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Wind power cluster power prediction method based on spatio-temporal correlation

A space-time correlation and wind power cluster technology, applied in the field of wind power generation, can solve the problem of low prediction accuracy and achieve the effects of reducing dimensions, improving prediction accuracy, and high prediction accuracy

Active Publication Date: 2022-03-01
HEBEI UNIV OF TECH
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Problems solved by technology

However, this method only considers the influence of wind speed on power and does not consider other factors, so the prediction accuracy is not very high

Method used

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  • Wind power cluster power prediction method based on spatio-temporal correlation
  • Wind power cluster power prediction method based on spatio-temporal correlation
  • Wind power cluster power prediction method based on spatio-temporal correlation

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Embodiment Construction

[0055] The present invention will be further explained below in conjunction with the embodiments and accompanying drawings, but this should not be used as a limitation to the protection scope of the present application.

[0056] In this example, the 2017-2019 wind power data of a wind power cluster in Zhangjiakou, North China, is used to implement and verify the power prediction method for wind power clusters based on spatio-temporal correlation. There are 11 wind farms in this wind power cluster, which are distributed in different regions, and the climate environment, altitude and other environments are also different. Obtain the weather forecast data (wind speed, wind direction, temperature) and wind power generation power of 11 wind farms for three years, and the time interval of the data is 10 minutes. The actual data in 2017 and 2018 are selected as the training sample data, and the actual data in 2019 is used as the test sample. Due to the limited medium and long-term p...

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Abstract

The invention discloses a wind power cluster power prediction method based on time-space correlation. The prediction method analyzes the time-space correlation between wind farms in the wind power cluster, uses various types of correlation calculation methods for calculation, and introduces the Shapley value method for calculation. Weighting makes the correlation evaluation more comprehensive and calculates the correlation in the wind power cluster more accurately. The prediction method considers various factors affecting power generation, and integrates various factors together to extract the overall temporal and spatial correlation characteristics of the wind power cluster, thereby achieving the effect of direct wind power cluster power prediction and avoiding errors caused by superimposed predictions of existing methods The disadvantages of superimposition along with it improve the prediction accuracy. In addition, the convolutional neural network is used to extract the key spatio-temporal features of the wind power cluster to achieve the purpose of reducing the dimension, so that the spatio-temporal features of the wind power cluster can be directly input into the neural network, corresponding to the power of the wind power cluster, and it is more convenient to carry out wind power cluster Generating power forecasting makes forecasting more accurate.

Description

technical field [0001] The invention belongs to the field of wind power generation, and in particular relates to a method for predicting the power of a wind power cluster based on time-space correlation, which accurately predicts the generating power of the wind power cluster according to relevant historical data of the wind power cluster. Background technique [0002] In recent years, wind power generation has developed vigorously around the world. Large-scale wind turbines are distributed in various regions. With the popularization of low-wind-speed wind turbines, large-scale wind turbines can also be installed in areas with low wind speed. With the construction of large-scale wind farms, wind power clusters are also formed. A regional wind power cluster includes multiple wind farms, and large-scale wind farms are connected to the grid, which has a strong impact on grid security and scheduling. [0003] For large-scale wind farms connected to the grid, wind power cluster p...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q10/04G06N3/04G06N3/08G06Q50/06
CPCG06Q10/04G06N3/08G06Q50/06G06N3/045
Inventor 张家安刘东王军燕夏云鹏
Owner HEBEI UNIV OF TECH
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