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Short-term wind power forecast method

A wind power forecasting and wind power technology, which is applied in forecasting, instrumentation, data processing applications, etc., can solve the problems that the accuracy of wind power forecasting needs to be improved

Inactive Publication Date: 2014-01-01
STATE GRID CORP OF CHINA +2
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Problems solved by technology

At present, the accuracy of wind power forecasting from the actual site still needs to be improved

Method used

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Embodiment

[0104] The technical scheme of the invention includes two parts, that is, decoupling the wind power by using the local mean value decomposition algorithm and performing prediction model evolution by using the genetic programming algorithm.

[0105] The wind power data of a wind farm for 5 days from May 13 to May 17, 2006 was selected as a sample, and the wind power data of May 18 was used for virtual prediction and comparative analysis. The time resolution of wind power data is every 15 minutes One sampling data point (96 points in 1 day). After the input wind power sample data is preprocessed, it is decomposed by the local mean value decomposition algorithm to obtain each power component. The listed selected wind power sample data and the decomposed power component curves are as follows: figure 2 .

[0106] Relevant factors such as time and wind speed are used as influencing factors, and the genetic programming algorithm is used to perform evolutionary calculations. After t...

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Abstract

The invention relates to a forecast method of a power system, in particular to a short-term wind power forecast method. The short-term wind power forecast method is based on the local mean decomposition algorithm and the genetic program design algorithm and includes the following steps that 1, wind power data are pre-processed; 2, a wind power forecast model is generated, wherein wind power forecast model generation comprises the following steps that (1), the wind power is decoupled in a stabilized mode on the basis of the local mean decomposition algorithm, (2) each component power forecast model is generated on the basis of the genetic program design algorithm, and (3) each component power forecast model is reconstructed so that the wind power forecast model can be obtained; 3, wind power forecast is achieved. According to the short-term wind power forecast method, the accuracy of the current short-term wind power forecast is further improved and the accurate short-term wind power forecast data are offered to a power grid so that a daily power generating plan can be made and safe economic dispatching can be conducted, wherein wind is used by the power grid for power generation.

Description

technical field [0001] The invention relates to a prediction method of an electric power system, in particular to a short-term wind power prediction method. Background technique [0002] Wind power forecasting is based on the historical wind power data of the wind farm, with time, wind speed, weather and other data as the influencing factors to establish the forecasting model of the output power of the wind farm, and these influencing factors are used as the input of the forecasting model to obtain the future of the wind farm. output power. The accuracy of wind power forecasting is of great significance for improving wind power accommodation capacity, stability and economy of power grid operation. At present, the accuracy of wind power forecasting from the actual site still needs to be improved. [0003] Local Mean Decomposition (LMD) is a new adaptive non-stationary signal analysis method proposed by J.S.Smith in 2005. This method decomposes the analyzed signal into pure ...

Claims

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Application Information

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IPC IPC(8): G06Q10/04G06Q50/06
Inventor 范新桥杨雨龙孟杰张文朝范宁宁
Owner STATE GRID CORP OF CHINA
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