Short-term wind power integrated prediction method and system based on error correction

A technology for wind power forecasting and wind power power, which is applied in forecasting, genetic laws, genetic models, etc., can solve problems such as large forecast errors, and achieve the effects of improving accommodation capacity, improving forecast accuracy, and optimizing power generation plans.

Inactive Publication Date: 2021-09-07
SHANDONG UNIV
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  • Abstract
  • Description
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  • Application Information

AI Technical Summary

Problems solved by technology

[0006] In order to solve the above problems, the present invention proposes a short-term wind power integrated prediction method and system based on error correction, which comprehensively utilizes the XGBoost model and the random forest model in the integrated learning algorithm to predict wind power, avoiding the single prediction model in a certain The shortcomings of large prediction errors at some points, and the method of residual learning to improve the accuracy of short-term wind power prediction

Method used

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  • Short-term wind power integrated prediction method and system based on error correction
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  • Short-term wind power integrated prediction method and system based on error correction

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Embodiment 1

[0051] According to an embodiment of the present invention, a short-term wind power integrated prediction method based on error correction is disclosed, referring to figure 1 , including the following steps:

[0052] (1) Obtain real-time wind farm operation data and weather forecast data;

[0053] Specifically, wind farm operation and numerical weather prediction data refer to any data related to wind power generation, including but not limited to: wind farm power generation, wind direction, wind speed, temperature, humidity, and air pressure.

[0054] (2) input the data into the trained wind power prediction model and the wind power error prediction model respectively for prediction;

[0055] Specifically, the operation and numerical weather forecast data of the wind farm within the preset time period are collected, and the data of meteorological elements such as 10-meter wind speed and 100-meter wind speed are extracted.

[0056] The historical data set is divided into two p...

Embodiment 2

[0154] According to an embodiment of the present invention, a short-term wind power integrated prediction system based on error correction is disclosed, including:

[0155] The data acquisition module is used to acquire the operation data and weather forecast data of the wind farm;

[0156] A model prediction module, used to input the data into the trained wind power prediction model and wind power error prediction model respectively for prediction;

[0157] The data output module is used to add the prediction results output by the two models as the final short-term wind power prediction result;

[0158] Among them, the training data set of the wind power prediction model is the historical operation data and weather data within the preset time period of the wind farm; the historical operation data and weather data within the preset time period of the wind farm are input into the wind power prediction model, and the output wind power The predicted value is based on the predict...

Embodiment 3

[0161] According to an embodiment of the present invention, an embodiment of a terminal device is disclosed, which includes a processor and a memory, the processor is used to implement instructions; the memory is used to store multiple instructions, and the instructions are suitable for being loaded and executed by the processor The short-term wind power integrated forecasting method based on error correction described in the first embodiment.

[0162] In some other embodiments, a computer-readable storage medium is disclosed, in which a plurality of instructions are stored, and the instructions are suitable for being loaded by a processor of a terminal device and executing the error correction-based short-term Wind Power Integrated Forecasting Method.

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Abstract

The invention discloses a short-term wind power integrated prediction method and system based on error correction. The method comprises the following steps: acquiring operation data and weather forecast data of a wind power plant; respectively inputting the data into a trained wind power prediction model and a trained wind power error prediction model for prediction; and adding prediction results output by the two models to serve as a final short-term wind power prediction result, wherein the training data set of the wind power prediction model is historical operation data and weather data of the wind power plant in a preset time period, and the power error data set, historical operation data of the wind power plant in a preset time period and weather data serve as a training data set of the wind power error prediction model. According to the method, the short-term wind power prediction precision is improved, and the absorption capability of the power grid on new energy power generation is improved.

Description

technical field [0001] The invention relates to the technical field of wind power prediction in the process of new energy power generation, in particular to a short-term wind power integrated prediction method and system based on error correction. Background technique [0002] The statements in this section merely provide background information related to the present invention and do not necessarily constitute prior art. [0003] With the increasingly prominent environmental problems and the continuous growth of energy demand, the development of new energy represented by wind power has become the consensus of all countries in the world. Wind energy has the advantages of non-pollution, renewable, and extensive resources, and has been vigorously developed and applied by many countries. However, the output power of wind power has strong randomness and volatility. The uncertainty of operation has increased significantly, and the contradiction between the safe operation of the s...

Claims

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Application Information

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Patent Type & AuthorityApplications(China)
IPC IPC(8): G06Q10/04G06Q50/06G06K9/62G06N3/12
CPCG06Q10/04G06Q50/06G06N3/126G06F18/24323
Inventor杨明丁婷婷于一潇李鹏
OwnerSHANDONG UNIV