Power grid reactive voltage control optimization method

Abstract

The invention discloses a power grid reactive voltage control optimization method, which relates to the field of reactive voltage control, and comprises the following steps: firstly, carrying out demand analysis and data collection, building a power grid model after the demand analysis and data collection are completed, and determining reactive compensation equipment after the power grid model is built; after the reactive compensation equipment is determined to be completed, optimization algorithm application is carried out, operation and simulation are carried out after the optimization algorithm application is completed, implementation and adjustment are carried out after the operation and simulation are completed, and effect evaluation is carried out after implementation and adjustment are completed. According to the reactive voltage control optimization method of the power grid, implementation and adjustment of reactive voltage control optimization of the power grid are a dynamic process, and adaptive adjustment needs to be carried out on the basis of real-time monitoring so as to cope with constantly changing power grid conditions. Through effective monitoring and data analysis and in combination with flexible control measures, the economical efficiency and stability of power grid operation can be ensured, and high-quality power service is provided for users.

Description

Technical Field

[0001] The invention relates to the technical field of reactive voltage control, and in particular to a reactive voltage control optimization method for a power grid. Background Art

[0002] Grid reactive power voltage control optimization refers to the optimization and stability of grid voltage level through reasonable configuration and dispatch of reactive power resources in the grid, while improving the energy efficiency and economy of the system. Reactive power plays an important role in maintaining voltage and supporting power transmission in the power system, so its control is crucial; In the existing technology, reactive voltage control systems often have a slow response speed and cannot adjust the output of generators or compensation equipment in time to cope with voltage fluctuations caused by grid load changes or faults. Many grids still rely on simple control strategies, such as PID control, which lacks flexibility and adaptability for the complex dynamic characteristics of power systems. In order to overcome the above-mentioned shortcomings, the Chinese patent of the prior art (publication number CN117526344A) discloses a distribution network reactive voltage control optimization method and system, which conducts a preliminary analysis of the distribution network, analyzes the reactive voltage and load characteristics, and sets optimization targets; based on the set optimization targets, collects grid data in real time, and performs data analysis through a machine learning deep analysis model; designs reactive voltage control strategies based on the analysis results, and optimizes the distribution network structure; updates reactive voltage control strategies based on monitoring results and current grid conditions. The provided distribution network reactive voltage control optimization method can improve the operating efficiency and stability of the grid, especially when dealing with large-scale new energy access and highly variable loads. Through predictive load management and real-time feedback adjustment, voltage fluctuations and equipment failures can be reduced, and the overall performance and reliability of the grid can be improved. In addition, the grid's ability to respond to extreme events and emergencies is also enhanced; In order to overcome the above shortcomings, the Chinese patent of the prior art (publication number CN104600720B) discloses a method for optimizing voltage and reactive power of a regional power grid, which applies multi-agent technology to the decision-making model of reactive power optimization control of the power grid, and changes the relationship between multiple objectives in reactive power optimization by changing the weight of the scoring basis, thereby enhancing the maintainability and scalability of the system. The reactive power optimization control of the regional power grid adopts a multi-agent technology model and proposes a reactive power optimization control system architecture based on multi-agent technology, which not only avoids a large number of redundant rules in the suboptimal control of the expert system, but also simply changes the relationship between multiple objectives in reactive power optimization by changing the weight of the scoring basis, greatly enhancing the maintainability and scalability of the system; Although the existing technology can overcome the above-mentioned deficiencies, there are still other problems in its operation process, such as: when the reactive power voltage of the power grid is controlled, the stability is poor and the constantly changing power grid conditions cannot be flexibly controlled and adjusted. Summary of the invention

[0003] The purpose of the present invention is to provide a method for optimizing reactive power voltage control of a power grid to solve the problem in the above background technology that when performing reactive power voltage control of the power grid, the stability is poor and the control and adjustment cannot be flexibly performed for the changing power grid conditions.

[0004] To achieve the above-mentioned purpose, the present invention provides the following technical solutions: a method for optimizing reactive power voltage control of a power grid, comprising S1, demand analysis and data collection; S2, establishing a power grid model; S3, determining reactive power compensation equipment; S4, application of optimization algorithm; S5, calculation and simulation; S6, implementation and adjustment; S7, effect evaluation; S8, reporting and optimization; The specific steps include: S1. Demand Analysis and Data Collection Load characteristics analysis: Collect grid load change data, analyze historical load curves, load characteristics, and seasonal changes; Grid status monitoring: using sensors and monitoring equipment to collect status information of voltage, current, power factor, transformers and other equipment; S2. Establishing a power grid model Mathematical model of power grid: According to the topological structure and parameter characteristics of the power grid, the mathematical model of the power grid is established, including the equivalent models of various equipment; Reactive current distribution model: Analyze the reactive power demand of each node and its impact on voltage; S3. Determine reactive power compensation equipment Equipment selection: Select appropriate reactive power compensation devices (such as SVC, STATCOM, capacitor bank, synchronous motor, etc.) according to the characteristics of the power grid; Configuration scheme design: formulate a configuration scheme for reactive power compensation equipment, indicate potential imbalance between supply and demand, and lay out compensation equipment; S4. Application of optimization algorithm Select optimization method: Select appropriate optimization algorithm (such as genetic algorithm, particle swarm) according to the characteristics of the power grid. optimization, linear programming, etc.); Algorithm implementation: Use the selected method to calculate the model and find the best reactive power compensation solution to meet the voltage control requirements; S5. Computation and simulation Formulate strategy: formulate specific reactive power regulation strategy based on optimization results; Simulation test: Verify in a simulated environment to evaluate the effectiveness and robustness of the optimization scheme under different load conditions; S6. Implementation and Adjustment Implementation plan: gradually implement the reactive power compensation plan in the actual power grid according to the optimization results; Dynamic adjustment: After data monitoring, the compensation equipment is adjusted in real time to enter or leave the network to maintain the optimized voltage level; S7. Effect evaluation Monitoring results: After implementation, the operation status of the power grid is continuously monitored to observe voltage fluctuations and changes in reactive power; Feedback and iteration: Based on the feedback from the implementation results, we continuously iterate and improve, update strategies and models to form a closed-loop management; S8. Reporting and Optimization Result report: Form a comprehensive report on the optimization process and results, record the analysis, decision-making basis and implementation results; Experience summary: Summarize the experience gained during the optimization process and improve subsequent optimization strategies and methods.

[0005] Furthermore, in step S1, the collected data is cleaned and preprocessed to ensure the accuracy and consistency of the data, a power system model is established based on the collected data, the reactive voltage control effect under different conditions is simulated and analyzed, a suitable optimization algorithm is used to optimize the reactive voltage control strategy, and the application of heuristic methods, genetic algorithms, etc. in this regard is explored.

[0006] Furthermore, in step S2, the operating data of the actual power grid is collected and compared with the model calculation results to verify the accuracy of the model, perform power flow calculation and dynamic simulation, verify whether the performance of the model under different operating conditions is consistent with the actual situation, and determine the influence of the model parameters on the results through sensitivity analysis, so as to further optimize and adjust the model.

[0007] Furthermore, in step S3, the optimal location of the reactive power compensation equipment is determined to maximize its efficiency and effect, usually near the key node or load center where the voltage fluctuation is large. According to the flow calculation results and load characteristics, the capacity of each reactive power compensation equipment is reasonably determined to ensure that it can meet the reactive power demand at peak load, design the control strategy of the reactive power compensation equipment to ensure that it can respond quickly when the load changes, faults or other situations occur, install the reactive power compensation equipment according to the design plan, and ensure compatibility with the existing power grid, establish a real-time monitoring system, monitor the changes in grid voltage and reactive power, evaluate the performance of the reactive power compensation equipment, and adjust it according to the data, regularly evaluate the working status of the reactive power compensation equipment and the operation status of the power grid to ensure its stable and efficient operation. According to the changes in the power grid, adjust the optimization plan in a timely manner.

[0008] Furthermore, in step S4, reactive voltage control is performed in a certain power grid case by using an optimization algorithm to evaluate the effectiveness and feasibility of the algorithm, thereby ensuring that the voltage is within a specified range and reactive loss is minimized. In modern power grids, it is often necessary to meet multiple goals at the same time (such as reducing costs and improving reliability). An improved multi-objective optimization algorithm (such as an improved genetic algorithm) can be used to guide decision makers to make balanced decisions.

[0009] Furthermore, in step S5, it is ensured that the parameters and structure of the power grid model are accurate, the performance characteristics of all components should be based on actual data, and for the optimization algorithm, the parameter settings should be reasonably tuned to avoid premature convergence or low computational efficiency. Multiple simulations should be performed to confirm the reliability of the results to avoid fluctuations in the results due to accidental factors. The optimization results should be compared with the actual operating data, and the control strategy should be continuously improved to ensure its adaptability and performance.

[0010] Furthermore, in step S6, a comprehensive feedback mechanism is established to ensure that various departments and relevant personnel can obtain information on the operating status of the power grid and the effects of the optimization plan in a timely manner. When implementing the reactive voltage control optimization plan, the impact on users must be fully considered, the power quality must be maintained, and training for operators must be carried out to improve their understanding of the optimization plan and their on-site response capabilities, to ensure the effective implementation of the optimization plan, to pay attention to changes in the external environment and regulations, and to ensure that reactive voltage control measures are consistent with relevant policies and environmental protection requirements.

[0011] Furthermore, in step S7, the evaluation results are compiled into a report to describe the actual effects of the optimization method in voltage control, reducing reactive power loss, improving system stability, etc., and to propose improvement measures and future development directions for the problems found. According to the evaluation results, the reactive power voltage control strategy is adjusted, and the equipment configuration and operation mode are optimized. If it is found that the control effect is not good under specific conditions, targeted optimization or new control means should be added.

[0012] Furthermore, the step S8 ensures that the input data used is accurate and comprehensive to improve the reliability of the model, regularly updates the system model, incorporates the latest operating data and technological advances, establishes a flexible control mechanism, can dynamically adjust the reactive power output according to real-time data and scenario changes, monitors the control strategy in real time to ensure that it adapts to load changes and external environment, establishes user feedback channels, understands user needs and opinions on power quality, combines user feedback with system feedback, optimizes technical solutions, improves user satisfaction, actively explores the application of new technologies (such as smart grids, the Internet of Things, etc.) in reactive voltage control to enhance the intelligence level of the system, combines energy storage systems to improve the flexibility and responsiveness of the system, formulates emergency plans to quickly respond to emergencies such as equipment failures and network anomalies, conducts regular drills and evaluations to ensure the stability and safety of the system in emergency situations, conducts a comprehensive analysis of the implementation cost and expected benefits of the optimization plan, evaluates the return on investment of reactive compensation equipment, and ensures maximum economic benefits.

[0013] Compared with the prior art, the present invention has the following beneficial effects: 1. Demand analysis and data collection of the network reactive power voltage control optimization method are necessary steps to ensure the safe and economical operation of the power system. Through comprehensive demand analysis, reasonable collection and processing of relevant data, it can provide strong support for the optimization of reactive power voltage control and help achieve the robustness and economy of the power system; Furthermore, by fully analyzing the load characteristics, power flow and dynamic conditions of the power grid, as well as considering economics and technical specifications, it is possible to reasonably determine the appropriate reactive power compensation equipment and optimize its configuration. This can effectively improve the stability and economy of the power system and meet the needs of various reactive power. Furthermore, the application of optimization algorithms in reactive power voltage control of power grids can greatly improve the efficiency and accuracy of control. By selecting appropriate optimization algorithms and reasonable application processes, the power grid system can achieve better voltage control effects and ensure the economy and stability of the system. In addition, with the development of new technologies, optimization algorithms combining machine learning and artificial intelligence have gradually been introduced into this field to further improve optimization capabilities and real-time performance. 2. The application of optimization algorithms in reactive power voltage control of power grids can greatly improve the efficiency and accuracy of control. By selecting appropriate optimization algorithms and reasonable application processes, the power grid system can achieve better voltage control effects and ensure the economy and stability of the system. In addition, with the development of new technologies, optimization algorithms combining machine learning and artificial intelligence have gradually been introduced into this field to further improve optimization capabilities and real-time performance; Furthermore, calculation and simulation are indispensable links in the optimization of reactive power and voltage control in power grids. Through system modeling, appropriate algorithm selection and application, and effective use of simulation tools, the effectiveness of reactive power and voltage control strategies can be comprehensively evaluated, providing safe and economical operation solutions for power systems; Furthermore, the implementation and adjustment of grid reactive power and voltage control optimization is a dynamic process, which requires adaptive adjustment based on real-time monitoring to cope with the ever-changing grid conditions. Through effective monitoring and data analysis, combined with flexible control measures, the economy and stability of grid operation can be ensured, providing users with high-quality power services. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] Figure 1 It is a schematic diagram of the overall process structure of the present invention; Figure 2 This is a schematic diagram of the pretreatment process structure of the present invention; Figure 3 This is a schematic diagram of the structure of the operation implementation process of the present invention; Figure 4 It is a schematic diagram of the effect evaluation, reporting and optimization process structure of the present invention. DETAILED DESCRIPTION

[0015] The following will be combined with the drawings in the embodiments 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. Embodiment 1:

[0016] like Figure 1-Figure 4 The technical solution shown is to solve the problem of inconvenience in optimizing reactive power voltage control in the power grid; The specific steps include: S1. Demand Analysis and Data Collection Load characteristics analysis: Collect grid load change data, analyze historical load curves, load characteristics, and seasonal changes; Grid status monitoring: using sensors and monitoring equipment to collect status information of voltage, current, power factor, transformers and other equipment; S2. Establishing a power grid model Mathematical model of power grid: According to the topological structure and parameter characteristics of the power grid, the mathematical model of the power grid is established, including the equivalent models of various equipment; Reactive current distribution model: Analyze the reactive power demand of each node and its impact on voltage; S3. Determine reactive power compensation equipment Equipment selection: Select appropriate reactive power compensation devices (such as SVC, STATCOM, capacitor bank, synchronous motor, etc.) according to the characteristics of the power grid; Configuration scheme design: formulate a configuration scheme for reactive power compensation equipment, indicate potential imbalance between supply and demand, and lay out compensation equipment; S4. Application of optimization algorithm Select optimization method: Select appropriate optimization algorithm (such as genetic algorithm, particle swarm) according to the characteristics of the power grid. optimization, linear programming, etc.); Algorithm implementation: Use the selected method to calculate the model and find the best reactive power compensation solution to meet the voltage control requirements; S5. Computation and simulation Formulate strategy: formulate specific reactive power regulation strategy based on optimization results; Simulation test: Verify in a simulated environment to evaluate the effectiveness and robustness of the optimization scheme under different load conditions; S6. Implementation and Adjustment Implementation plan: gradually implement the reactive power compensation plan in the actual power grid according to the optimization results; Dynamic adjustment: After data monitoring, the compensation equipment is adjusted in real time to enter or leave the network to maintain the optimized voltage level; S7. Effect evaluation Monitoring results: After implementation, the operation status of the power grid is continuously monitored to observe voltage fluctuations and changes in reactive power; Feedback and iteration: Based on the feedback from the implementation results, we continuously iterate and improve, update strategies and models to form a closed-loop management; S8. Reporting and Optimization Result report: Form a comprehensive report on the optimization process and results, record the analysis, decision-making basis and implementation results; Experience summary: Summarize the experience gained during the optimization process and improve subsequent optimization strategies and methods.

[0017] Step S1, clean and pre-process the collected data to ensure the accuracy and consistency of the data, establish a power system model based on the collected data, analyze the reactive voltage control effect under different conditions through simulation, use a suitable optimization algorithm to optimize the reactive voltage control strategy, and explore the application of heuristic methods, genetic algorithms, etc. in this regard. Step S2, collect the operating data of the actual power grid, compare it with the model calculation results, so as to verify the accuracy of the model, perform flow calculation and dynamic simulation, and verify whether the performance of the model under different operating conditions is in line with the actual situation. Through sensitivity analysis, determine the degree of influence of model parameters on the results, and further optimize and adjust the model. Step S3, determine the optimal location of the reactive compensation equipment , to maximize its efficiency and effectiveness, usually near key nodes or load centers where voltage fluctuations are large. According to the flow calculation results and load characteristics, the capacity of each reactive compensation device is reasonably determined to ensure that it can meet the reactive power demand at peak load. The control strategy of the reactive compensation device is designed to ensure that it can respond quickly when load changes, faults or other situations occur. The reactive compensation equipment is installed according to the design plan and its compatibility with the existing power grid is ensured. A real-time monitoring system is established to monitor changes in grid voltage and reactive power, evaluate the performance of the reactive compensation equipment, and make adjustments based on the data. The working status of the reactive compensation equipment and the operation status of the power grid are regularly evaluated to ensure its stable and efficient operation.According to the changes in the power grid, the optimization plan is adjusted in time. Step S4, by using the optimization algorithm to control reactive voltage in a certain power grid case, the effectiveness and feasibility of the algorithm are evaluated to ensure that the voltage is within the specified range and the reactive loss is minimized. In modern power grids, it is often necessary to meet multiple goals at the same time (such as reducing costs and improving reliability). Improved multi-objective optimization algorithms (such as improved genetic algorithms) can guide decision makers to make balanced decisions. Step S5 ensures that the parameters and structure of the power grid model are accurate. The performance characteristics of all components should be based on actual data. For the optimization algorithm, the parameter settings should be reasonably tuned to avoid premature convergence or low computational efficiency. Perform multiple simulations to confirm the results. reliability, avoid fluctuations in results due to accidental factors, compare the optimization results with the actual operating data, continuously improve the control strategy, ensure its adaptability and performance, step S6, establish a comprehensive feedback mechanism to ensure that all departments and relevant personnel can obtain information on the operation status of the power grid and the effects of the optimization plan in a timely manner, when implementing the reactive power voltage control optimization plan, fully consider the impact on users, maintain the quality of power, carry out training for operators, improve their understanding of the optimization plan and on-site response capabilities, ensure the effective implementation of the optimization plan, pay attention to changes in the external environment and regulations, and ensure that the reactive power voltage control measures are consistent with relevant policies and environmental protection requirements, step S7, organize the evaluation results A report is prepared to describe the actual effects of the optimization method in voltage control, reducing reactive power loss, and improving system stability. Improvement measures and future development directions are proposed for the problems found. According to the evaluation results, the reactive voltage control strategy is adjusted to optimize the equipment configuration and operation mode. If the control effect is not good under specific conditions, targeted optimization or new control methods should be added. Step S8 ensures that the input data used is accurate and comprehensive to improve the reliability of the model. The system model is updated regularly to incorporate the latest operating data and technological advances. A flexible control mechanism is established to dynamically adjust the reactive power output according to real-time data and scenario changes. The control strategy is monitored in real time to ensure its Adapt to load changes and external environment, establish user feedback channels, understand users' needs and opinions on power quality, combine user feedback with system feedback, optimize technical solutions, improve user satisfaction, and actively explore the application of new technologies (such as smart grids, the Internet of Things, etc.) in reactive power and voltage control to enhance the intelligence level of the system. Combined with energy storage systems, improve the flexibility and responsiveness of the system, formulate emergency plans to quickly respond to emergencies such as equipment failures and network anomalies, conduct regular drills and evaluations to ensure the stability and safety of the system in emergency situations, conduct a comprehensive analysis of the implementation cost and expected benefits of the optimization plan, evaluate the return on investment of reactive power compensation equipment, and ensure maximum economic benefits. In the embodiment, the demand analysis and data collection of the network reactive voltage control optimization method are necessary steps to ensure the safe and economic operation of the power system. Through comprehensive demand analysis, reasonable collection and processing of relevant data, it is possible to provide strong support for the optimization of reactive voltage control, help achieve the robustness and economy of the power system, and by fully analyzing the load characteristics, power flow and dynamic conditions of the power grid, and considering the economy and technical specifications, it is possible to reasonably determine the appropriate reactive compensation equipment and optimize its configuration scheme. In this way, the stability and economy of the power system can be effectively improved, and the needs of various types of reactive power can be met. The application of the optimization algorithm in the reactive voltage control of the power grid can greatly improve the efficiency and accuracy of the control. By selecting a suitable optimization algorithm and a reasonable application process, the power grid system can achieve a better voltage control effect and ensure the economy and stability of the system. In addition, with the development of new technologies, the optimization algorithm combined with machine learning and artificial intelligence has also been gradually introduced into this field to further improve the optimization capability and real-time performance. The application of the optimization algorithm in the reactive voltage control of the power grid can greatly improve the efficiency and accuracy of the control. By selecting a suitable optimization algorithm and a reasonable application process, the power grid system can achieve a better voltage control effect and ensure the economy and stability of the system. In addition, with the development of new technologies, optimization algorithms combining machine learning and artificial intelligence have gradually been introduced into this field to further improve optimization capabilities and real-time performance. Calculation and simulation are indispensable links in the optimization of reactive power voltage control in power grids. Through system modeling, appropriate algorithm selection and application, and effective use of simulation tools, the effectiveness of reactive power voltage control strategies can be comprehensively evaluated to provide safe and economical operation plans for power systems. The implementation and adjustment of reactive power voltage control optimization in power grids is a dynamic process that requires adaptive adjustments based on real-time monitoring to cope with changing grid conditions. Through effective monitoring and data analysis, combined with flexible control measures, the economy and stability of power grid operation can be ensured, providing users with high-quality power services; 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 method for optimizing reactive power voltage control of a power grid, comprising S1, demand analysis and data collection; S2, establishing a power grid model; S3, determining reactive power compensation equipment; S4, application of optimization algorithm; S5, calculation and simulation; S6, implementation and adjustment; S7, effect evaluation; S8, reporting and optimization; It is characterized in that The specific steps include: S1. Demand Analysis and Data Collection Load characteristics analysis: Collect grid load change data, analyze historical load curves, load characteristics, and seasonal changes; Grid status monitoring: using sensors and monitoring equipment to collect status information of voltage, current, power factor, transformers and other equipment; S2. Establishing a power grid model Mathematical model of power grid: According to the topological structure and parameter characteristics of the power grid, the mathematical model of the power grid is established, including the equivalent models of various equipment; Reactive current distribution model: Analyze the reactive power demand of each node and its impact on voltage; S3. Determine reactive power compensation equipment Equipment selection: Select appropriate reactive power compensation devices (such as SVC, STATCOM, capacitor bank, synchronous motor, etc.) according to the characteristics of the power grid; Configuration scheme design: formulate a configuration scheme for reactive power compensation equipment, indicate potential imbalance between supply and demand, and lay out compensation equipment; S4. Application of optimization algorithm Select optimization method: Select appropriate optimization algorithm (such as genetic algorithm, particle swarm) according to the characteristics of the power grid. optimization, linear programming, etc.); Algorithm implementation: Use the selected method to calculate the model and find the best reactive power compensation solution to meet the voltage control requirements; S5. Computation and simulation Formulate strategy: formulate specific reactive power regulation strategy based on optimization results; Simulation test: Verify in a simulated environment to evaluate the effectiveness and robustness of the optimization scheme under different load conditions; S6. Implementation and Adjustment Implementation plan: gradually implement the reactive power compensation plan in the actual power grid according to the optimization results; Dynamic adjustment: After data monitoring, the compensation equipment is adjusted in real time to enter or leave the network to maintain the optimized voltage level; S7. Effect evaluation Monitoring results: After implementation, the operation status of the power grid is continuously monitored to observe voltage fluctuations and changes in reactive power; Feedback and iteration: Based on the feedback from the implementation results, we continuously iterate and improve, update strategies and models to form a closed-loop management; S8. Reporting and Optimization Result report: Form a comprehensive report on the optimization process and results, record the analysis, decision-making basis and implementation results; Experience summary: Summarize the experience gained during the optimization process and improve subsequent optimization strategies and methods.

2. A method for optimizing reactive power voltage control of a power grid according to claim 1, characterized in that: In step S1, the collected data is cleaned and preprocessed to ensure the accuracy and consistency of the data, a power system model is established based on the collected data, the reactive voltage control effect under different conditions is simulated and analyzed, a suitable optimization algorithm is used to optimize the reactive voltage control strategy, and the application of heuristic methods, genetic algorithms, etc. in this regard is explored.

3. A method for optimizing reactive power voltage control of a power grid according to claim 1, characterized in that: In step S2, the operating data of the actual power grid is collected and compared with the model calculation results to verify the accuracy of the model, and power flow calculation and dynamic simulation are performed to verify whether the performance of the model under different operating conditions is consistent with the actual situation. Through sensitivity analysis, the influence of model parameters on the results is determined to further optimize and adjust the model.

4. A method for optimizing reactive power voltage control of a power grid according to claim 1, characterized in that: The step S3 is to determine the best location of the reactive compensation equipment to maximize its efficiency and effect, usually near the key node or load center where the voltage fluctuation is large. According to the flow calculation results and load characteristics, the capacity of each reactive compensation equipment is reasonably determined to ensure that it can meet the reactive power demand at peak load, design the control strategy of the reactive compensation equipment to ensure that it can respond quickly when the load changes, faults or other situations occur, install the reactive compensation equipment according to the design plan, and ensure compatibility with the existing power grid, establish a real-time monitoring system to monitor the changes in grid voltage and reactive power, evaluate the performance of the reactive compensation equipment, and adjust it according to the data, regularly evaluate the working status of the reactive compensation equipment and the operation status of the power grid to ensure its stable and efficient operation. According to the changes in the power grid, adjust the optimization plan in time.

5. A method for optimizing reactive power voltage control of a power grid according to claim 1, characterized in that: In step S4, reactive voltage control is performed in a certain power grid case by using an optimization algorithm to evaluate the effectiveness and feasibility of the algorithm, ensure that the voltage is within a specified range, and that reactive loss is minimized. In modern power grids, it is often necessary to meet multiple goals at the same time (such as reducing costs and improving reliability). An improved multi-objective optimization algorithm (such as an improved genetic algorithm) can help decision makers make balanced decisions.

6. A method for optimizing reactive power voltage control of a power grid according to claim 1, characterized in that: The step S5 ensures that the parameters and structure of the power grid model are accurate, the performance characteristics of all components should be based on actual data, and for the optimization algorithm, the parameter settings should be reasonably tuned to avoid premature convergence or low computational efficiency. Multiple simulations are performed to confirm the reliability of the results to avoid fluctuations in the results due to accidental factors. The optimization results are compared with the actual operating data, and the control strategy is continuously improved to ensure its adaptability and performance.

7. A method for optimizing reactive power voltage control in a power grid according to claim 1, characterized in that: The step S6 establishes a comprehensive feedback mechanism to ensure that various departments and relevant personnel can obtain information on the operation status of the power grid and the effects of the optimization plan in a timely manner. When implementing the reactive voltage control optimization plan, the impact on users must be fully considered to maintain the power quality, and training for operators must be carried out to improve their understanding of the optimization plan and their on-site response capabilities to ensure the effective implementation of the optimization plan. Attention must be paid to changes in the external environment and regulations to ensure that reactive voltage control measures are consistent with relevant policies and environmental protection requirements.

8. A method for optimizing reactive power voltage control in a power grid according to claim 1, characterized in that: In step S7, the evaluation results are compiled into a report to describe the actual effects of the optimization method in voltage control, reducing reactive power loss, improving system stability, etc., and to propose improvement measures and future development directions for the problems found. According to the evaluation results, the reactive power voltage control strategy is adjusted, and the equipment configuration and operation mode are optimized. If it is found that the control effect is not good under specific conditions, targeted optimization or new control means should be added.

9. A method for optimizing reactive power voltage control in a power grid according to claim 1, characterized in that: The step S8 ensures that the input data used is accurate and comprehensive to improve the reliability of the model, regularly updates the system model, incorporates the latest operating data and technological advances, establishes a flexible control mechanism, can dynamically adjust the reactive power output according to real-time data and scenario changes, monitors the control strategy in real time to ensure that it adapts to load changes and external environment, establishes user feedback channels, understands user needs and opinions on power quality, combines user feedback with system feedback, optimizes technical solutions, improves user satisfaction, actively explores the application of new technologies (such as smart grids, the Internet of Things, etc.) in reactive voltage control to enhance the intelligence level of the system, combines energy storage systems to improve the flexibility and responsiveness of the system, formulates emergency plans to quickly respond to emergencies such as equipment failures and network anomalies, conducts regular drills and evaluations to ensure the stability and safety of the system in emergency situations, conducts a comprehensive analysis of the implementation cost and expected benefits of the optimization plan, evaluates the return on investment of reactive compensation equipment, and ensures maximum economic benefits.

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