Electric evaluation system and monitoring method for booster station of wind power plant

Abstract

The invention discloses an electrical evaluation system and monitoring method for a booster station of a wind power plant. According to the invention, the optimization configuration module provides a strong decision support capability for the electric evaluation system of the booster station of the wind power plant through sub-modules of objective function construction, constraint condition setting, optimization algorithm engine, result output and the like in the optimization configuration module. Firstly, the objective function construction module can convert a complex optimization objective into a computable mathematical function according to user demands and preferences, multiple cost factors such as equipment purchase, installation, operation maintenance and the like are considered, and comprehensiveness and practicability of the optimization objective are ensured. The constraint condition setting module ensures the feasibility and rationality of an optimization result in practical application, and by setting constraint conditions such as power balance and equipment capacity limitation, an unpractical solution is avoided. And the optimization algorithm engine module performs iterative computation by using advanced algorithms such as a genetic algorithm and the like to find an optimal solution meeting conditions, so that the accuracy and the efficiency of decision making are improved.

Description

Technical Field

[0001] The present invention belongs to the technical field of wind farm booster station inspection, and specifically relates to an electrical evaluation system and monitoring method for a wind farm booster station. Background Art

[0002] The wind farm booster station is an indispensable part of the wind power generation system. Its main function is to increase the low-voltage electric energy generated by the wind turbine to a voltage level suitable for long-distance transmission through a transformer, so as to efficiently and stably transmit the electric energy to the power grid. The booster station is usually located in the central area of ​​the wind farm and consists of key equipment such as transformers, high-voltage switchgear, relay protection devices, and automatic control systems. With the transformation of the global energy structure and the rapid development of renewable energy, wind power generation, as an important form of clean energy, has seen its installed capacity and power generation increase year by year. As an important part of the wind power generation system, the wind farm booster station undertakes the key task of boosting the electric energy generated by the wind turbine and transmitting it to the power grid. However, the operating status, safety performance, and energy efficiency level of the electrical equipment of the wind farm booster station directly affect the power generation efficiency and economic benefits of the wind farm.

[0003] However, the current electrical evaluation of wind farm substations mainly relies on manual inspections and regular maintenance, which has many problems: first, manual inspections are inefficient, costly, and difficult to achieve real-time monitoring; second, regular maintenance is often based on experience or fixed cycles, lacks specificity and flexibility, and may lead to over-repair or under-repair of equipment, easily resulting in problems such as untimely fault warnings and inaccurate energy efficiency assessments. Summary of the invention

[0004] The purpose of the present invention is to provide an electrical evaluation system and monitoring method for a wind farm booster station in order to solve the above-mentioned problems.

[0005] The technical solution adopted by the present invention is as follows: an evaluation system for electrical equipment of a wind farm booster station, the system comprising: a data acquisition module, a data processing module, an analysis and evaluation module, an optimization configuration module, a report generation module, a user interface module and a system management module;

[0006] The optimization configuration module is internally provided with an objective function construction module, a constraint condition setting module, an optimization algorithm engine module and a result output module;

[0007] The data acquisition module collects the operating data of the electrical equipment of the wind farm booster station in real time, and sends the data to the data processing module through the data transmission subsystem;

[0008] The data processing module cleans, converts and synchronizes the data to ensure the quality and consistency of the data and provide a reliable data basis for the analysis and evaluation module;

[0009] The analysis and evaluation module uses the processed data to analyze and evaluate the equipment status, safety performance and energy efficiency, and generates evaluation results; these results are transmitted to the optimization configuration module;

[0010] The optimization configuration module proposes targeted optimization suggestions and decision support based on the evaluation results;

[0011] The results of the analysis and evaluation module and the optimization configuration module are sent to the report generation module to automatically generate a detailed evaluation report;

[0012] The user interface module serves as a window for users to interact with the system, displaying data, analysis results and reports, and receiving user operation instructions; the system management module runs through the entire system and is responsible for user management, system configuration and log management.

[0013] In a preferred embodiment, the data acquisition module is the core foundation of the electrical evaluation system of the wind farm booster station, and is responsible for real-time and accurate collection of operating data of various electrical equipment in the booster station; the data acquisition module includes a variety of sensors, among which: the current sensor is used to monitor the current size and fluctuation, the voltage sensor is used to measure the voltage value, and the temperature sensor is used to detect the temperature of the equipment; in addition, it also includes a wind speed sensor and a power sensor to fully obtain the operating status of the wind farm; the data acquisition module transmits the data collected by the sensor to the data processing module in real time through wired or wireless communication to ensure the timeliness and accuracy of the data;

[0014] The data processing module is responsible for processing the raw data transmitted by the data acquisition module, including data cleaning, data conversion and data synchronization operations.

[0015] In a preferred embodiment, the analysis and evaluation module performs an in-depth analysis on the processed data to evaluate the status, safety performance and energy efficiency of the electrical equipment in the substation; a variety of analysis methods and algorithms are used, including status monitoring, fault diagnosis, and energy efficiency analysis; the operating status of the main transformer of the substation is monitored in real time through the status monitoring algorithm, and an early warning is immediately issued once an abnormality is found; the fault diagnosis algorithm is used to analyze the cause and location of the equipment failure and provide maintenance suggestions; the energy efficiency analysis evaluates the energy utilization efficiency of the substation and puts forward optimization suggestions; the results generated by the analysis and evaluation module are not only used to guide the operation and maintenance of the wind farm, but also provide decision support for the optimization configuration module.

[0016] In a preferred embodiment, the objective function construction submodule first receives the optimization objectives input by the user according to the specific needs and preferences of the user, and then converts these objectives into computable mathematical functions; in this process, the module will consider various cost factors, including equipment purchase costs, installation costs, and operation and maintenance costs, and combine them in appropriate mathematical forms; finally, the constructed objective function will be used as the input of the optimization algorithm to guide the algorithm to find the best solution that meets the conditions;

[0017] The objective function formula is calculated by minimizing the total cost algorithm:

[0018] minC=C_wind+C_storage+C_operation;

[0019] Among them, C_wind is the cost of wind power generation, C_storage is the cost of energy storage system, and C_operation is the operation and maintenance cost.

[0020] In a preferred embodiment, the constraint setting submodule is responsible for defining the constraints that must be followed in the optimization problem to ensure the feasibility and rationality of the optimization results in practical applications; allowing users to set a series of constraints according to actual needs and system limitations, including power balance constraints, equipment capacity limitations, and reliability requirements; the module converts these constraints into mathematical expressions, and together with the objective function, constitutes a complete mathematical model of the optimization problem;

[0021] The power balance constraint calculation formula is:

[0022] P_wind+P_storage-P_load=0;

[0023] Among them, P_wind is the wind power generation power, P_storage is the charging and discharging power of the energy storage system, where discharge is positive and charging is negative, and P_load is the load power.

[0024] In a preferred embodiment, the optimization algorithm engine submodule uses the GA genetic algorithm to perform iterative calculations according to the objective function and constraints. The module initializes a population, representing the solution, and then continuously evolves the population through selection, crossover and mutation operations until an optimal solution or a near-optimal solution that meets the termination condition is found; in this process, the module evaluates the fitness of each solution, that is, the value of the objective function, and guides the search direction of the algorithm according to the fitness; finally, the algorithm outputs the optimal solution or a set of excellent solutions for use by subsequent modules;

[0025] The algorithm flow is:

[0026] S1. Initialize the population: randomly generate a certain number of initial solutions (individuals), each of which represents a wind-solar-storage-load configuration scheme;

[0027] S2. Selection: According to the fitness value of individuals, select excellent individuals to enter the next generation; use roulette selection and tournament selection methods;

[0028] S3. Crossover: Pair the selected individuals and generate new individuals through crossover operation to achieve gene recombination and information exchange;

[0029] S4. Mutation: Randomly change certain genes of new individuals to increase the diversity of the population and avoid falling into local optimality;

[0030] S5. Fitness evaluation: Calculate the fitness value of each individual and evaluate its quality; the fitness function is associated with the objective function;

[0031] S6. Termination judgment: Check whether the termination condition is met; if so, output the optimal solution; otherwise, return to step 2 to continue iteration;

[0032] The fitness function formula is:

[0033] Where F(x) is the fitness value of individual x; C(x) is the objective function value corresponding to individual x, that is, the total cost; ∈ is a very small positive number used to avoid the situation where the denominator is zero.

[0034] In a preferred embodiment, the result output and interpretation submodule presents the results of the electrical optimization algorithm of the wind farm substation to the user in an intuitive and easy-to-understand manner, and provides necessary explanations and analyses; in terms of operation method, the module first receives the results output by the optimization algorithm engine, including the optimal solution vector and the objective function value, and then organizes these results into tables and charts and displays them to the user; at the same time, the module will explain the results, explaining how the optimal solution meets the constraints and optimization goals, as well as the specific meaning and influence of each parameter.

[0035] In a preferred embodiment, the report generation module is responsible for collating the results of the analysis and evaluation module and the optimization configuration module into a detailed electrical evaluation report for the wind farm substation; the module automatically collects analysis results, charts, and statistical data, and generates a report according to a predetermined format and template; the report content includes an overview of the equipment operation status, fault diagnosis results, energy efficiency analysis results, and optimization suggestions; the system generates a monthly evaluation report, which lists in detail the operation status of each device in the substation this month, the faults that occurred and their handling, and energy efficiency improvement suggestions, to help managers fully understand the operation status of the wind farm and formulate corresponding management and maintenance strategies;

[0036] The user interface module is a window for users to interact with the system. It is responsible for displaying data, analyzing results and reports, and receiving user operation instructions. The module is designed with an intuitive and friendly interface, allowing users to easily view real-time data, historical records, and alarm information. Users can view the current, voltage, and temperature data of the main transformer of the substation in real time through the interface. Once the system issues an early warning, the interface will immediately display the alarm information and prompt the cause of the fault. Users can also query historical data, generate reports, and set system parameters through the interface. The user interface module enables wind farm managers to easily and quickly obtain the required information and conduct effective management.

[0037] In a preferred embodiment, the system management module is responsible for the management and maintenance of the entire system to ensure the security, stability and maintainability of the system; the module includes user management, system configuration and log management functions; user management is used to add, delete and assign permissions to ensure that only authorized users can access the system; system configuration is used to set system parameters and sensor thresholds to adapt to different operating requirements; log management records the system's operation log and alarm log for subsequent query and analysis; system administrators add new users through the system management module and set their access rights to ensure the security of system data; in addition, administrators also adjust the alarm thresholds of sensors as needed to enable the system to more accurately reflect the operating status of the equipment; the system management module provides powerful background support for the electrical evaluation system of the wind farm substation to ensure the long-term stable operation of the system.

[0038] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0039] 1. In the present invention, the optimization configuration module provides a powerful decision support capability for the electrical evaluation system of the wind farm booster station through its internal submodules such as objective function construction, constraint setting, optimization algorithm engine and result output. First, the objective function construction module can convert complex optimization objectives into computable mathematical functions according to user needs and preferences, taking into account multiple cost factors such as equipment purchase, installation, operation and maintenance, and ensuring the comprehensiveness and practicality of the optimization objectives. The constraint setting module ensures the feasibility and rationality of the optimization results in practical applications, and avoids unrealistic solutions by setting constraints such as power balance and equipment capacity limitations. The optimization algorithm engine module uses advanced algorithms such as genetic algorithms for iterative calculations to find the best solution that meets the conditions, greatly improving the accuracy and efficiency of decision-making. The result output and interpretation submodule presents the optimization results in an intuitive and easy-to-understand manner, and provides detailed explanations, so that wind farm managers can easily understand and adopt optimization suggestions. This helps to minimize operating costs and maximize energy efficiency, thereby improving the overall operating efficiency of wind farms.

[0040] 2. In the present invention, the data processing module cleans, converts and synchronizes the data, improves the data quality, and provides consistent and comparable data support for analysis and evaluation. The analysis and evaluation module uses advanced analysis methods and algorithms to conduct in-depth analysis of equipment status, safety performance and energy efficiency, providing wind farm managers with comprehensive equipment operation insights and early warnings, which helps prevent failures and improve equipment utilization. The report generation module automatically organizes the analysis results and generates detailed evaluation reports, which simplifies the information aggregation and report preparation process, allowing managers to quickly obtain key information and formulate effective strategies. The user interface module provides an intuitive and friendly interactive interface, allowing users to easily view data, results and reports, improving the system's ease of use and user experience. The system management module is responsible for user management, system configuration and log management, ensuring the security, stability and maintainability of the system, and providing a solid guarantee for the long-term operation of the system. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 is the overall system block diagram of the present invention;

[0042] Figure 2 This is a system block diagram of the optimized configuration module in the present invention. DETAILED DESCRIPTION

[0043] In order to make the purpose, technical solution and advantages of the present invention more clearly understood, the present invention is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0044] Reference Figures 1-2 ,

[0045] Example:

[0046] An electrical evaluation system for a wind farm booster station, the system comprising: a data acquisition module, a data processing module, an analysis and evaluation module, an optimization configuration module, a report generation module, a user interface module and a system management module;

[0047] The optimization configuration module is internally provided with an objective function construction module, a constraint condition setting module, an optimization algorithm engine module and a result output module;

[0048] The data acquisition module collects the operating data of the electrical equipment in the wind farm booster station in real time, and sends the data to the data processing module through the data transmission subsystem.

[0049] The data processing module cleans, converts and synchronizes the data to ensure the quality and consistency of the data, providing a reliable data foundation for the analysis and evaluation module.

[0050] The analysis and evaluation module uses the processed data to analyze and evaluate the equipment status, safety performance and energy efficiency, and generates evaluation results. These results are transmitted to the optimization configuration module;

[0051] The optimization configuration module provides targeted optimization suggestions and decision support based on the evaluation results.

[0052] The results of the analysis and evaluation module and the optimization configuration module are sent to the report generation module to automatically generate a detailed evaluation report.

[0053] The user interface module is a window for users to interact with the system, displaying data, analysis results and reports, and receiving user operation instructions. The system management module runs through the entire system and is responsible for user management, system configuration and log management.

[0054] The data acquisition module is the core foundation of the electrical evaluation system of the wind farm substation, and is responsible for real-time and accurate collection of operating data of various electrical equipment in the substation. Specifically, the module includes a variety of sensors, such as current sensors for monitoring current size and fluctuations, voltage sensors for measuring voltage values, and temperature sensors for detecting equipment temperature. In addition, it may also include wind speed sensors, power sensors, etc. to fully obtain the operating status of the wind farm. The data acquisition module transmits the data collected by the sensor to the data processing module in real time through wired or wireless communication to ensure the timeliness and accuracy of the data. The current sensor can monitor the current changes of the main transformer of the substation in real time. Once an abnormal fluctuation is found, the data will be immediately transmitted to the subsequent modules for analysis and processing.

[0055] The data processing module is responsible for processing the raw data transmitted by the data acquisition module, including data cleaning, data conversion and data synchronization. Data cleaning mainly removes noise, fills missing values ​​and corrects erroneous data to ensure data quality. Data conversion converts data collected by different sensors into a unified format for subsequent analysis. Data synchronization ensures the temporal consistency of data from different data sources. When the system receives data from current sensors and temperature sensors, the data processing module will first clean the data to remove abnormal values ​​caused by sensor failure or transmission errors, and then convert the current and temperature data into a unified numerical format, and ensure the temporal correspondence between the two types of data, providing an accurate and consistent data basis for the analysis and evaluation module.

[0056] The analysis and evaluation module is the core analysis unit of the system, responsible for in-depth analysis of the processed data and evaluating the status, safety performance and energy efficiency of the electrical equipment in the booster station. This module uses a variety of analysis methods and algorithms, such as status monitoring, fault diagnosis, and energy efficiency analysis. Through the status monitoring algorithm, the operating status of the main transformer of the booster station is monitored in real time, and an early warning is issued immediately once an abnormality is found. The fault diagnosis algorithm is used to analyze the cause and location of equipment failure and provide maintenance suggestions. The energy efficiency analysis evaluates the energy utilization efficiency of the booster station and puts forward optimization suggestions. The results generated by the analysis and evaluation module are not only used to guide the operation and maintenance of the wind farm, but also provide decision support for the optimization configuration module.

[0057] The objective function construction submodule first receives the optimization objectives input by the user according to the user's specific needs and preferences, and then converts these objectives into computable mathematical functions. In this process, the module will consider various cost factors, including equipment purchase costs, installation costs, and operation and maintenance costs, and combine them in an appropriate mathematical form. Finally, the constructed objective function will serve as the input of the optimization algorithm to guide the algorithm to find the best solution that meets the conditions.

[0058] The objective function formula is calculated by minimizing the total cost algorithm:

[0059] minC=C_wind+C_storage+C_operation

[0060] Among them, C_wind is the cost of wind power generation, C_storage is the cost of energy storage system, and C_operation is the operation and maintenance cost.

[0061] The constraint setting submodule is responsible for defining the constraints that must be followed in the optimization problem to ensure the feasibility and rationality of the optimization results in practical applications. It allows users to set a series of constraints, including power balance constraints, equipment capacity constraints, and reliability requirements, based on actual needs and system limitations. The module converts these constraints into mathematical expressions, which together with the objective function form a complete mathematical model of the optimization problem.

[0062] The power balance constraint calculation formula is:

[0063] P_wind+P_storage-P_load=0

[0064] Among them, P_wind is the wind power generation power, P_storage is the charging and discharging power of the energy storage system, where discharge is positive and charging is negative, and P_load is the load power.

[0065] The optimization algorithm engine submodule uses the GA genetic algorithm to perform iterative calculations based on the objective function and constraints. The module will initialize a population to represent possible solutions, and then continuously evolve the population through selection, crossover, and mutation operations until the optimal solution or approximate optimal solution that meets the termination conditions is found. In this process, the module will evaluate the fitness of each solution, that is, the value of the objective function, and guide the algorithm's search direction based on the fitness. Finally, the algorithm will output the optimal solution or a set of excellent solutions for use by subsequent modules.

[0066] The algorithm flow is:

[0067] S1. Initialize the population: randomly generate a certain number of initial solutions (individuals), each of which represents a possible wind-solar-storage-load configuration scheme;

[0068] S2. Selection: According to the fitness value of individuals, excellent individuals are selected to enter the next generation; roulette wheel selection and tournament selection methods are usually used;

[0069] S3. Crossover: Pair the selected individuals and generate new individuals through crossover operation to achieve gene recombination and information exchange;

[0070] S4. Mutation: Randomly change certain genes of new individuals to increase the diversity of the population and avoid falling into local optimality;

[0071] S5. Fitness evaluation: Calculate the fitness value of each individual and evaluate its quality; the fitness function is usually associated with the objective function;

[0072] S6. Termination judgment: Check whether the termination condition is met; if so, output the optimal solution; otherwise, return to step 2 to continue iteration;

[0073] The fitness function formula is:

[0074] Where F(x) is the fitness value of individual x; C(x) is the objective function value corresponding to individual x, that is, the total cost; ∈ is a very small positive number used to avoid the situation where the denominator is zero.

[0075] The result output and interpretation submodule presents the results of the electrical optimization algorithm of the wind farm substation to the user in an intuitive and easy-to-understand manner, and provides necessary explanations and analyses; in terms of operation method, the module first receives the results output by the optimization algorithm engine, including the optimal solution vector and the objective function value, and then organizes these results into tables and charts for display to the user; at the same time, the module will explain the results, explaining how the optimal solution meets the constraints and optimization goals, as well as the specific meaning and influence of each parameter.

[0076] The report generation module is responsible for collating the results of the analysis and evaluation module and the optimization configuration module into a detailed electrical evaluation report for the wind farm booster station. This module automatically collects analysis results, charts, statistical data, etc., and generates reports according to the predetermined format and template. The report content may include an overview of the equipment operating status, fault diagnosis results, energy efficiency analysis results, optimization suggestions, etc. The system can generate a monthly evaluation report that lists in detail the operating status of each device in the booster station this month, the faults that occurred and how they were handled, energy efficiency improvement suggestions, etc., to help managers fully understand the operating status of the wind farm and formulate corresponding management and maintenance strategies.

[0077] The user interface module is a window for users to interact with the system. It is responsible for displaying data, analyzing results and reports, and receiving user operation instructions. The module is designed with an intuitive and friendly interface, allowing users to easily view real-time data, historical records, alarm information, etc. Users can view the current, voltage and temperature data of the main transformer of the booster station in real time through the interface. Once the system issues an early warning, the interface will immediately display the alarm information and prompt the possible cause of the fault. Users can also query historical data, generate reports, set system parameters, etc. through the interface. The user interface module enables wind farm managers to easily and quickly obtain the required information and conduct effective management.

[0078] The system management module is responsible for the management and maintenance of the entire system, ensuring the security, stability and maintainability of the system. This module includes functions such as user management, system configuration and log management. User management is used to add, delete and assign permissions to ensure that only authorized users can access the system. System configuration is used to set system parameters, sensor thresholds, etc. to meet different operating requirements. Log management records the system's operation logs, alarm logs, etc. for subsequent query and analysis. System administrators can add new users and set their access rights through the system management module to ensure the security of system data. In addition, administrators can also adjust the alarm threshold of sensors as needed so that the system can more accurately reflect the operating status of the equipment. The system management module provides powerful background support for the electrical evaluation system of the wind farm booster station, ensuring the long-term stable operation of the system.

[0079] When the monitoring method is executed, the electrical evaluation system for a wind farm booster station according to the above embodiment is run.

[0080] In the present invention, the optimization configuration module provides a powerful decision support capability for the electrical evaluation system of the wind farm booster station through its internal submodules such as objective function construction, constraint setting, optimization algorithm engine and result output. First, the objective function construction module can convert complex optimization objectives into computable mathematical functions according to user needs and preferences, taking into account multiple cost factors such as equipment purchase, installation, operation and maintenance, and ensuring the comprehensiveness and practicality of the optimization objectives. The constraint setting module ensures the feasibility and rationality of the optimization results in practical applications, and avoids unrealistic solutions by setting constraints such as power balance and equipment capacity limitations. The optimization algorithm engine module uses advanced algorithms such as genetic algorithms for iterative calculations to find the best solution that meets the conditions, greatly improving the accuracy and efficiency of decision-making. The result output and interpretation submodule presents the optimization results in an intuitive and easy-to-understand manner, and provides detailed explanations, so that wind farm managers can easily understand and adopt optimization suggestions. This helps to minimize operating costs and maximize energy efficiency, thereby improving the overall operating efficiency of wind farms.

[0081] In the present invention, the data processing module cleans, converts and synchronizes the data, improves the data quality, and provides consistent and comparable data support for analysis and evaluation. The analysis and evaluation module uses advanced analysis methods and algorithms to conduct in-depth analysis of equipment status, safety performance and energy efficiency, providing wind farm managers with comprehensive equipment operation insights and early warnings, which helps prevent failures and improve equipment utilization. The report generation module automatically organizes the analysis results and generates detailed evaluation reports, which simplifies the information aggregation and report preparation process, allowing managers to quickly obtain key information and formulate effective strategies. The user interface module provides an intuitive and friendly interactive interface, allowing users to easily view data, results and reports, improving the system's ease of use and user experience. The system management module is responsible for user management, system configuration and log management, ensuring the security, stability and maintainability of the system, and providing a solid guarantee for the long-term operation of the system.

[0082] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the term "comprises" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device. In the absence of further restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, article or device including the elements.

[0083] The above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An electrical evaluation system for a wind farm booster station, characterized in that: The system includes: a data acquisition module, a data processing module, an analysis and evaluation module, an optimization configuration module, a report generation module, a user interface module and a system management module; The optimization configuration module is internally provided with an objective function construction module, a constraint condition setting module, an optimization algorithm engine module and a result output module; The data acquisition module collects the operating data of the electrical equipment of the wind farm booster station in real time, and sends the data to the data processing module through the data transmission subsystem; The data processing module cleans, converts and synchronizes the data to ensure the quality and consistency of the data and provide a reliable data basis for the analysis and evaluation module; The analysis and evaluation module uses the processed data to analyze and evaluate the equipment status, safety performance and energy efficiency, and generates evaluation results; these results are transmitted to the optimization configuration module; The optimization configuration module proposes targeted optimization suggestions and decision support based on the evaluation results; The results of the analysis and evaluation module and the optimization configuration module are sent to the report generation module to automatically generate a detailed evaluation report; The user interface module serves as a window for users to interact with the system, displaying data, analysis results and reports, and receiving user operation instructions; the system management module runs through the entire system and is responsible for user management, system configuration and log management.

2. The wind farm booster station electrical evaluation system according to claim 1, characterized in that: The data acquisition module is the core foundation of the electrical evaluation system of the wind farm booster station, and is responsible for real-time and accurate collection of operating data of various electrical equipment in the booster station; the data acquisition module includes a variety of sensors, among which: the current sensor is used to monitor the current size and fluctuation, the voltage sensor is used to measure the voltage value, and the temperature sensor is used to detect the temperature of the equipment; in addition, it also includes a wind speed sensor and a power sensor to fully obtain the operating status of the wind farm; the data acquisition module transmits the data collected by the sensor to the data processing module in real time through wired or wireless communication to ensure the timeliness and accuracy of the data; The data processing module is responsible for processing the raw data transmitted by the data acquisition module, including data cleaning, data conversion and data synchronization operations.

3. The wind farm booster station electrical evaluation system according to claim 1, characterized in that: The analysis and evaluation module conducts in-depth analysis on the processed data to evaluate the status, safety performance and energy efficiency of the electrical equipment in the substation; it adopts a variety of analysis methods and algorithms, including status monitoring, fault diagnosis, and energy efficiency analysis; through the status monitoring algorithm, the operating status of the main transformer of the substation is monitored in real time, and once an abnormality is found, an early warning is immediately issued; the fault diagnosis algorithm is used to analyze the cause and location of equipment failure and provide maintenance suggestions; the energy efficiency analysis evaluates the energy utilization efficiency of the substation and puts forward optimization suggestions; the results generated by the analysis and evaluation module are not only used to guide the operation and maintenance of the wind farm, but also provide decision support for the optimization configuration module.

4. The wind farm booster station electrical evaluation system according to claim 1, characterized in that: The objective function construction submodule first receives the optimization objectives input by the user according to the specific needs and preferences of the user, and then converts these objectives into computable mathematical functions; in this process, the module will consider various cost factors, including equipment purchase costs, installation costs, and operation and maintenance costs, and combine them in appropriate mathematical forms; finally, the constructed objective function will serve as the input of the optimization algorithm to guide the algorithm to find the best solution that meets the conditions; The objective function formula is calculated by minimizing the total cost algorithm: minC=C_wind+C_storage+C_operation; Among them, C_wind is the cost of wind power generation, C_storage is the cost of energy storage system, and C_operation is the operation and maintenance cost.

5. The wind farm booster station electrical evaluation system according to claim 1, characterized in that: The constraint setting submodule is responsible for defining the constraints that must be followed in the optimization problem to ensure the feasibility and rationality of the optimization results in practical applications; it allows users to set a series of constraints according to actual needs and system limitations, including power balance constraints, equipment capacity limitations, and reliability requirements; the module converts these constraints into mathematical expressions, and together with the objective function, it constitutes a complete mathematical model of the optimization problem; The power balance constraint calculation formula is: P_wind+P_storage-P_load=0; Among them, P_wind is the wind power generation power, P_storage is the charging and discharging power of the energy storage system, where discharge is positive and charging is negative, and P_load is the load power.

6. The wind farm booster station electrical evaluation system according to claim 1, characterized in that: The optimization algorithm engine submodule uses the GA genetic algorithm to perform iterative calculations according to the objective function and constraints. The module will initialize a population, representing the solution, and then continuously evolve the population through selection, crossover and mutation operations until the optimal solution or approximate optimal solution that meets the termination conditions is found; in this process, the module will evaluate the fitness of each solution, that is, the value of the objective function, and guide the search direction of the algorithm according to the fitness; finally, the algorithm will output the optimal solution or a set of excellent solutions for use by subsequent modules; The algorithm flow is: S1. Initialize the population: randomly generate a certain number of initial solutions (individuals), each of which represents a wind-solar-storage-load configuration scheme; S2. Selection: According to the fitness value of individuals, select excellent individuals to enter the next generation; use roulette selection and tournament selection methods; S3. Crossover: Pair the selected individuals and generate new individuals through crossover operation to achieve gene recombination and information exchange; S4. Mutation: Randomly change certain genes of new individuals to increase the diversity of the population and avoid falling into local optimality; S5. Fitness evaluation: calculate the fitness value of each individual and evaluate its quality; The fitness function is associated with the objective function; S6. Termination judgment: Check whether the termination condition is met; if so, output the optimal solution; Otherwise, return to step 2 and continue iterating; The fitness function formula is: Where F(x) is the fitness value of individual x; C(x) is the objective function value corresponding to individual x, that is, the total cost; ∈ is a very small positive number used to avoid the situation where the denominator is zero.

7. The wind farm booster station electrical evaluation system according to claim 1, characterized in that: The result output and interpretation submodule presents the results of the electrical optimization algorithm of the wind farm substation to the user in an intuitive and easy-to-understand manner, and provides necessary explanations and analyses; in terms of operation method, the module first receives the results output by the optimization algorithm engine, including the optimal solution vector and the objective function value, and then organizes these results into tables and charts for display to the user; at the same time, the module will explain the results, explaining how the optimal solution meets the constraints and optimization goals, as well as the specific meaning and influence of each parameter.

8. The wind farm booster station electrical evaluation system according to claim 1, characterized in that: The report generation module is responsible for collating the results of the analysis and evaluation module and the optimization configuration module into a detailed wind farm booster station electrical evaluation report; the module automatically collects analysis results, charts, and statistical data, and generates a report according to a predetermined format and template; The report includes an overview of equipment operating status, fault diagnosis results, energy efficiency analysis results, and optimization suggestions; The system generates a monthly evaluation report that lists in detail the operation status of each device in the booster station, the faults that occurred and how they were handled, and suggestions for energy efficiency improvement, helping managers to fully understand the operation status of the wind farm and formulate corresponding management and maintenance strategies; The user interface module is a window for users to interact with the system, responsible for displaying data, analysis results and reports, and receiving user operation instructions; The module is designed with an intuitive and friendly interface, allowing users to easily view real-time data, historical records, and alarm information; Users can view the current, voltage and temperature data of the main transformer of the substation in real time through the interface. Once the system issues an early warning, the interface will immediately display the alarm information and indicate the cause of the fault. Users can also query historical data, generate reports and set system parameters through the interface. The user interface module enables wind farm managers to easily and quickly obtain the required information for effective management.

9. The wind farm booster station electrical evaluation system according to claim 1, characterized in that: The system management module is responsible for the management and maintenance of the entire system to ensure the security, stability and maintainability of the system; this module includes user management, system configuration and log management functions; user management is used to add, delete and assign permissions to ensure that only authorized users can access the system; system configuration is used to set system parameters and sensor thresholds to meet different operating requirements; Log management records the system's operation logs and alarm logs for subsequent query and analysis. System administrators add new users through the system management module and set their access rights to ensure the security of system data. In addition, administrators also adjust the alarm thresholds of sensors as needed so that the system can more accurately reflect the operating status of the equipment.

10. A monitoring method for an electrical evaluation system of a wind farm booster station as claimed in claim 1, characterized in that: When the monitoring method is executed, the wind farm booster station electrical evaluation system according to any one of claims 1 to 9 is run.

Images