A meteorological data analysis system and method for wind and solar power station power plant

Abstract

The present invention discloses a meteorological data analysis system and method for a wind and solar power plant, and relates to the technical field of meteorological data analysis for power plants. The system comprises: a data acquisition and processing module: real-time acquisition of meteorological data of wind and solar power plants, and data preprocessing; a data analysis and prediction module: using statistical methods and machine learning algorithms to analyze meteorological data, and predicting the power generation potential of wind and solar power plants; a result visualization module: displaying the data analysis results and prediction results in a visualized form. The present invention collects data in real time through high-precision acquisition equipment such as anemometers, barometers, thermometers, hygrometers, and radiometers, ensuring that the data is accurate and reliable, meeting the high-precision data analysis of local areas of wind farms, and being able to accurately reflect wind speed changes, thereby ensuring the accuracy of meteorological data analysis of wind and solar power plants.

Description

Technical Field

[0001] The present invention relates to the technical field of meteorological data analysis for power plants, and in particular to a system and method for analyzing meteorological data for wind and solar power plants. Background Art

[0002] With the global emphasis on environmental protection and sustainable development, energy structure transformation has become an important strategy for all countries. Wind and solar energy, as clean and renewable forms of energy, have received widespread attention and promotion. As one of the main forms of utilization of these two energy sources, the construction and operation of wind and solar power plants are of great significance to promoting energy structure transformation and achieving green development goals. Therefore, in-depth analysis of the meteorological data of wind and solar power plants to optimize their operating efficiency and power generation capacity has become an important topic at present. Therefore, a meteorological data analysis system and method for wind and solar power plants has been developed.

[0003] The existing technology has the following problems:

[0004] At present, some meteorological data systems cannot meet the needs of high-precision data analysis, making it difficult to improve the comprehensiveness and accuracy of the analysis results, and cannot accurately reflect the wind speed changes in local areas of wind farms. At the same time, some current systems have problems such as untimely data updates and slow processing speeds, which causes the analysis results to lag behind actual meteorological changes, affecting the timely response and decision-making of power plants, and the level of intelligence needs to be improved. Summary of the invention

[0005] The present invention provides a meteorological data analysis system and method for a wind-solar power plant to solve the problems raised in the above-mentioned background technology.

[0006] In order to solve the above technical problems, the technical solution adopted by the present invention is:

[0007] In a first aspect, the present invention provides a meteorological data analysis system for a wind and solar power plant, the system comprising:

[0008] Data acquisition and processing module: real-time collection of meteorological data from wind and solar power stations and power plants, and data preprocessing;

[0009] Data analysis and prediction module: Analyze meteorological data using statistical methods and machine learning algorithms, and predict the power generation potential of wind and solar power plants;

[0010] Result visualization module: displays data analysis results and prediction results in a visual form.

[0011] Preferably, the meteorological data includes wind speed, wind direction, temperature, air pressure, humidity and solar radiation intensity, wherein the meteorological data comes from ground observation stations, satellite remote sensing and radar monitoring.

[0012] Preferably, the visualization forms include charts, graphs, pie charts, bar charts and three-dimensional models.

[0013] In a second aspect, the present invention further provides a method for analyzing meteorological data of a wind-solar power plant, the method comprising:

[0014] S1: Data acquisition and processing;

[0015] S2: Data analysis and model building;

[0016] S3: Data prediction and visualization;

[0017] S4: Application of results and feedback.

[0018] Preferably, the S1 comprises:

[0019] S11: Real-time collection of meteorological data through high-precision collection equipment;

[0020] S12: Use advanced data processing techniques for data preprocessing, including cleaning, integration, noise removal, missing value filling and data correction.

[0021] The data collection equipment includes anemometer, barometer, thermometer, hygrometer and radiometer.

[0022] Preferably, S2 includes:

[0023] S21: Perform descriptive statistics on the preprocessed meteorological data to understand the basic characteristics of the data, including mean, standard deviation, maximum and minimum values, and perform trend analysis and correlation analysis;

[0024] S22: Based on historical meteorological data and power generation data, establish a wind speed prediction model and a photovoltaic power generation prediction model, and train the models;

[0025] S23: Optimize model parameters by applying machine learning algorithms;

[0026] S24: Evaluate and optimize the model through cross-validation and evaluation index methods;

[0027] S25: Regularly update and tune the prediction model in real time.

[0028] Preferably, S3 includes:

[0029] S31: Use the prediction model to make data predictions;

[0030] S32: Display the data analysis results and prediction results in a visual form.

[0031] Preferably, S4 includes: applying the prediction results to the planning, design, operation and maintenance of wind and solar power plants, verifying and adjusting the model according to actual power generation conditions, and forming a closed-loop feedback mechanism.

[0032] Due to the adoption of the above technical solution, the present invention has the following technical advances compared with the prior art:

[0033] 1. The present invention provides a meteorological data analysis system and method for a wind and solar power station power plant. Through high-precision collection equipment such as anemometers, barometers, thermometers, hygrometers, and radiometers, data is collected in real time to ensure that the data is accurate and reliable, meet the needs of high-precision data analysis in local areas of wind farms, and can accurately reflect changes in wind speed, thereby ensuring the accuracy of meteorological data analysis in wind and solar power stations. Key meteorological data such as wind speed, wind direction, temperature, air pressure, humidity, solar radiation intensity, etc. are collected in real time through multiple channels such as ground observation stations, satellite remote sensing, and radar monitoring to ensure that the data is comprehensive, representative, and timely.

[0034] 2. The present invention provides a meteorological data analysis system and method for a wind and solar power plant. The system integrates multiple data sources and analysis methods, can comprehensively reflect the meteorological conditions of the wind and solar power plant, and uses machine learning algorithms to analyze meteorological data, thereby improving the intelligence level of the system.

[0035] 3. The present invention provides a meteorological data analysis system and method for a wind and solar power plant. By updating and optimizing the prediction model in real time, the data can be updated in a timely manner to ensure the timeliness and accuracy of the prediction results, improve the processing speed of the system, and avoid the analysis results lagging behind the actual meteorological changes, which affects the timely response and decision-making of the power plant.

[0036] 4. The present invention provides a meteorological data analysis system and method for a wind and solar power plant. Through the cooperation of multiple modules such as a data acquisition and processing module, a data analysis and prediction module, and a result visualization module, the system realizes the comprehensive collection, efficient processing, precise analysis and result visualization of the meteorological data of the wind and solar power plant, provides strong data support for the planning, design, operation and maintenance of the power plant, helps to improve the power generation efficiency and economic benefits of the wind and solar power plant, and promotes the sustainable development of renewable energy. The result visualization module makes the data analysis results and prediction results more intuitive and easy to understand, so that users can intuitively understand the information behind the data. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] Figure 1 This is a framework diagram of the meteorological data analysis system for wind and solar power stations and power plants of the present invention;

[0038] Figure 2 It is a schematic diagram of the flow chart of the meteorological data analysis method of the wind and solar power station power plant of the present invention;

[0039] Figure 3 It is a schematic diagram of the data collection and processing flow of the present invention;

[0040] Figure 4 A schematic diagram of the data analysis and model building process of the present invention;

[0041] Figure 5 It is a schematic diagram of the data prediction and visualization process of the present invention. DETAILED DESCRIPTION

[0042] In order to make the technical means, creative features, objectives and effects achieved by the present invention easy to understand, the present invention is further explained below in conjunction with specific implementation methods.

[0043] First, as Figure 1 As shown, the present invention provides a meteorological data analysis system for a wind and solar power station power plant, the system comprising:

[0044] Data acquisition and processing module: real-time collection of meteorological data from wind and solar power stations and power plants, and data preprocessing;

[0045] Data analysis and prediction module: Analyze meteorological data using statistical methods and machine learning algorithms, and predict the power generation potential of wind and solar power plants;

[0046] Result visualization module: Displays data analysis results and prediction results in a visual form, making them more intuitive and easy to understand, allowing users to intuitively understand the information behind the data.

[0047] The system integrates a variety of data sources and analysis methods, and can comprehensively reflect the meteorological conditions of wind and solar power plants. Through the cooperation of multiple modules such as data acquisition and processing modules, data analysis and prediction modules, and result visualization modules, it can realize the comprehensive collection, efficient processing, precise analysis and result visualization of meteorological data of wind and solar power plants, providing strong data support for the planning, design, operation and maintenance of power plants, helping to improve the power generation efficiency and economic benefits of wind and solar power plants and promote the sustainable development of renewable energy.

[0048] Meteorological data include wind speed, wind direction, temperature, air pressure, humidity and solar radiation intensity, among which meteorological data come from ground observation stations, satellite remote sensing and radar monitoring.

[0049] Key meteorological data such as wind speed, wind direction, temperature, air pressure, humidity, and solar radiation intensity are collected in real time through multiple channels such as ground observation stations, satellite remote sensing, and radar monitoring to ensure the comprehensiveness, representativeness, and timeliness of the data.

[0050] Second, as Figure 2As shown, the present invention also provides a method for analyzing meteorological data of a wind-solar power plant, the method comprising:

[0051] S1: Data acquisition and processing;

[0052] S2: Data analysis and model building;

[0053] S3: Data prediction and visualization;

[0054] S4: Application of results and feedback.

[0055] like Figure 3 As shown, S1 includes:

[0056] S11: Real-time collection of meteorological data through high-precision collection equipment;

[0057] S12: Use advanced data processing technology to preprocess data, including cleaning, integration, noise removal, filling missing values ​​and data correction, to reduce the impact of random noise, ensure data accuracy and consistency, improve data quality, and ensure the accuracy of subsequent data analysis.

[0058] The data collection equipment includes anemometer, barometer, thermometer, hygrometer and radiometer.

[0059] Real-time data collection is carried out through high-precision data collection equipment such as anemometers, barometers, thermometers, hygrometers, and radiometers to ensure that the data is accurate and reliable, meet the needs of high-precision data analysis in local areas of wind farms, and accurately reflect wind speed changes, thereby ensuring the accuracy of meteorological data analysis in wind and solar power stations and power plants.

[0060] like Figure 4 As shown, S2 includes:

[0061] S21: Perform descriptive statistics on the preprocessed meteorological data to understand the basic characteristics of the data, including mean, standard deviation, maximum and minimum values, and perform trend analysis and correlation analysis to reveal the changing patterns and internal connections of meteorological parameters;

[0062] S22: Based on historical meteorological data and power generation data, establish a wind speed prediction model and a photovoltaic power generation prediction model, and train the models;

[0063] S23: By applying machine learning algorithms to optimize model parameters, the accuracy of model predictions is improved, while the intelligence level of the system is improved;

[0064] S24: Evaluate and optimize the model through cross-validation and evaluation index methods to ensure the stability and reliability of the model in practical applications;

[0065] S25: Regularly updating and tuning the prediction model in real time can update data in a timely manner, ensure the timeliness and accuracy of the prediction results, improve the processing speed of the system, and avoid the analysis results lagging behind the actual meteorological changes, which affects the timely response and decision-making of the power plant.

[0066] like Figure 5 As shown, S3 includes:

[0067] S31: Use the prediction model to make data predictions;

[0068] S32: Display the data analysis results and prediction results in a visual form.

[0069] S4 includes: applying the prediction results to the planning, design, operation and maintenance of wind and solar power plants, verifying and adjusting the model according to the actual power generation situation, and forming a closed-loop feedback mechanism.

[0070] In summary, key meteorological data such as wind speed, wind direction, temperature, air pressure, humidity and solar radiation intensity are collected in real time through ground observation stations, satellite remote sensing and radar monitoring and other channels to ensure the comprehensiveness, representativeness and timeliness of the data. High-precision data collection equipment such as anemometers, barometers, thermometers, hygrometers and radiometers are used to collect data in real time to ensure the accuracy and reliability of the data, meet the needs of high-precision data analysis, and accurately reflect the changes in wind speed in local areas of wind farms. Advanced data processing technology is used for data preprocessing to ensure data accuracy and consistency and improve data quality. Descriptive statistics are performed on the preprocessed meteorological data to understand the basic characteristics of the data such as the mean, standard deviation, maximum and minimum values, and trend analysis and correlation analysis are performed to reveal the changing laws and internal connections of meteorological parameters. Combined with power generation data, the impact of meteorological conditions on power generation efficiency is analyzed. Prediction models are used for data prediction, and the data analysis results and prediction results are displayed in a visual form to make the data analysis results and prediction results more vivid. The results are more intuitive and easy to understand, which makes it easier for users to intuitively understand the information behind the data. The prediction results are applied to the planning, design, operation and maintenance of wind and solar power plants, and the model is verified and adjusted according to the actual power generation situation to form a closed-loop feedback mechanism. In addition, by updating and tuning the prediction model in real time, the data can be updated in time to ensure the timeliness and accuracy of the prediction results, improve the processing speed of the system, avoid the analysis results lagging behind the actual meteorological changes, and affect the timely response and decision-making of the power plant. The machine learning algorithm is used to analyze the meteorological data to improve the intelligence level of the system. The system integrates a variety of data sources and analysis methods, which can fully reflect the meteorological conditions of wind and solar power plants, thereby realizing the comprehensive collection, efficient processing, accurate analysis and result visualization of meteorological data of wind and solar power plants, providing strong data support for the planning, design, operation and maintenance of power plants, helping to improve the power generation efficiency and economic benefits of wind and solar power plants, and promoting the sustainable development of renewable energy.

[0071] The above generally describes the present invention in detail, but it is obvious to a person skilled in the art that some modifications or improvements can be made to the present invention. Therefore, modifications or improvements that do not depart from the spirit of the present invention are within the scope of protection of the present invention.

Claims

1. A meteorological data analysis system for a wind and solar power plant, characterized in that: The system includes: Data acquisition and processing module: real-time collection of meteorological data from wind and solar power stations and power plants, and data preprocessing; Data analysis and prediction module: Analyze meteorological data using statistical methods and machine learning algorithms, and predict the power generation potential of wind and solar power plants; Result visualization module: displays data analysis results and prediction results in a visual form.

2. A meteorological data analysis system for a wind-solar power plant according to claim 1, characterized in that: The meteorological data include wind speed, wind direction, temperature, air pressure, humidity and solar radiation intensity, wherein the meteorological data comes from ground observation stations, satellite remote sensing and radar monitoring.

3. A method for analyzing meteorological data of a wind-solar power plant, comprising a meteorological data analysis system for a wind-solar power plant according to any one of claims 1 to 2, characterized in that: The method includes: S1: Data acquisition and processing; S2: Data analysis and model building; S3: Data prediction and visualization; S4: Application of results and feedback.

4. A method for analyzing meteorological data of a wind-solar power plant according to claim 3, characterized in that: The S1 includes: S11: Real-time collection of meteorological data through high-precision collection equipment; S12: Use advanced data processing technology to pre-process data. The data collection equipment includes anemometer, barometer, thermometer, hygrometer and radiometer.

5. The method for analyzing meteorological data of a wind-solar power plant according to claim 3, characterized in that: The S2 includes: S21: Perform descriptive statistics on the preprocessed meteorological data to understand the basic characteristics of the data, including mean, standard deviation, maximum and minimum values, and perform trend analysis and correlation analysis; S22: Based on historical meteorological data and power generation data, establish a wind speed prediction model and a photovoltaic power generation prediction model, and train the models; S23: Optimize model parameters by applying machine learning algorithms; S24: Evaluate and optimize the model through cross-validation and evaluation index methods; S25: Regularly update and tune the prediction model in real time.

6. The method for analyzing meteorological data of a wind-solar power plant according to claim 3, characterized in that: The S3 includes: S31: Use the prediction model to make data predictions; S32: Display the data analysis results and prediction results in a visual form.

7. A method for analyzing meteorological data of a wind-solar power plant according to claim 6, characterized in that: The S4 includes: applying the prediction results to the planning, design, operation and maintenance of wind and solar power plants, verifying and adjusting the model according to the actual power generation situation, and forming a closed-loop feedback mechanism.

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