A method and system for evaluating power generation performance of a wind farm

Abstract

The present invention discloses a method and system for evaluating the power generation performance of a wind farm, which relates to the technical field of power generation performance evaluation. Representative aerosol monitoring points of a wind farm are selected; based on the changes in aerosol collection data of each representative aerosol monitoring point and the changes in the corresponding wind farm power generation data, the changes are analyzed, and the degree of influence of the aerosol collection data of each representative aerosol monitoring point on the changes in the wind farm power generation data is respectively identified; the aerosol collection data of each representative aerosol monitoring point of the wind farm is monitored in real time, and then the aerosol collection data of each representative aerosol monitoring point is used to analyze the degree of influence of the changes in the wind farm power generation data, and the power generation performance of the wind farm is evaluated in real time. Through accurate monitoring and real-time analysis, it is helpful to improve the power generation performance of the wind farm, optimize the operation strategy, and improve the power generation efficiency.

Description

Technical Field

[0001] The present invention relates to the technical field of power generation performance evaluation, and in particular to a method and system for evaluating power generation performance of a wind farm. Background Art

[0002] As the global demand for renewable energy continues to grow, wind energy, as a clean and renewable form of energy, has received more and more attention. Wind farms, as an important part of wind energy utilization, have a direct impact on the conversion efficiency and economic benefits of wind energy.

[0003] However, traditional wind farm power generation performance evaluation methods ignore the potential impact of aerosols on wind farm power generation. Aerosols (such as dust and pollutants) will affect air quality, thereby affecting the efficiency of wind turbines. At the same time, existing methods do not fully consider the impact of sensor data acquisition capabilities and locations on data analysis. In addition, since there are many aerosol monitoring points and they are not concentrated, using aerosol data to evaluate power generation performance requires processing and analyzing a large amount of aerosol collection data and power generation data. The data processing efficiency is low, which in turn affects the efficiency and accuracy of power generation performance evaluation.

[0004] Therefore, in response to the above problems, a method and system for evaluating the power generation performance of a wind farm is urgently needed. Summary of the invention

[0005] In view of the shortcomings of the prior art, the present invention provides a method and system for evaluating the power generation performance of a wind farm, which solves the problem that the traditional wind farm power generation performance evaluation relies on macroscopic meteorological data or empirical models, ignores the specific impact of microscopic environmental factors such as aerosols on power generation performance, and that wind farms are usually large in area and have uneven aerosol distribution, making it unrealistic to directly evaluate the aerosol impact of the entire wind farm.

[0006] To achieve the above objectives, the present invention is implemented through the following technical solutions: a method for evaluating the power generation performance of a wind farm station, comprising the following steps: identifying aerosol sensors in the wind farm station, and then collecting power generation impact data of the locations of each aerosol sensor in the wind farm station; based on the data collection capabilities of each aerosol sensor in the wind farm station, analyzing the power generation impact data of the locations of each aerosol sensor in the wind farm station, and selecting representative aerosol monitoring points of the wind farm station; obtaining aerosol collection data and wind farm power generation data of representative aerosol monitoring points at each time point in the monitoring period; analyzing the changes in the aerosol collection data of each representative aerosol monitoring point and the corresponding changes in the power generation data of the wind farm station, respectively identifying the degree of influence of the aerosol collection data of each representative aerosol monitoring point on the changes in the power generation data of the wind farm station; real-time monitoring of the aerosol collection data of the representative aerosol monitoring points of the wind farm station, and then using the aerosol collection data of each representative aerosol monitoring point to analyze the degree of influence of the changes in the power generation data of the wind farm station, and real-time evaluation of the power generation performance of the wind farm station.

[0007] Furthermore, the power generation influencing data at the locations of the aerosol sensors of the wind farm station specifically include: aerosol concentration variation coefficient and wind speed frequency.

[0008] Furthermore, the specific analysis based on the consideration of the data collection capability of each aerosol sensor of the wind farm station is as follows: the wind farm station is divided into regions according to the working operation tasks of the wind farm station, and the regional division specifically includes wind turbine area, substation area, control center area, maintenance area, energy storage area, transmission line area and safety area; the data collection capability information and data collection capability threshold information of each aerosol sensor in each area of ​​the wind farm station are obtained, and the data collection capability information specifically includes data noise, response time, and data accuracy, and the data collection capability threshold information specifically includes data noise threshold, response time threshold, and data accuracy threshold; The data noise of each aerosol sensor in each area of ​​the wind farm station is compared with the data noise threshold, the response time is compared with the response time threshold, and the data accuracy is compared with the data accuracy threshold; the aerosol sensors in each area with data noise lower than the data noise threshold, response time lower than the response time threshold, and data accuracy higher than the data accuracy threshold are screened out, and the measurement range of the screened aerosol sensors in each area is further compared, and the aerosol sensor with the largest measurement range in each area is selected for marking, and then the power generation impact data of the marked aerosol sensors are analyzed.

[0009] Furthermore, the power generation impact data of each aerosol sensor location in the wind farm station are analyzed, and the specific analysis steps for selecting representative aerosol monitoring points of the wind farm station are as follows: respectively summing up the aerosol concentration variation coefficient and wind speed frequency at the marked aerosol sensor location, and obtaining the power generation impact score of each marked aerosol sensor location; sorting each marked aerosol sensor according to the size of the power generation impact score, and selecting the required number of aerosol sensor locations as representative aerosol monitoring points of the wind farm station based on the sorting order.

[0010] Furthermore, the aerosol collection data is specifically aerosol concentration; and the wind farm power generation data is specifically power generation.

[0011] Furthermore, based on the changes in the aerosol collection data of each representative aerosol monitoring point and the changes in the corresponding wind farm power generation data, analysis is performed to identify the degree of influence of the aerosol collection data of each representative aerosol monitoring point on the change in the wind farm power generation data. The specific analysis steps are as follows: based on the aerosol concentration of the representative aerosol monitoring point at each time point in the monitoring period, the change in aerosol concentration in each time period in the monitoring period is obtained; based on the power generation at each time point in the monitoring period, the change in power generation in each time period in the monitoring period is obtained; the change in aerosol concentration in each time period of each representative aerosol monitoring point is compared with the change in power generation in each time period, and then the average value of the comparison results is taken to obtain the change influence factor of the power generation performance of each representative aerosol monitoring point and the wind farm. The change influence factor is used to measure the degree of influence of the aerosol collection data on the change in the wind farm power generation data.

[0012] Furthermore, the aerosol collection data of the representative aerosol monitoring points of the wind farm are monitored in real time, and then the aerosol collection data of each representative aerosol monitoring point are used to analyze the degree of influence of changes in the power generation data of the wind farm. The specific analysis steps for real-time evaluation of the power generation performance of the wind farm are as follows: the aerosol collection data of each representative aerosol monitoring point of the wind farm monitored in real time are obtained, that is, the aerosol concentration collected by each representative aerosol monitoring point of the wind farm; the aerosol concentration collected by each representative aerosol monitoring point of the wind farm is multiplied by the corresponding representative aerosol monitoring point and the change influence factor of the wind farm power generation performance, and the average value is taken to obtain the power generation performance evaluation value of the wind farm. The power generation performance evaluation value of the wind farm is used to measure the power generation performance of the current wind farm.

[0013] A wind farm station power generation performance evaluation system, using the above-mentioned wind farm station power generation performance evaluation method, including: a power generation impact data acquisition module, used to identify aerosol sensors in the wind farm station, and then collect power generation impact data of the locations of various aerosol sensors in the wind farm station; an aerosol monitoring point selection module, used to analyze the power generation impact data of the locations of various aerosol sensors in the wind farm station based on the data collection capabilities of various aerosol sensors in the wind farm station, and select representative aerosol monitoring points of the wind farm station; a monitoring data acquisition module, used to obtain aerosol collection data of representative aerosol monitoring points at various time points in the monitoring period; The module is used to analyze the changes of aerosol collection data at each representative aerosol monitoring point and the corresponding changes of wind farm power generation data, and identify the degree of influence of aerosol collection data at each representative aerosol monitoring point on the changes of wind farm power generation data; the module is used to evaluate the power generation performance of wind farms in real time, and monitor the aerosol collection data at the representative aerosol monitoring points of wind farms in real time, and then use the aerosol collection data at each representative aerosol monitoring point to analyze the degree of influence of changes in wind farm power generation data, and evaluate the power generation performance of wind farms in real time.

[0014] The present invention has the following beneficial effects:

[0015] The method and system for evaluating the power generation performance of a wind farm can more accurately evaluate the impact of aerosols on the power generation performance of a wind farm by analyzing the impact of aerosol concentration changes on the power generation of the wind farm, and help identify whether aerosol concentration changes have a significant impact on power generation, and then take corresponding measures to improve power generation efficiency; by analyzing the power generation impact data of the location of each aerosol sensor, the most representative aerosol monitoring point is selected, making the evaluation process more centralized and effective, and avoiding the interference of redundant data; based on the data collection capability of each aerosol sensor, in-depth analysis of the data can improve the accuracy and effectiveness of the analysis, and selecting appropriate monitoring points can ensure that the analysis results are more representative; by real-time monitoring of the data of representative aerosol monitoring points, the impact of aerosol concentration changes on the power generation of the wind farm can be timely understood. The impact of aerosols on power generation can be monitored, so that wind farms can adjust their operating strategies in real time, such as adjusting the operating mode of wind turbines to optimize power generation performance; it provides a data-driven approach to evaluate the power generation performance of wind farms, and can make more scientific and accurate decisions based on the data, thereby improving the overall operational efficiency of wind farms; through real-time monitoring of changes in aerosol concentrations, early warnings can be given of situations that may affect power generation, and corresponding adjustments can be made, which will help reduce the negative impact of aerosols on wind farm power generation and thus improve power generation stability; accurate identification of the impact of aerosols on power generation can optimize the operation and maintenance strategies of wind farms, reduce unnecessary maintenance and adjustments, and save operating costs; at the same time, understanding the impact of aerosols on wind farms is also helpful for environmental management, and aerosol sources can be controlled or corresponding measures can be taken to reduce the negative impact of aerosols on the environment. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 The present invention is a flow chart of a method for evaluating the power generation performance of a wind farm.

[0017] Figure 2 This is a structural diagram of a wind farm power generation performance evaluation system of the present invention. DETAILED DESCRIPTION

[0018] The embodiment of the present application uses a method and system for evaluating the power generation performance of a wind farm station, which realizes real-time evaluation of wind farm station power generation by comprehensively considering the relationship between aerosol concentration and wind farm station power generation data, thereby improving the power generation efficiency and stability of the wind farm.

[0019] The overall idea of ​​the problem in the embodiment of this application is as follows:

[0020] By systematically analyzing the impact of changes in aerosol concentration within wind farms on power generation, we can achieve accurate and real-time evaluation of wind farm power generation performance. By combining aerosol monitoring with wind farm power generation data, we can identify key influencing factors and optimize the operation and management of wind farms. We can clarify the correlation between changes in aerosol concentration and changes in wind farm power generation, and use data from representative monitoring points for real-time monitoring and dynamic evaluation.

[0021] See also Figure 1 The embodiment of the present invention provides a technical solution: a method for evaluating the power generation performance of a wind farm station, comprising the following steps: identifying aerosol sensors in the wind farm station, and then collecting power generation impact data of the locations of each aerosol sensor in the wind farm station; analyzing the power generation impact data of the locations of each aerosol sensor in the wind farm station based on the data collection capability of each aerosol sensor in the wind farm station, and selecting representative aerosol monitoring points of the wind farm station; obtaining aerosol collection data and wind farm power generation data of representative aerosol monitoring points at each time point in the monitoring period; analyzing the changes in the aerosol collection data of each representative aerosol monitoring point and the corresponding changes in the power generation data of the wind farm station, respectively identifying the degree of influence of the aerosol collection data of each representative aerosol monitoring point on the changes in the power generation data of the wind farm station; real-time monitoring of the aerosol collection data of the representative aerosol monitoring points of the wind farm station, and then using the aerosol collection data of each representative aerosol monitoring point to analyze the degree of influence of the changes in the power generation data of the wind farm station, and evaluating the power generation performance of the wind farm station in real time.

[0022] Specifically, the power generation influencing data at the location of each aerosol sensor of the wind farm station specifically include: aerosol concentration variation coefficient and wind speed frequency.

[0023] In this implementation plan, the coefficient of variation of aerosol concentration and wind speed frequency are selected as the basis for evaluating the power generation impact data of each aerosol sensor location in the wind farm station because the coefficient of variation of aerosol concentration and wind speed frequency can effectively reflect the stability of aerosol concentration and the distribution characteristics of wind speed, thereby helping to judge the representativeness of the monitoring point and the validity of the data. The specific coefficient of variation of aerosol concentration represents the ratio of the standard deviation of aerosol concentration data to the mean, which can measure the relative volatility of aerosol concentration. A higher coefficient of variation indicates that the aerosol concentration is more unstable, and vice versa, it indicates that the concentration is relatively stable. The standard deviation and mean are calculated through long-term aerosol concentration monitoring data, and then the coefficient of variation of aerosol concentration is calculated; the wind speed frequency is used to describe the frequency of wind speed occurrence in different wind speed ranges, which can reflect the common situation of wind speed in the wind farm. Understanding the distribution of wind speed can help evaluate the impact of aerosol concentration on power generation. Long-term wind speed data is obtained by installing wind speed sensors and counting the frequency of occurrence in different wind speed ranges.

[0024] Specifically, the specific analysis based on the consideration of the data collection capability of each aerosol sensor of the wind farm station is as follows: the wind farm station is divided into regions according to the working operation tasks of the wind farm station, and the regional division specifically includes wind turbine area, substation area, control center area, maintenance area, energy storage area, transmission line area and safety area; the data collection capability information and data collection capability threshold information of each aerosol sensor in each area of ​​the wind farm station are obtained, and the data collection capability information specifically includes data noise, response time, and data accuracy, and the data collection capability threshold information specifically includes data noise threshold, response time threshold, and data accuracy threshold; the wind farm The data noise of each aerosol sensor in each area of ​​the station is compared with the data noise threshold, the response time is compared with the response time threshold, and the data accuracy is compared with the data accuracy threshold; the aerosol sensors with data noise lower than the data noise threshold, response time lower than the response time threshold, and data accuracy higher than the data accuracy threshold in each area are screened out, and the measurement ranges of the screened aerosol sensors in each area are further compared, and the aerosol sensor with the largest measurement range in each area is selected for marking, and then the power generation impact data of the marked aerosol sensors are analyzed.

[0025] In this implementation manner, the wind farm area division may be based not only on the above-mentioned division based on work operation tasks, but also on geographical location, and may be specifically based on subjective division by wind farm operators. The safety zone specifically refers to the safety facility area of ​​the wind farm station. The safety facilities specifically include fences, surveillance cameras, and alarm systems, which are used to protect the safety of the wind farm station. Data noise refers to the random interference or error that occurs in the sensor acquisition process in addition to the actual measurement signal. A high noise level will affect the clarity and availability of the data. The stability and noise level of the sensor output are tested under known standard conditions. The noise level can also be measured by comparing the sensor output with the known aerosol concentration standard value. The response time refers to the time required for the sensor to output stable data from receiving the input signal. A shorter response time means that the sensor can reflect the actual situation more quickly. It is obtained by applying a sudden change in aerosol concentration to the sensor and measuring its reaction time. It can also be obtained by referring to the sensor's technical specification. Data accuracy refers to the degree of proximity between the sensor measurement result and the actual aerosol concentration. High accuracy means that the measurement result is closer to the true value. The sensor is calibrated using a standard aerosol sample of known concentration and the measurement result is obtained by comparing the standard value. The accuracy of the sensor can also be evaluated through long-term monitoring and historical data analysis.

[0026] The data noise threshold is obtained by comparing and analyzing the noise levels of multiple sensors to determine the upper limit of noise in industry standards or best practices. You can also refer to industry standards, technical specifications provided by manufacturers, or acceptable noise levels determined through field tests. The response time threshold is based on actual application needs and sets requirements for response time. You can also refer to industry standards, application scenario requirements, or the most suitable response time determined based on equipment performance test results. The data accuracy threshold is obtained by calibrating standard aerosol samples to determine the accuracy range of the sensor. You can also refer to industry standards, technical specifications provided by manufacturers, or accuracy requirements determined through experiments and long-term monitoring.

[0027] By comparing the actual data collection capability of the sensor with the pre-set threshold, aerosol sensors that meet the requirements are screened out, ensuring that the sensors used in different areas have sufficient accuracy and response speed to effectively reflect the actual aerosol concentration level; depending on the different regions, sensors with the best performance within a specific measurement range are selected to ensure that the monitoring system in each area is in the best working condition; after screening out suitable sensors, their measurement ranges are further compared and the sensors with the largest measurement range are selected, ensuring that in each area, the selected sensors can cover a wider range of particle sizes and concentrations, thereby improving the comprehensiveness and effectiveness of monitoring.

[0028] Specifically, the power generation impact data of each aerosol sensor location in the wind farm station are analyzed, and the specific analysis steps of the representative aerosol monitoring point of the wind farm station are selected as follows: the aerosol concentration variation coefficient and wind speed frequency at the marked aerosol sensor location are respectively given weighted values ​​and summed to obtain the power generation impact score of each marked aerosol sensor location. The specific calculation formula for the power generation impact score is: , where Indicated as the aerosol sensor number, Indicates The power generation impact score of each aerosol sensor location, Indicates The coefficient of variation of aerosol concentration at the location of each aerosol sensor, Indicates The wind speed frequency at the location of the aerosol sensor, represents the weight value of the coefficient of variation of aerosol concentration, Represents the weight value of wind speed frequency; sorts each marked aerosol sensor according to the size of the power generation impact score, and selects the locations of the required number of aerosol sensors as representative aerosol monitoring points of the wind farm station based on the sorting order.

[0029] In this implementation plan, the specific method of assigning weight values ​​of aerosol concentration variation coefficient and wind speed frequency is analyzed as follows: experts with experience in wind farm operation or evaluation score the importance of aerosol concentration variation coefficient and wind speed frequency based on their professional knowledge and experience, and obtain the weight value of each indicator. The original data such as aerosol concentration variation coefficient and wind speed frequency can also be standardized to eliminate the influence of dimension and order of magnitude. Then, the PCA method is used to calculate the characteristic root, variance explanation rate and load coefficient of each principal component, and the weight of each principal component is determined according to the variance explanation rate, so as to obtain the weight value of aerosol concentration variation coefficient and wind speed frequency.

[0030] Monitoring points with higher coefficients of variation of aerosol concentrations indicate larger fluctuations in aerosol concentrations. Such fluctuations can help identify the impact of aerosol concentrations on power generation under different conditions and provide more extensive reference data. Points with high coefficients of variation can provide aerosol concentration data under extreme or marginal conditions, which is essential for understanding the maximum impact of aerosols on power generation. By selecting these points, the potential negative impact of these special environments on power generation performance can be identified and analyzed, helping to develop optimization measures for specific problems, and helping to optimize the design and operation of wind farms, ensuring that the system can adapt to changes in aerosol concentrations and improving the robustness of the system. Monitoring points with higher wind speed frequencies are usually located in areas with higher wind speed frequencies, which means that these points can reflect the actual wind farm performance. The actual wind speed conditions, selecting these points can ensure that the monitoring data can more accurately reflect the actual operating conditions of the wind farm, so as to more effectively evaluate the impact of aerosol concentration on power generation, help to understand the specific impact of aerosol concentration on power generation under high wind speed conditions, provide practical data for optimizing the operation of wind turbines, and thus provide a reliable basis for the overall power generation performance optimization; comprehensive selection of monitoring points with high coefficient of variation of aerosol concentration and wind speed frequency can cover the extreme fluctuations of aerosol concentration and the impact under common wind speed conditions, can fully understand the various potential impacts of aerosol concentration changes on power generation performance, ensure the comprehensiveness of the evaluation results, improve the adaptability and robustness of the system under different conditions, thereby improving the overall operational stability and efficiency of the wind farm.

[0031] A specific example is: assuming that the weight value of the coefficient of variation of aerosol concentration is 0.6, and the weight value of the wind speed frequency is 0.4, the aerosol sensors currently marked are: Sensor A: The coefficient of variation of aerosol concentration is 0.15, and the wind speed frequency is 0.5; Sensor B: The coefficient of variation of aerosol concentration is 0.2, and the wind speed frequency is 0.6; Sensor C: The coefficient of variation of aerosol concentration is 0.1, and the wind speed frequency is 0.4; Sensor D: The coefficient of variation of aerosol concentration is 0.25, and the wind speed frequency is 0.55. The power generation impact score calculation formula is used to calculate: Sensor The power generation impact score of sensor A is 0.29, the power generation impact score of sensor B is 0.36, the power generation impact score of sensor C is 0.22, and the power generation impact score of sensor D is 0.37. The sensors are ranked according to the power generation impact score as follows: sensor D, sensor B, sensor A, and sensor C. Now three representative aerosol monitoring points need to be selected, and the three representative aerosol monitoring points selected are the locations of sensor D, sensor B, and sensor A.

[0032] Specifically, the aerosol collection data refers to aerosol concentration; the wind farm power generation data refers to power generation.

[0033] Based on the changes in the aerosol collection data of each representative aerosol monitoring point and the changes in the corresponding wind farm station power generation data, the specific analysis steps for identifying the impact of the aerosol collection data of each representative aerosol monitoring point on the changes in the wind farm station power generation data are as follows: Based on the aerosol concentration of the representative aerosol monitoring point at each time point in the monitoring period, the aerosol concentration change in each time period in the monitoring period is obtained: , where Indicates the number of the representative aerosol monitoring point, Indicates the number of each time point in the monitoring period. Indicates Representative aerosol monitoring points and time points To time point The change in aerosol concentration, Indicates Representative aerosol monitoring points and time points The aerosol concentration, Indicates Representative aerosol monitoring points and time points The aerosol concentration; based on the power generation at each time point in the monitoring period, the power generation change in each time period in the monitoring period is obtained: , where Indicates time point To time point The change in power generation, Indicates time point of power generation, Indicates time point The change in aerosol concentration at each representative aerosol monitoring point in each time period is compared with the change in power generation in each time period, and then the average value of the comparison results is taken to obtain the change influencing factors of each representative aerosol monitoring point and the power generation performance of the wind farm: , where Indicates The representative aerosol monitoring points and the influencing factors of the power generation performance of wind farms, It represents the total number of time periods within the monitoring period. The change impact factor is used to measure the impact of aerosol collection data on the change of wind farm station power generation data.

[0034] In this implementation scheme, aerosol concentration is specifically collected at set monitoring points using aerosol sensors; power generation is obtained through the power generation monitoring system of the wind farm. By quantitatively analyzing the relationship between changes in aerosol concentration and changes in wind farm power generation, the degree of influence of different aerosol monitoring points on power generation performance can be accurately evaluated, which helps to identify the main factors affecting power generation and help operators and decision makers optimize operating strategies; selecting monitoring points with a more significant relationship between changes in aerosol concentration and power generation as representative monitoring points can ensure that the selected points can effectively reflect the power generation performance of the entire wind farm, help simplify the monitoring and evaluation process, and improve the efficiency and accuracy of data analysis; by real-time monitoring of data from representative aerosol monitoring points, the actual impact of aerosol influence on current power generation performance can be timely evaluated, which can help the wind farm operation team quickly respond to changes and take necessary adjustment measures to optimize power generation efficiency.

[0035] Specifically, the aerosol collection data of the representative aerosol monitoring points of the wind farm station are monitored in real time, and then the aerosol collection data of each representative aerosol monitoring point are used to analyze the degree of influence of changes in the power generation data of the wind farm station. The specific analysis steps for real-time evaluation of the power generation performance of the wind farm station are as follows: the aerosol collection data of each representative aerosol monitoring point of the wind farm station under real-time monitoring, that is, the aerosol concentration collected by each representative aerosol monitoring point of the wind farm station; the aerosol concentration collected by each representative aerosol monitoring point of the wind farm station is multiplied by the corresponding representative aerosol monitoring point and the change influence factor of the wind farm station power generation performance, and the average value is taken to obtain the wind farm station power generation performance evaluation value, which is used to measure the current wind farm station power generation performance.

[0036] In this implementation plan, the specific calculation formula for the wind farm station power generation performance evaluation value is: , where represents the wind farm power generation performance evaluation value, Indicates Aerosol concentrations collected at representative aerosol monitoring points, Indicates the total number of representative aerosol monitoring points. The number of representative aerosol monitoring points is set according to the actual monitoring needs. For example, three representative aerosol monitoring points can be set. , the wind farm power generation performance evaluation value is calculated as: By real-time monitoring and analyzing the data from representative aerosol monitoring points, the impact of changes in aerosol concentration on the power generation performance of wind farms can be evaluated in real time, allowing the operation team to quickly understand the current power generation efficiency and take timely adjustment measures to optimize power generation performance; quantifying the relationship between aerosol concentration and power generation can provide a more precise and accurate evaluation of power generation performance, helping to avoid decisions based on experience or subjective judgment, thereby optimizing the operation and management of wind farms.

[0037] A wind farm station power generation performance evaluation system, using the above-mentioned wind farm station power generation performance evaluation method, including: a power generation impact data acquisition module, used to identify aerosol sensors in the wind farm station, and then collect power generation impact data of the locations of various aerosol sensors in the wind farm station; an aerosol monitoring point selection module, used to analyze the power generation impact data of the locations of various aerosol sensors in the wind farm station based on the data collection capabilities of various aerosol sensors in the wind farm station, and select representative aerosol monitoring points of the wind farm station; a monitoring data acquisition module, used to obtain aerosol collection data of representative aerosol monitoring points at various time points in the monitoring period; The module is used to analyze the changes of aerosol collection data at each representative aerosol monitoring point and the corresponding changes of wind farm power generation data, and identify the degree of influence of aerosol collection data at each representative aerosol monitoring point on the changes of wind farm power generation data; the module is used to evaluate the power generation performance of wind farms in real time, and monitor the aerosol collection data at the representative aerosol monitoring points of wind farms in real time, and then use the aerosol collection data at each representative aerosol monitoring point to analyze the degree of influence of changes in wind farm power generation data, and evaluate the power generation performance of wind farms in real time.

[0038] In summary, this application has at least the following effects:

[0039] By combining the data from aerosol sensors and the power generation data of wind farms, the impact of aerosols on the power generation performance of wind farms can be more accurately assessed, thereby providing more targeted improvement suggestions. By analyzing the data from different aerosol sensors, representative aerosol monitoring points can be identified, which helps to concentrate resources for key monitoring and helps operators understand which areas have the greatest impact on power generation performance, thereby optimizing the operation strategy of the wind farm. Real-time monitoring of the data from representative aerosol monitoring points allows dynamic adjustment of the power generation performance of the wind farm. If it is found that changes in a certain aerosol level have a significant impact on power generation, operators can take measures to mitigate these impacts and maintain the stability of power generation performance. By identifying and analyzing the specific impact of aerosols on power generation, strategies to reduce the impact of aerosols can be formulated, thereby improving the power generation efficiency of wind farms. By real-time monitoring of changes in aerosol concentrations, situations that may affect power generation can be warned in advance and corresponding adjustments can be made, which helps to reduce the negative impact of aerosols on wind farm power generation, thereby improving power generation stability. Based on the analysis results of the impact of aerosols on power generation performance, the layout of wind turbines in wind farms and the setting of aerosol monitoring points can be optimized to improve overall power generation performance.

[0040] It should be understood by those skilled in the art that the embodiments of the present invention may be provided as methods and systems. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program codes.

[0041] The present invention is described with reference to the flowcharts and structure diagrams of the methods and systems according to the embodiments of the present invention. It should be understood that each process and combination of modules in the flowcharts and structure diagrams can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowcharts. Figure 1 process or processes and structures Figure 1 A device that specifies functionality in a module or modules.

[0042] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 process or processes and structures Figure 1 A function specified in a module or multiple modules.

[0043] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 process or processes and structures Figure 1 Steps to specify functionality in a module or multiple modules.

[0044] Although the preferred embodiments of the present invention have been described, those skilled in the art may make other changes and modifications to these embodiments once they have learned the basic creative concept. Therefore, the appended claims are intended to be interpreted as including the preferred embodiments and all changes and modifications that fall within the scope of the present invention.

[0045] Obviously, those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention. Thus, if these modifications and variations of the present invention fall within the scope of the claims of the present invention and their equivalents, the present invention is also intended to include these modifications and variations.

Claims

1. A method for evaluating the power generation performance of a wind farm, characterized in that: The following steps are involved: Identify aerosol sensors within wind farms and collect data on the impact of each aerosol sensor location on power generation; Based on the data collection capabilities of each aerosol sensor at the wind farm station, the power generation impact data of each aerosol sensor location at the wind farm station is analyzed, and representative aerosol monitoring points of the wind farm station are selected; Obtain aerosol collection data and wind farm power generation data from representative aerosol monitoring points at each time point during the monitoring period; Based on the changes in the aerosol collection data of each representative aerosol monitoring point and the changes in the corresponding wind farm station power generation data, the influence of the aerosol collection data of each representative aerosol monitoring point on the changes in the wind farm station power generation data is identified respectively; The aerosol collection data of representative aerosol monitoring points of the wind farm station are monitored in real time, and then the aerosol collection data of each representative aerosol monitoring point are used to analyze the impact of changes in the wind farm station's power generation data, and the power generation performance of the wind farm station is evaluated in real time.

2. A method for evaluating the power generation performance of a wind farm according to claim 1, characterized in that: The power generation influencing data at the locations of the aerosol sensors of the wind farm station specifically include: aerosol concentration variation coefficient and wind speed frequency.

3. A method for evaluating the power generation performance of a wind farm according to claim 1, characterized in that: The specific analysis based on the consideration of the data collection capability of each aerosol sensor at the wind farm station is as follows: The wind farm is divided into areas according to its operation tasks. The areas include wind turbine area, substation area, control center area, maintenance area, energy storage area, transmission line area and safety area. Acquire data acquisition capability information and data acquisition capability threshold information of each aerosol sensor in each area of ​​the wind farm station, wherein the data acquisition capability information specifically includes data noise, response time, and data accuracy, and the data acquisition capability threshold information specifically includes data noise threshold, response time threshold, and data accuracy threshold; Compare the data noise of each aerosol sensor in each area of ​​the wind farm station with the data noise threshold, the response time with the response time threshold, and the data accuracy with the data accuracy threshold; Aerosol sensors with data noise lower than the data noise threshold, response time lower than the response time threshold, and data accuracy higher than the data accuracy threshold in each area are screened out, and the measurement ranges of the screened aerosol sensors in each area are further compared, and the aerosol sensor with the largest measurement range in each area is selected for marking, and then the power generation impact data of the marked aerosol sensors are analyzed.

4. A method for evaluating the power generation performance of a wind farm according to claim 1, characterized in that: The power generation impact data of each aerosol sensor location in the wind farm station are analyzed, and the specific analysis steps of the representative aerosol monitoring points of the wind farm station are selected as follows: The weighted values ​​of the aerosol concentration variation coefficient and wind speed frequency at the locations of the marked aerosol sensors are summed up to obtain the power generation impact score of the locations of the marked aerosol sensors; The marked aerosol sensors are sorted according to the power generation impact score, and the locations of the required number of aerosol sensors are selected as representative aerosol monitoring points of the wind farm station based on the sorting order.

5. A method for evaluating the power generation performance of a wind farm according to claim 1, characterized in that: The aerosol collection data is specifically aerosol concentration; The wind farm power generation data specifically refers to power generation.

6. A method for evaluating the power generation performance of a wind farm according to claim 1, characterized in that: Based on the analysis of the changes in the aerosol collection data of each representative aerosol monitoring point and the changes in the corresponding wind farm station power generation data, the specific analysis steps for identifying the impact of the aerosol collection data of each representative aerosol monitoring point on the changes in the wind farm station power generation data are as follows: Based on the aerosol concentration of the representative aerosol monitoring point at each time point in the monitoring period, the aerosol concentration change in each time period in the monitoring period is obtained; Based on the power generation at each time point in the monitoring period, the power generation change in each time period in the monitoring period is obtained; The changes in aerosol concentration at each representative aerosol monitoring point in each time period were compared with the changes in power generation in each time period, and then the average values ​​of the comparison results were taken to obtain the change impact factors of each representative aerosol monitoring point and the power generation performance of the wind farm. The change impact factors are used to measure the impact of aerosol collection data on the changes in wind farm power generation data.

7. A method for evaluating the power generation performance of a wind farm according to claim 1, characterized in that: The aerosol collection data of the representative aerosol monitoring points of the wind farm station are monitored in real time, and then the aerosol collection data of each representative aerosol monitoring point are used to analyze the influence of the change of the power generation data of the wind farm station. The specific analysis steps for real-time evaluation of the power generation performance of the wind farm station are as follows: Acquire aerosol collection data of each representative aerosol monitoring point of the wind farm station under real-time monitoring, that is, aerosol concentration collected by each representative aerosol monitoring point of the wind farm station; The aerosol concentration collected at each representative aerosol monitoring point of the wind farm is multiplied by the corresponding representative aerosol monitoring point and the change influencing factor of the wind farm's power generation performance, and the average value is taken to obtain the wind farm's power generation performance evaluation value, which is used to measure the current wind farm's power generation performance.

8. A wind farm power generation performance evaluation system, using a wind farm power generation performance evaluation method according to any one of claims 1 to 7, characterized in that: include: A power generation impact data acquisition module is used to identify aerosol sensors in the wind farm station, and then collect power generation impact data at the location of each aerosol sensor in the wind farm station; The aerosol monitoring point selection module is used to analyze the power generation impact data of the locations of each aerosol sensor in the wind farm station based on the data collection capabilities of each aerosol sensor in the wind farm station, and select representative aerosol monitoring points in the wind farm station; A monitoring data acquisition module is used to obtain aerosol collection data and wind farm station power generation data of representative aerosol monitoring points at each time point in the monitoring period; The correlation impact analysis module is used to analyze the changes in the aerosol collection data of each representative aerosol monitoring point and the changes in the corresponding wind farm station power generation data, and identify the degree of influence of the aerosol collection data of each representative aerosol monitoring point on the changes in the wind farm station power generation data; The real-time evaluation module for the power generation performance of a wind farm is used to monitor the aerosol collection data of the representative aerosol monitoring points of the wind farm in real time, and then use the aerosol collection data of each representative aerosol monitoring point to analyze the impact of changes in the power generation data of the wind farm, and conduct real-time evaluation of the power generation performance of the wind farm.

Images