning configuration model;

[0010] Step S103, collecting real-time new energy synchronous machine stack system operation data and substituting it into the regional power grid multi-point layout new energy synchronous machine stack system planning configuration model to obtain the first new energy synchronous machine stack system planning configuration;

[0011] Step S104, substituting the planned configuration of the new energy synchronous machine stack system into the preset new energy synchronous machine stack system simulation model to obtain power grid operation simulation data, extracting data features of the power grid operation simulation data to obtain power grid operation simulation feature data, matching the power grid operation simulation feature data in a preset transient overvoltage scheme configuration knowledge base to obtain a transient overvoltage scheme configuration matching result, the transient overvoltage matching scheme result includes a transient overvoltage matching scheme configuration success and a transient overvoltage matching scheme failure;

[0012] Step S105, if the transient overvoltage matching scheme is unsuccessful, the historical data of the regional power grid multi-point layout of new energy synchronous machine stack system is used, and the historical data of the regional power grid multi-point layout of new energy synchronous machine stack system and the power grid operation simulation feature data are used to optimize the regional power grid multi-point layout of new energy synchronous machine stack system planning and configuration model using a genetic algorithm, and the optimized regional power grid multi-point layout of new energy synchronous machine stack system planning and configuration model is used to process the real-time new energy synchronous machine stack system operation data, and the second new energy synchronous machine stack system planning configuration is output, and the second new energy synchronous machine stack system planning configuration is used as the regional power grid multi-point layout of new energy synchronous machine stack system planning configuration.

[0013] Furthermore, the method for planning and configuring a regional power grid multi-point layout new energy synchronous machine and reactor system, step S101, comprises:

[0014] The basic data of regional power grid includes the topological structure of regional power grid, transmission line parameters, substation location, substation capacity, and substation load distribution information;

[0015] New energy resource data include regional wind energy and regional solar energy;

[0016] Acquiring power system operation data including real-time load data of the power grid, real-time power supply and demand curve of the power grid, real-time power grid frequency of the power grid and real-time voltage stability index of the power grid;

[0017] The parameters of new energy synchronous machines are obtained, including the technical parameters of new energy wind turbines, the technical parameters of the inverter and synchronous machine in the new energy solar power generation system, the rated power, rated voltage, moment of inertia, control strategy parameters and protection settings of the new energy synchronous machine.

[0018] Furthermore, the method for planning and configuring a regional power grid multi-point layout new energy synchronous machine and reactor system, step S102, comprises:

[0019] Based on the basic data of regional power grid, the basic data of regional power grid, new energy resource data, power system operation data and new energy synchronous machine parameters are preprocessed and data features are extracted. The preprocessed data and the extracted data features are used to train the neural network model. The model parameters are adjusted by the gradient descent method to minimize the model prediction error. The planning and configuration model of the regional power grid multi-point layout new energy synchronous machine system is obtained.

[0020] Furthermore, the method for planning and configuring a regional power grid multi-point layout new energy synchronous machine system, step S103, comprises:

[0021] Through the sensors, monitoring equipment or remote communication interfaces installed on the new energy synchronous machine stack system, the real-time operation data of the new energy synchronous machine stack system is collected, the collected real-time operation data is preprocessed, and the preprocessed data is loaded into the planning and configuration model of the regional power grid multi-point layout new energy synchronous machine stack system. The planning and configuration model of the regional power grid multi-point layout new energy synchronous machine stack system is used to calculate the input real-time operation data to obtain the planning and configuration scheme of the new energy synchronous machine stack system. The planning and configuration scheme of the new energy synchronous machine stack system includes the deployment points, capacity configuration and control strategy of the synchronous machine;

[0022] The planning configuration of the new energy synchronous machine stack system is decoded and converted into planning configuration information, which includes the geographical location of the deployment point, the capacity and model of the synchronous machine, and the setting of the control parameters, and is output in the form of a report.

[0023] Furthermore, the method for planning and configuring a regional power grid multi-point layout new energy synchronous machine and reactor system, step S104, comprises:

[0024] Determine the simulation target and scope, select the simulation tool, and build the synchronous machine model in the simulation tool according to the simulation target and scope, the simulation tool, and the actual configuration and parameters of the new energy synchronous machine stack system;

[0025] Set the initial conditions and boundary conditions of the model, and configure different simulation scenarios according to the operating characteristics of the new energy synchronous reactor system and the actual situation of the power grid. Different simulation scenarios include normal operation scenarios, fault scenarios, and extreme weather scenarios;

[0026] Run the simulation model, collect grid operation simulation data, start the simulation tool, run the simulation model according to the set parameters and scenarios, monitor the operating status of the model during the simulation, and collect the grid operation data generated during the simulation. The grid operation data includes voltage, current, power and frequency.

[0027] Furthermore, the method for planning and configuring a new energy synchronous machine system for a regional power grid with multiple points layout, step S105, comprises:

[0028] The power grid operation simulation characteristic data is compared with the historical data of the regional power grid multi-point layout new energy synchronous machine reactor system to verify the accuracy of the new energy synchronous machine reactor system simulation model. If there is a large deviation between the power grid operation simulation characteristic data and the historical data of the regional power grid multi-point layout new energy synchronous machine reactor system, the historical data of the regional power grid multi-point layout new energy synchronous machine reactor system is optimized.

[0029] Furthermore, the method for planning and configuring a new energy synchronous machine system for a regional power grid with multiple points layout, step S105, comprises:

[0030] Integrate the historical data of the regional power grid multi-point layout new energy synchronous machine system and the power grid operation simulation feature data, and organize the historical data of the regional power grid multi-point layout new energy synchronous machine system, including the operation records, fault records and maintenance records of the new energy synchronous machine system, and extract the power grid operation simulation feature data, including voltage fluctuations, current changes and power factor indicators;

[0031] receiving optimization objectives, wherein the optimization objectives include minimizing voltage fluctuations, maximizing utilization of new energy, and reducing system losses;

[0032] Receive the framework parameters of the genetic algorithm, determine the population size of the genetic algorithm according to the framework parameters of the genetic algorithm, that is, the number of solutions participating in the optimization at the same time, design the selection, crossover, and mutation genetic operators, and define the fitness function to evaluate the quality of each solution, where the solution is the planning configuration plan;

[0033] Generate an initial solution set, i.e., a population of the genetic algorithm, and randomly generate a set of initial solutions according to the parameter range and constraint conditions of the planning and configuration model of the new energy synchronous reactor system with multi-point layout of the regional power grid, each solution represents a planning and configuration scheme of the new energy synchronous reactor system;

[0034] Calculate the fitness value of each solution in the population, substitute each solution into the planning and configuration model of the regional power grid multi-point layout new energy synchronous machine reactor system, and calculate the fitness value corresponding to each solution by combining the historical data of the regional power grid multi-point layout new energy synchronous machine reactor system and the power grid operation simulation feature data;

[0035] A new set of solutions is generated through selection, crossover, and mutation until the preset number of iterations is reached or the optimization goal is met. After the optimization is completed, the solution with the highest fitness value is selected from the population as the optimal solution, that is, the optimized planning and configuration plan for the new energy synchronous reactor system.

[0036] Beneficial effects of the present invention;

[0037] The present invention arranges the new energy synchronous machine system at multiple points. The present invention can effectively regulate the power grid current, reduce network losses, and improve the voltage support capacity of the power grid, especially in solving the transient overvoltage problem in some sending-end high-proportion new energy power systems. This helps to reduce voltage fluctuations and flicker in the power grid and improve the overall stability of the power grid. Through the intelligent planning and configuration method, the present invention can reasonably allocate the deployment points, capacity configuration and control strategies of the new energy synchronous machine, thereby realizing the maximum utilization of new energy, helping to improve the efficiency and economy of new energy power generation, and promoting the development of green energy.

[0038] The present invention adopts advanced technologies such as neural network models and genetic algorithms to realize the intelligent and automated planning and configuration of the new energy synchronous machine system, which not only improves the efficiency and accuracy of planning and configuration, but also reduces the cost and risk of human intervention. By collecting and analyzing a large amount of basic data on the power grid, new energy resource data, power system operation data, and new energy synchronous machine parameters, the present invention provides solid data support for planning and configuration. This makes the decision-making process more scientific and objective, and helps to improve the feasibility and practicality of the planning and configuration scheme.

[0039] The present invention performs simulation verification through a preset new energy synchronous machine system simulation model, which can more accurately evaluate the effect of the planning configuration scheme. At the same time, matching is performed in combination with the transient overvoltage scheme configuration knowledge base, which further improves the accuracy of simulation verification. The planning configuration method of the present invention has high flexibility and scalability. With the changes in the grid structure, the distribution of new energy resources and the operating conditions of the power system, the method of the present invention can quickly adapt and make corresponding optimization adjustments.

[0040] To sum up, the present invention effectively improves the stability of the regional power grid, optimizes the utilization of new energy, realizes the intelligence and data-driven decision-making process, improves the accuracy of simulation verification through an intelligent planning and configuration method, and has good flexibility and scalability. It provides a comprehensive and effective solution for the planning and configuration of multi-point layout of new energy synchronous machine stack systems in regional power grids. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] In order to more clearly illustrate the technical solution of the present invention, the following is a brief introduction to the drawings required for use in the embodiments. Obviously, for ordinary technicians in this field, other drawings can be obtained based on the drawings without paying any creative labor.

[0042] Figure 1 A schematic flow chart of a method for planning and configuring a new energy synchronous machine stack system for a regional power grid with a multi-point layout provided in an embodiment of the present invention. DETAILED DESCRIPTION

[0043] In order to make the purpose, technical solution and advantages of the present invention clearer, the technical solution of the present invention will be clearly and completely described in conjunction with the specific embodiments of the present invention and the corresponding drawings. 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. The technical solutions provided by the embodiments of the present invention are described in detail below in conjunction with the drawings.

[0044] In order to better understand the purpose of the present invention, the present invention is described in further detail below.

[0045] The present invention provides a method for planning and configuring a new energy synchronous machine and reactor system for a regional power grid with multiple points, comprising:

[0046] Step S101, obtaining regional power grid basic data, new energy resource data, power system operation data and new energy synchronous machine parameters;

[0047] In step S101, obtaining regional power grid basic data, new energy resource data, power system operation data and new energy synchronous machine parameters is the first and most important step in planning and configuring the new energy synchronous machine stack system.

[0048] The topological structure of a regional power grid describes the substations, transmission lines and the connections between them in the grid.

[0049] Transmission line parameters include electrical parameters such as line resistance, reactance, and susceptance.

[0050] The substation location records the geographical location of each substation, which helps to determine the reasonable deployment location of the new energy synchronous machine.

[0051] Substation capacity reflects the ability of the substation to process electrical energy.

[0052] The substation load distribution information shows the load conditions in different areas of the power grid, which helps to evaluate the impact of new energy synchronous machines on the power grid load.

[0053] Regional wind energy records the distribution and intensity of wind energy resources in the region and is an important basis for planning wind power generation.

[0054] Regional solar energy provides information such as the radiation intensity and sunshine time of solar energy resources in the region.

[0055] The real-time load data of the power grid is used to reflect the current load level of the power grid.

[0056] The real-time electricity supply and demand curve of the power grid shows the dynamic balance relationship between electricity supply and demand in the power grid, which helps to understand the operating status of the power grid.

[0057] The real-time grid frequency of the power grid is one of the important indicators for evaluating the stability of the power grid.

[0058] The real-time voltage stability index of the power grid provides a quantitative assessment of the voltage stability of the power grid, which is of great significance for identifying potential problems in the power grid.

[0059] New energy synchronous machine parameters include:

[0060] The technical parameters of new energy wind turbines include the rated power, speed range, wind energy conversion efficiency, etc., which are parameters for evaluating wind power generation capacity.

[0061] The technical parameters of the inverter and synchronous machine in the new energy solar power generation system describe the coordination and working performance between the inverter and the synchronous machine.

[0062] Rated power, rated voltage, moment of inertia, control strategy parameters and protection settings of new energy synchronous machines: These parameters together determine the operating characteristics and protection mechanisms of the synchronous machine.

[0063] Step S102, based on the regional power grid basic data, the regional power grid basic data, the new energy resource data, the power system operation data and the new energy synchronous machine parameters are used to train the neural network model to obtain a regional power grid multi-point layout new energy synchronous machine system planning configuration model;

[0064] Train the neural network model and pre-process the collected regional power grid basic data, new energy resource data, power system operation data and new energy synchronous machine parameters, which includes data cleaning (removing outliers, missing value processing, etc.), data normalization or standardization and other steps to improve the quality and consistency of the data.

[0065] Next, extract features from the preprocessed data. These features should be able to fully reflect the structure and operation status of the power grid and the characteristics of the new energy synchronous machine, such as the topological structure characteristics of the power grid, the parameter characteristics of the transmission line, the load characteristics of the power system, the distribution characteristics of the new energy resources, and the technical parameter characteristics of the synchronous machine.

[0066] Select a neural network model suitable for handling such planning configuration problems, such as multi-layer perceptron (MLP), convolutional neural network (CNN) or recurrent neural network (RNN). Depending on the complexity of the problem and the characteristics of the data, it may be necessary to design a specific network structure, such as increasing the number of hidden layers and selecting a suitable activation function.

[0067] Determine the structure of the input layer, hidden layer and output layer of the model. The input layer should be able to receive preprocessed feature data; the hidden layer is used to extract the deep features of the data; the output layer outputs the planning and configuration scheme of the new energy synchronous machine stack system, such as the deployment point, capacity configuration and control strategy of the synchronous machine.

[0068] The neural network model is trained using the preprocessed data and its features as input. During the training process, the model continuously adjusts its internal parameters (weights and biases) to minimize the prediction error and learn the mapping relationship between input data and output configuration.

[0069] The model parameters are adjusted using the gradient descent method or its variants (such as the Adam optimizer). In each iteration, the error between the planned configuration predicted by the model and the actual configuration is calculated, and then the model parameters are updated according to the error back-propagation algorithm.

[0070] Repeat the above training process until the performance of the model on the validation set reaches the preset standard or the number of training times reaches the preset upper limit. At this point, the model is considered to have learned the effective mapping relationship between input data and output configuration.

[0071] After the model training is completed, the model is verified using the test set to evaluate its generalization ability on unseen data. If the model performance meets the expected standard, it is saved as a regional power grid multi-point layout new energy synchronous machine reactor system planning and configuration model. The saved model will be used in subsequent steps to process the real-time new energy synchronous machine reactor system operation data to output a reasonable planning and configuration plan.

[0072] Step S103, collecting real-time new energy synchronous machine stack system operation data and substituting it into the regional power grid multi-point layout new energy synchronous machine stack system planning configuration model to obtain the first new energy synchronous machine stack system planning configuration;

[0073] The operation data of the new energy synchronous machine system is collected in real time through sensors, monitoring equipment or remote communication interfaces installed on the new energy synchronous machine system. These data should include the operation status of the synchronous machine (such as power output, voltage, current, etc.), environmental parameters (such as wind speed, light intensity, etc., which are particularly important for wind and solar power generation systems) and relevant operation data of the power grid (such as power grid frequency, voltage stability indicators, etc.).

[0074] Preprocess the collected real-time operation data to ensure the quality and consistency of the data. The preprocessing steps may include data cleaning (noise removal, outlier processing, etc.), data normalization or standardization, etc., so that the model can better process the data.

[0075] The pre-processed real-time operation data is loaded into the regional power grid multi-point layout new energy synchronous reactor system planning and configuration model. The model will calculate the preliminary new energy synchronous reactor system planning and configuration scheme based on the input data and the mapping relationship between input and output learned during the training process.

[0076] The model outputs the planning and configuration scheme of the first new energy synchronous machine system. This scheme usually includes information such as the deployment point, capacity configuration and control strategy of the synchronous machine. This information will provide a basis for subsequent simulation verification and optimization steps.

[0077] Decode the planning configuration scheme output by the model and convert it into planning configuration information that is easy to understand and implement. This includes detailed information such as the geographical location of the deployment point, the capacity and model of the synchronous machine, and the setting of control parameters. Organize the planning configuration information into a report format for decision makers, engineers and other relevant personnel to review and use.

[0078] Step S104, substituting the planned configuration of the new energy synchronous machine stack system into the preset new energy synchronous machine stack system simulation model to obtain power grid operation simulation data, extracting data features of the power grid operation simulation data to obtain power grid operation simulation feature data, matching the power grid operation simulation feature data in a preset transient overvoltage scheme configuration knowledge base to obtain a transient overvoltage scheme configuration matching result, the transient overvoltage matching scheme result includes a transient overvoltage matching scheme configuration success and a transient overvoltage matching scheme failure;

[0079] Substitute the new energy synchronous machine stack system planning configuration obtained in step S103 into the preset new energy synchronous machine stack system simulation model. This simulation model should be able to accurately simulate the actual operation of the power grid, including the dynamic characteristics of the synchronous machine, the topological structure of the power grid, load changes and other factors.

[0080] Start the simulation model and run it according to the preset simulation parameters and scenarios. During the simulation, the model will simulate the operation of the power grid under different conditions, including normal operation, fault conditions, and extreme weather conditions. During the simulation, relevant data on the operation of the power grid, such as voltage, current, power, frequency, etc., are collected. These data will be used to evaluate the impact of the planned configuration on the operation of the power grid.

[0081] The collected power grid operation simulation data is subjected to data feature extraction to obtain key feature data that can reflect the power grid operation status. These feature data should be able to fully and accurately reflect the operation of the power grid under different working conditions.

[0082] The extracted power grid operation simulation feature data is matched in the preset transient overvoltage scheme configuration knowledge base, which should contain various possible transient overvoltage situations and their corresponding solutions.

[0083] The matching process will determine whether the current planning configuration can effectively solve the potential transient overvoltage problem. There are two matching results: the transient overvoltage matching solution is successfully configured and the transient overvoltage matching solution is unsuccessful.

[0084] If the matching result is successful, it means that the current planning configuration can effectively solve the transient overvoltage problem and can enter the next implementation stage.

[0085] If the matching result is unsuccessful, it means that the current planning configuration may not be able to completely solve the transient overvoltage problem, or there are other potential risks. At this time, it is necessary to enter step S105 to optimize the planning configuration.

[0086] Through the simulation verification and transient overvoltage scheme matching in step S104, we can make a preliminary assessment of the planning configuration of the new energy synchronous machine system to ensure that it can effectively solve the transient overvoltage problem in the power grid. If the matching is unsuccessful, we still need further optimization steps to improve the planning configuration.

[0087] Step S105, if the transient overvoltage matching scheme is unsuccessful, the historical data of the regional power grid multi-point layout of new energy synchronous machine stack system is used, and the historical data of the regional power grid multi-point layout of new energy synchronous machine stack system and the power grid operation simulation feature data are used to optimize the regional power grid multi-point layout of new energy synchronous machine stack system planning and configuration model using a genetic algorithm, and the optimized regional power grid multi-point layout of new energy synchronous machine stack system planning and configuration model is used to process the real-time new energy synchronous machine stack system operation data, and the second new energy synchronous machine stack system planning configuration is output, and the second new energy synchronous machine stack system planning configuration is used as the regional power grid multi-point layout of new energy synchronous machine stack system planning configuration.

[0088] According to the matching result of step S104, it is confirmed that the current planning configuration of the new energy synchronous machine stack system cannot solve the transient overvoltage problem and needs to be optimized. Collect historical data of the new energy synchronous machine stack system with multiple points in the regional power grid. These data should include past planning configuration schemes, actual operation results, fault records, and corresponding treatment measures. Historical data provides valuable experience and reference for the optimization process.

[0089] The collected historical data is integrated with the power grid operation simulation characteristic data obtained in step S104. The data is pre-processed such as cleaning, normalization or standardization to ensure the quality and consistency of the data.

[0090] Select genetic algorithm as the optimization algorithm. Genetic algorithm is a search algorithm based on the principle of biological evolution. It has the advantages of strong global search capability and easy parallelization. It is suitable for solving complex optimization problems. Set the optimization goal according to actual needs. For example, the amplitude, duration or frequency of transient overvoltage can be minimized as the optimization goal.

[0091] The planning and configuration model of the regional power grid multi-point layout of new energy synchronous reactor system is optimized by using the historical data of the regional power grid multi-point layout of new energy synchronous reactor system and the power grid operation simulation feature data, combined with the genetic algorithm. When constructing the optimization model, it is necessary to define the fitness function to evaluate the advantages and disadvantages of different planning and configuration schemes.

[0092] Execute the optimization process of the genetic algorithm. Through genetic operations such as selection, crossover, and mutation, new planning configuration schemes are continuously generated and their fitness is evaluated. This process is repeated until a planning configuration scheme that meets the optimization goal is found or the preset number of iterations is reached.

[0093] The optimized regional power grid multi-point layout new energy synchronous machine reactor system planning configuration model is used to process the real-time new energy synchronous machine reactor system operation data and output the second new energy synchronous machine reactor system planning configuration. This configuration scheme should have better performance in solving transient overvoltage problems than the previous scheme.

[0094] The second new energy synchronous machine reactor system planning configuration is used as the final planning configuration scheme for the multi-point layout of the new energy synchronous machine reactor system in the regional power grid. According to this scheme, the new energy synchronous machine reactor system is adjusted and optimized accordingly.

[0095] Specifically, the method for planning and configuring a regional power grid multi-point layout new energy synchronous machine and reactor system, step S101, comprises:

[0096] The basic data of regional power grid includes the topological structure of regional power grid, transmission line parameters, substation location, substation capacity, and substation load distribution information;

[0097] New energy resource data include regional wind energy and regional solar energy;

[0098] Acquiring power system operation data including real-time load data of the power grid, real-time power supply and demand curve of the power grid, real-time power grid frequency of the power grid and real-time voltage stability index of the power grid;

[0099] The parameters of new energy synchronous machines are obtained, including the technical parameters of new energy wind turbines, the technical parameters of the inverter and synchronous machine in the new energy solar power generation system, the rated power, rated voltage, moment of inertia, control strategy parameters and protection settings of the new energy synchronous machine.

[0100] The topological structure of the regional power grid: including the connection relationship between various nodes in the power grid (such as substations, power plants, etc.), as well as the direction and length of transmission lines.

[0101] Transmission line parameters: including electrical parameters such as resistance, reactance, susceptance, etc. of the transmission line, as well as the rated voltage and rated current of the line.

[0102] Substation location: The geographical location information of the substation, including longitude, latitude or specific address description.

[0103] Substation capacity: The transformer capacity of a substation, indicating the maximum electrical load it can handle.

[0104] Substation load distribution information: the load area served by the substation and its load distribution, including the size and type of load (such as industrial, commercial, residential, etc.) and the law of load change.

[0105] Wind energy in the region: including the distribution of wind speed, wind energy density, frequency distribution of wind direction, etc. These data are usually obtained through meteorological stations or special wind energy assessment equipment.

[0106] Solar energy in the region: including solar radiation intensity, sunshine duration, annual and daily changes in solar radiation, etc. These data are usually obtained through solar radiometers or meteorological stations.

[0107] Real-time load data of the power grid: indicates the power load situation in the power grid at each moment, usually including the total load, the proportion of various types of loads, and the load change trend.

[0108] Real-time power supply and demand curve of the power grid: It indicates the balance between power supply and demand in the power grid, including the output of generators, load consumption, and the charging and discharging status of energy storage devices.

[0109] Real-time grid frequency of the power grid: It indicates the frequency of the alternating current in the power grid, which is one of the important indicators for the stable operation of the power grid.

[0110] Real-time voltage stability indicators of the power grid: used to evaluate the stability of the power grid voltage, including the voltage fluctuation range, voltage deviation and voltage recovery capability.

[0111] Technical parameters of new energy wind turbines: including rated power, rated voltage, speed range, starting wind speed, cut-out wind speed, rotor diameter, generator type, etc.

[0112] The technical parameters of the inverter and synchronous machine in the new energy solar power generation system include the rated power, conversion efficiency, input voltage range, output voltage and frequency of the inverter, as well as the matching parameters of the inverter and synchronous machine, such as control strategy, protection settings, etc.

[0113] The rated power and rated voltage of the new energy synchronous machine: indicate the maximum power and voltage that the synchronous machine can provide during normal operation.

[0114] Moment of inertia: refers to the inertia of the synchronous machine rotor when it rotates, which affects the response speed of the synchronous machine to changes in grid frequency.

[0115] Control strategy parameters: including parameters related to the control strategies such as synchronous machine startup, grid connection, speed regulation, and voltage regulation.

[0116] Protection settings: including the setting parameters of the synchronous motor's overcurrent protection, overvoltage protection, undervoltage protection, overheating protection and other protection functions.

[0117] Specifically, the method for planning and configuring a regional power grid multi-point layout of a new energy synchronous machine and reactor system, step S102 includes:

[0118] Based on the basic data of regional power grid, the basic data of regional power grid, new energy resource data, power system operation data and new energy synchronous machine parameters are preprocessed and data features are extracted. The preprocessed data and the extracted data features are used to train the neural network model. The model parameters are adjusted by the gradient descent method to minimize the model prediction error. The planning and configuration model of the regional power grid multi-point layout new energy synchronous machine system is obtained.

[0119] Preprocess the regional power grid basic data, new energy resource data, power system operation data and new energy synchronous machine parameters. The purpose of preprocessing includes cleaning data (removing erroneous, abnormal or missing data), normalizing or standardizing data (converting data to a uniform scale so that the model can better process it), and possible data conversion (such as converting time series data to frequency domain data, etc.).

[0120] Extract features that have an important impact on the planning and configuration of the new energy synchronous machine system from the preprocessed data. These features may include the topological structure characteristics of the power grid, the load distribution characteristics, the spatiotemporal distribution characteristics of new energy resources, the technical parameter characteristics of the synchronous machine, etc. The feature extraction methods may include statistical analysis, machine learning algorithms, signal processing technology, etc.

[0121] According to the extracted data features, a neural network model suitable for solving the planning and configuration problem of the new energy synchronous reactor system is constructed. The structure of the neural network may include an input layer, a hidden layer, and an output layer, where the input layer receives the extracted data features, the hidden layer performs complex nonlinear transformations, and the output layer gives suggestions or prediction results for the planning configuration.

[0122] Use the preprocessed data and extracted data features as the input of the neural network, and adjust the parameters of the neural network (such as weights and biases) through optimization algorithms such as gradient descent to minimize the prediction error of the model. During the training process, it may be necessary to divide the data set into training sets, validation sets, and test sets in order to evaluate the performance of the model and perform parameter tuning.

[0123] After training is completed, the test set is used to verify and evaluate the neural network model. Evaluation indicators may include prediction accuracy, recall rate, F1 score, etc.

[0124] After training, verification and evaluation, a neural network model was obtained that can be used for planning and configuring the new energy synchronous reactor system in the multi-point layout of the regional power grid. This model can give optimized planning and configuration suggestions based on new input data (such as real-time power system operation data and new energy resource data).

[0125] Through the training process of step S102, we obtain a neural network model that can predict and optimize the planning and configuration of the new energy synchronous machine reactor system. This model will serve as the basis for subsequent steps (such as simulation verification and optimization) to help us better plan and configure the new energy synchronous machine reactor system in the regional power grid.

[0126] Specifically, the method for planning and configuring a regional power grid multi-point layout new energy synchronous machine and reactor system, step S103, comprises:

[0127] Through the sensors, monitoring equipment or remote communication interfaces installed on the new energy synchronous machine stack system, the real-time operation data of the new energy synchronous machine stack system is collected, the collected real-time operation data is preprocessed, and the preprocessed data is loaded into the planning and configuration model of the regional power grid multi-point layout new energy synchronous machine stack system. The planning and configuration model of the regional power grid multi-point layout new energy synchronous machine stack system is used to calculate the input real-time operation data to obtain the planning and configuration scheme of the new energy synchronous machine stack system. The planning and configuration scheme of the new energy synchronous machine stack system includes the deployment points, capacity configuration and control strategy of the synchronous machine;

[0128] The planning configuration of the new energy synchronous machine stack system is decoded and converted into planning configuration information, which includes the geographical location of the deployment point, the capacity and model of the synchronous machine, and the setting of the control parameters, and is output in the form of a report.

[0129] The operation data of the system is collected in real time through various sensors, monitoring equipment or remote communication interfaces installed on the new energy synchronous machine system. These data may include electrical parameters such as the output power, speed, voltage, current, etc. of the synchronous machine, as well as environmental parameters such as ambient temperature, wind speed, and solar radiation intensity.

[0130] Preprocess the collected real-time operation data to ensure the accuracy and consistency of the data. Preprocessing may include data cleaning (removing erroneous or abnormal data), data normalization or standardization (converting data to a range acceptable to the model), data synchronization (ensuring the consistency of data from different sources in time), etc.

[0131] The pre-processed real-time operation data is loaded into the previously trained regional power grid multi-point layout new energy synchronous reactor system planning and configuration model. The model will use this data as input for subsequent calculations and optimization.

[0132] The planning and configuration model of the new energy synchronous machine and reactor system with multi-point layout in the regional power grid is used to calculate the input real-time operation data to obtain the planning and configuration scheme of the new energy synchronous machine and reactor system. This scheme should take into account factors such as the current state of the power grid, future load forecasts, and the availability of new energy resources, and give specific suggestions on the deployment points, capacity configuration, and control strategies of the synchronous machine.

[0133] Decode the calculated planning configuration scheme and convert it into planning configuration information that is easier to understand and implement. This information should include the geographical location of the deployment point (such as longitude, latitude or specific address description), the capacity and model of the synchronous machine (such as rated power, rated voltage, moment of inertia, etc.), and the setting of control parameters (such as starting wind speed, cut-out wind speed, control strategy parameters, etc.).

[0134] Organize the planning configuration information into a report form so that decision makers or implementers can clearly understand and adopt these recommendations. The report may include charts, tables, text descriptions, etc., so that people from different backgrounds can understand it.

[0135] Specifically, the method for planning and configuring a regional power grid multi-point layout new energy synchronous machine and reactor system, step S104 includes:

[0136] Determine the simulation target and scope, select the simulation tool, and build the synchronous machine model in the simulation tool according to the simulation target and scope, the simulation tool, and the actual configuration and parameters of the new energy synchronous machine stack system;

[0137] Set the initial conditions and boundary conditions of the model, and configure different simulation scenarios according to the operating characteristics of the new energy synchronous reactor system and the actual situation of the power grid. Different simulation scenarios include normal operation scenarios, fault scenarios, and extreme weather scenarios;

[0138] Run the simulation model, collect grid operation simulation data, start the simulation tool, run the simulation model according to the set parameters and scenarios, monitor the operating status of the model during the simulation, and collect the grid operation data generated during the simulation. The grid operation data includes voltage, current, power and frequency.

[0139] Determine the simulation objectives and scope, evaluate the impact of the new energy synchronous machine system on the stability of the power grid, optimize the layout and capacity configuration of the synchronous machine, verify the effectiveness of the control strategy, etc. According to the simulation objectives, define the scope of the simulation, including the simulation time scale (such as short-term, medium-term, long-term), spatial scale (such as local power grid, regional power grid, national power grid) and physical phenomena that need to be considered (such as power flow distribution, voltage stability, frequency response, etc.).

[0140] Select the appropriate simulation tool according to the simulation objectives and scope. Common power system simulation tools include PSASP, PSS / E, ETAP, DIgSILENT, etc. These tools have different characteristics and advantages and need to be selected according to specific needs.

[0141] In the simulation tool, a synchronous machine model is built according to the actual configuration and parameters of the new energy synchronous machine stack system. This includes the electrical parameters of the synchronous machine (such as rated power, rated voltage, impedance, etc.), mechanical parameters (such as moment of inertia, damping coefficient, etc.) and control strategy parameters (such as speed regulator parameters, excitation system parameters, etc.).

[0142] Set the initial conditions of the simulation model, such as the initial power flow distribution of the power grid, the initial operating state of the synchronous machine, etc. Set the boundary conditions of the simulation model according to the actual situation of the power grid and the simulation objectives, such as the access point of the external power grid, the change law of the load, etc.

[0143] Different simulation scenarios are configured according to the operating characteristics of the new energy synchronous reactor system and the actual situation of the power grid. These scenarios should cover various operating conditions that the power grid may encounter, such as normal operation scenarios, fault scenarios (such as line tripping, generator failure, etc.), and extreme weather scenarios (such as strong winds, heavy rains, high temperatures, etc.).

[0144] Start simulation: Start the simulation tool and run the simulation model according to the set parameters and scenarios.

[0145] Monitoring status: During the simulation process, the running status of the model is monitored in real time to ensure the smooth progress of the simulation process.

[0146] Data collection: Collect the grid operation data generated during the simulation, including voltage, current, power, frequency, etc. These data will be used for subsequent analysis and evaluation.

[0147] Data collection: Organize and save the data generated during the simulation process for subsequent analysis.

[0148] Data analysis: Analyze the collected simulation data to evaluate the impact of the new energy synchronous machine system on the stability of the power grid, optimize the layout and capacity configuration of the synchronous machine, verify the effectiveness of the control strategy, etc.

[0149] Specifically, the method for planning and configuring a regional power grid multi-point layout new energy synchronous machine and reactor system, step S105, comprises:

[0150] The power grid operation simulation characteristic data is compared with the historical data of the regional power grid multi-point layout new energy synchronous machine reactor system to verify the accuracy of the new energy synchronous machine reactor system simulation model. If there is a large deviation between the power grid operation simulation characteristic data and the historical data of the regional power grid multi-point layout new energy synchronous machine reactor system, the historical data of the regional power grid multi-point layout new energy synchronous machine reactor system is optimized.

[0151] The grid operation simulation characteristic data is compared with the historical data of the regional grid multi-point layout new energy synchronous reactor system. This process aims to evaluate the accuracy of the simulation model by comparing the actual operation data with the simulation data.

[0152] The comparison results will be used to verify the accuracy of the new energy synchronous reactor system simulation model. If the simulation data is highly consistent with the historical data, it means that the model can simulate the operation of the actual system well; otherwise, the model may need to be further adjusted and optimized.

[0153] Deviation analysis: If it is found that there is a large deviation between the power grid operation simulation characteristic data and the historical data of the regional power grid multi-point layout new energy synchronous reactor system, a deviation analysis is required. This process aims to find out the cause of the deviation, which may be improper model parameter settings, simulation conditions that do not match the actual situation, errors in historical data, etc.

[0154] Data optimization: Based on the results of deviation analysis, the historical data of the regional power grid multi-point layout of new energy synchronous reactor system is optimized. This may include data cleaning (removing erroneous or abnormal data), data calibration (adjusting data to make it more consistent with the actual situation), data enhancement (increasing data points through interpolation or extrapolation to increase data density), etc.

[0155] After completing the data optimization, the simulation model needs to be rerun and the new simulation results need to be compared with the optimized historical data. This process may require multiple iterations until the accuracy of the simulation model meets the requirements. During the iterative optimization process, if the model itself is found to have defects or deficiencies, the model may need to be adjusted. This may include modifying the model structure, adjusting model parameters, improving control strategies, etc.

[0156] After the accuracy of the simulation model is met, the simulation results need to be evaluated, including analyzing the performance of the new energy synchronous reactor system in different scenarios and evaluating the feasibility and effectiveness of the planning configuration scheme.

[0157] The evaluation results should be organized into a report so that decision makers or implementers can clearly understand the accuracy of the simulation model, the optimization process of historical data, and the analysis and evaluation of simulation results. The report should include detailed data comparison results, deviation analysis, data optimization methods, model adjustment plans, and simulation results analysis.

[0158] Specifically, the method for planning and configuring a regional power grid multi-point layout new energy synchronous machine and reactor system, step S105, comprises:

[0159] Integrate the historical data of the regional power grid multi-point layout new energy synchronous machine system and the power grid operation simulation feature data, and organize the historical data of the regional power grid multi-point layout new energy synchronous machine system, including the operation records, fault records and maintenance records of the new energy synchronous machine system, and extract the power grid operation simulation feature data, including voltage fluctuations, current changes and power factor indicators;

[0160] receiving optimization objectives, wherein the optimization objectives include minimizing voltage fluctuations, maximizing utilization of new energy, and reducing system losses;

[0161] Receive the framework parameters of the genetic algorithm, determine the population size of the genetic algorithm according to the framework parameters of the genetic algorithm, that is, the number of solutions participating in the optimization at the same time, design the selection, crossover, and mutation genetic operators, and define the fitness function to evaluate the quality of each solution, where the solution is the planning configuration plan;

[0162] Generate an initial solution set, i.e., a population of the genetic algorithm, and randomly generate a set of initial solutions according to the parameter range and constraint conditions of the planning and configuration model of the new energy synchronous reactor system with multi-point layout of the regional power grid, each solution represents a planning and configuration scheme of the new energy synchronous reactor system;

[0163] Calculate the fitness value of each solution in the population, substitute each solution into the planning and configuration model of the regional power grid multi-point layout new energy synchronous machine reactor system, and calculate the fitness value corresponding to each solution by combining the historical data of the regional power grid multi-point layout new energy synchronous machine reactor system and the power grid operation simulation feature data;

[0164] A new set of solutions is generated through selection, crossover, and mutation until the preset number of iterations is reached or the optimization goal is met. After the optimization is completed, the solution with the highest fitness value is selected from the population as the optimal solution, that is, the optimized planning and configuration plan for the new energy synchronous reactor system.

[0165] Integrate historical data of new energy synchronous reactor systems in multi-point layout of regional power grids, including operation records, fault records and maintenance records of new energy synchronous reactor systems. These data provide actual operation experience and reference for optimization. Extract characteristic data from power grid operation simulation, such as voltage fluctuations, current changes and power factor indicators. These data reflect the operation status of the power grid under different configurations and are an important basis for evaluating the pros and cons of planning configuration schemes.

[0166] According to the actual needs of the power grid and the characteristics of the new energy synchronous reactor system, the optimization goals are set. Common optimization goals include minimizing voltage fluctuations, maximizing the utilization rate of new energy, and reducing system losses.

[0167] Determine the population size of the genetic algorithm (i.e. the number of solutions participating in the optimization at the same time), the design method of the selection, crossover, and mutation genetic operators, and the definition method of the fitness function. The fitness function is used to evaluate the quality of each solution. It is usually constructed according to the optimization goal, such as converting indicators such as voltage fluctuation, new energy utilization rate, and system loss into fitness values.

[0168] According to the parameter range and constraints of the planning and configuration model of the new energy synchronous machine-to-reactor system with multi-point layout in the regional power grid, a set of initial solutions is randomly generated. Each solution represents a planning and configuration scheme for the new energy synchronous machine-to-reactor system, including the deployment point, capacity configuration and control strategy of the synchronous machine.

[0169] Substitute each solution into the regional power grid multi-point layout new energy synchronous reactor system planning and configuration model, combine historical data and simulation feature data, and calculate the fitness value corresponding to each solution. This step is the key to evaluating the pros and cons of each solution.

[0170] Selection operation: Select excellent solutions as parents based on the fitness value to generate the next generation of solutions.

[0171] Crossover operation: Perform a crossover operation on the selected parent solution to generate a new solution (offspring).

[0172] Mutation operation: Perform mutation operation on the newly generated solutions to increase the diversity of solutions.

[0173] Iterative optimization: Repeat the selection, crossover, and mutation operations until the preset number of iterations is reached or the optimization goal is met.

[0174] After the optimization is completed, the solution with the highest fitness value is selected from the population as the optimal solution. This solution is the optimized planning configuration scheme for the new energy synchronous reactor system. The optimal solution and its corresponding planning configuration scheme are output. The data, charts and results of the optimization process are sorted out and a detailed report is generated so that decision makers or implementers can understand the optimization process and results.

[0175] The present invention provides a method for planning and configuring a regional power grid multi-point layout new energy synchronous machine system. Aiming at the weak voltage support capability of some high-proportion new energy power systems at the sending end, the serious transient overvoltage problem, and the transient overvoltage that will cause voltage fluctuations and flicker in the power grid, the following technical solutions are adopted to solve the problem:

[0176] First, by obtaining regional power grid basic data, new energy resource data, power system operation data and new energy synchronous machine parameters, these data provide a basis for subsequent model training and planning configuration.

[0177] Secondly, based on the above data, a neural network model is used for training to obtain a regional power grid multi-point layout new energy synchronous machine reactor system planning and configuration model. This model can output the first new energy synchronous machine reactor system planning and configuration based on real-time new energy synchronous machine reactor system operation data.

[0178] Then, the planned configuration is substituted into the preset new energy synchronous machine system simulation model for simulation to obtain the grid operation simulation data. The features of these data are extracted and matched in the preset transient overvoltage scheme configuration knowledge base to check whether there is a suitable transient overvoltage scheme configuration.

[0179] If the transient overvoltage matching solution is unsuccessful, that is, no suitable configuration solution is found, the historical data of the regional power grid multi-point layout of the new energy synchronous reactor system and the power grid operation simulation feature data will be used to optimize the planning configuration model using a genetic algorithm. Through continuous iteration and optimization, the second new energy synchronous reactor system planning configuration is obtained. This configuration solution is more likely to solve the transient overvoltage problem after optimization.

[0180] In specific implementation, by monitoring the real-time operation data of the new energy synchronous machine system and substituting it into the optimized planning configuration model, a more accurate and effective planning configuration scheme can be calculated. This scheme includes the deployment point, capacity configuration and control strategy of the synchronous machine, which can effectively improve the stability of the regional power grid and solve the transient overvoltage problem, thereby avoiding voltage fluctuations and flicker problems in the power grid.

[0181] In summary, the present invention provides an effective planning and configuration method for a regional power grid multi-point layout of new energy synchronous machine systems through a series of steps such as neural network model training, simulation verification, and genetic algorithm optimization, which can solve the problems of weak voltage support capacity and transient overvoltage in some sending-end high-proportion new energy power systems.

Claims

1. A method for planning and configuring a new energy synchronous machine system for a regional power grid with multiple points, characterized in that: include: Step S101, obtaining regional power grid basic data, new energy resource data, power system operation data and new energy synchronous machine parameters; Step S102, based on the regional power grid basic data, the regional power grid basic data, the new energy resource data, the power system operation data and the new energy synchronous machine parameters are used to train the neural network model to obtain a regional power grid multi-point layout new energy synchronous machine system planning configuration model; Step S103, collecting real-time new energy synchronous machine stack system operation data and substituting it into the regional power grid multi-point layout new energy synchronous machine stack system planning configuration model to obtain the first new energy synchronous machine stack system planning configuration; Step S104, substituting the planned configuration of the new energy synchronous machine stack system into the preset new energy synchronous machine stack system simulation model to obtain power grid operation simulation data, extracting data features of the power grid operation simulation data to obtain power grid operation simulation feature data, matching the power grid operation simulation feature data in a preset transient overvoltage scheme configuration knowledge base to obtain a transient overvoltage scheme configuration matching result, the transient overvoltage matching scheme result includes a transient overvoltage matching scheme configuration success and a transient overvoltage matching scheme failure; Step S105, if the transient overvoltage matching scheme is unsuccessful, the historical data of the regional power grid multi-point layout of new energy synchronous machine stack system is used, and the historical data of the regional power grid multi-point layout of new energy synchronous machine stack system and the power grid operation simulation feature data are used to optimize the regional power grid multi-point layout of new energy synchronous machine stack system planning and configuration model using a genetic algorithm, and the optimized regional power grid multi-point layout of new energy synchronous machine stack system planning and configuration model is used to process the real-time new energy synchronous machine stack system operation data, and the second new energy synchronous machine stack system planning configuration is output, and the second new energy synchronous machine stack system planning configuration is used as the regional power grid multi-point layout of new energy synchronous machine stack system planning configuration.

2. The method for planning and configuring a new energy synchronous machine system for a regional power grid with multiple points layout as claimed in claim 1, characterized in that: The step S101 includes: The basic data of regional power grid include the topological structure of regional power grid, transmission line parameters, substation location, substation capacity, and substation load distribution information; New energy resource data include regional wind energy and regional solar energy; Acquiring power system operation data including real-time load data of the power grid, real-time power supply and demand curve of the power grid, real-time power grid frequency of the power grid and real-time voltage stability index of the power grid; The parameters of new energy synchronous machines are obtained, including the technical parameters of new energy wind turbines, the technical parameters of the inverter and synchronous machine in the new energy solar power generation system, the rated power, rated voltage, moment of inertia, control strategy parameters and protection settings of the new energy synchronous machine.

3. The method for planning and configuring a new energy synchronous machine system for a regional power grid with multiple points layout as claimed in claim 1, characterized in that: The step S102 includes: Based on the basic data of regional power grid, the basic data of regional power grid, new energy resource data, power system operation data and new energy synchronous machine parameters are preprocessed and data features are extracted. The preprocessed data and the extracted data features are used to train the neural network model. The model parameters are adjusted by the gradient descent method to minimize the model prediction error. The planning and configuration model of the regional power grid multi-point layout new energy synchronous machine system is obtained.

4. The method for planning and configuring a new energy synchronous machine system for a regional power grid with multiple points layout as claimed in claim 1, characterized in that: The step S103 includes: Through the sensors, monitoring equipment or remote communication interfaces installed on the new energy synchronous machine stack system, the real-time operation data of the new energy synchronous machine stack system is collected, the collected real-time operation data is preprocessed, and the preprocessed data is loaded into the planning and configuration model of the regional power grid multi-point layout new energy synchronous machine stack system. The planning and configuration model of the regional power grid multi-point layout new energy synchronous machine stack system is used to calculate the input real-time operation data to obtain the planning and configuration scheme of the new energy synchronous machine stack system. The planning and configuration scheme of the new energy synchronous machine stack system includes the deployment points, capacity configuration and control strategy of the synchronous machine; The planning configuration of the new energy synchronous machine stack system is decoded and converted into planning configuration information, which includes the geographical location of the deployment point, the capacity and model of the synchronous machine, and the setting of the control parameters, and is output in the form of a report.

5. The method for planning and configuring a new energy synchronous machine system for a regional power grid with multiple points layout as claimed in claim 1, characterized in that: The step S104 includes: Determine the simulation target and scope, select the simulation tool, and build the synchronous machine model in the simulation tool according to the simulation target and scope, the simulation tool, and the actual configuration and parameters of the new energy synchronous machine stack system; Set the initial conditions and boundary conditions of the model, and configure different simulation scenarios according to the operating characteristics of the new energy synchronous reactor system and the actual situation of the power grid. Different simulation scenarios include normal operation scenarios, fault scenarios, and extreme weather scenarios; Run the simulation model, collect grid operation simulation data, start the simulation tool, run the simulation model according to the set parameters and scenarios, monitor the operating status of the model during the simulation, and collect the grid operation data generated during the simulation. The grid operation data includes voltage, current, power and frequency.

6. The method for planning and configuring a new energy synchronous machine system for a regional power grid with multiple points layout as claimed in claim 1, characterized in that: The step S105 includes: The power grid operation simulation characteristic data is compared with the historical data of the regional power grid multi-point layout new energy synchronous machine reactor system to verify the accuracy of the new energy synchronous machine reactor system simulation model. If there is a large deviation between the power grid operation simulation characteristic data and the historical data of the regional power grid multi-point layout new energy synchronous machine reactor system, the historical data of the regional power grid multi-point layout new energy synchronous machine reactor system is optimized.

7. The method for planning and configuring a new energy synchronous machine system for a regional power grid with multiple points of layout as claimed in claim 6, characterized in that: The step S105 includes: Integrate the historical data of the regional power grid multi-point layout new energy synchronous machine system and the power grid operation simulation feature data, and organize the historical data of the regional power grid multi-point layout new energy synchronous machine system, including the operation records, fault records and maintenance records of the new energy synchronous machine system, and extract the power grid operation simulation feature data, including voltage fluctuations, current changes and power factor indicators; receiving optimization objectives, wherein the optimization objectives include minimizing voltage fluctuations, maximizing utilization of renewable energy, and reducing system losses; Receive the framework parameters of the genetic algorithm, determine the population size of the genetic algorithm according to the framework parameters of the genetic algorithm, that is, the number of solutions participating in the optimization at the same time, design the selection, crossover, and mutation genetic operators, and define the fitness function to evaluate the quality of each solution, where the solution is the planning configuration plan; Generate an initial solution set, i.e., a population of the genetic algorithm, and randomly generate a set of initial solutions according to the parameter range and constraint conditions of the planning and configuration model of the new energy synchronous reactor system with multi-point layout of the regional power grid, each solution represents a planning and configuration scheme of the new energy synchronous reactor system; Calculate the fitness value of each solution in the population, substitute each solution into the planning and configuration model of the regional power grid multi-point layout new energy synchronous machine reactor system, and calculate the fitness value corresponding to each solution by combining the historical data of the regional power grid multi-point layout new energy synchronous machine reactor system and the power grid operation simulation feature data; A new set of solutions is generated through selection, crossover, and mutation until the preset number of iterations is reached or the optimization goal is met. After the optimization is completed, the solution with the highest fitness value is selected from the population as the optimal solution, that is, the optimized planning and configuration plan for the new energy synchronous reactor system.

Images