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Short-term wind speed forecasting method of wind farm

A wind speed prediction and wind farm technology, applied in the field of electric power information, can solve the problem that the prediction accuracy cannot reach a satisfactory level, and achieve the effect of reducing data requirements, high accuracy, and short time consumption

Inactive Publication Date: 2010-08-04
ZHEJIANG UNIV
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  • Application Information

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Problems solved by technology

However, these methods also have serious shortcomings, that is, the prediction accuracy cannot reach a satisfactory level.

Method used

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  • Short-term wind speed forecasting method of wind farm
  • Short-term wind speed forecasting method of wind farm
  • Short-term wind speed forecasting method of wind farm

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Experimental program
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Embodiment Construction

[0019] The wind speed of wind farm of the present invention carries out short-term prediction and carries out according to the following steps:

[0020] In step (1), the wind speed data recorded by the wind speed measuring equipment installed in the wind farm is collected, and the time series data of historical wind speed are formed according to the sequence of collection time points. The collection interval between adjacent wind speed data points in the historical wind speed time series can be arbitrarily selected within the range of 10 to 60 minutes, and the data collection interval in each historical wind speed time series is fixed. The time series of the historical wind speed is used as the original data of this forecasting method. Among them, the time series of historical wind speed can be expressed according to formula (1):

[0021] X={x(t), t=1, 2, ..., N.} (1)

[0022] In formula (1), X represents the historical wind speed time series, x(t) represents the wind speed ...

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Abstract

The invention discloses a new short-term wind speed forecasting method of a wind farm, which comprises the following steps: collecting wind speed data of the wind farm, forming the time sequence of the historical wind speed and carrying out normalization treatment; applying the chaos analysis method for analyzing the time sequence of the historical wind speed after the normalization treatment for obtaining phase space reconstruction parameters of a wind power system in the area located by the wind farm, wherein the parameters are delay time and embedding dimension of the time sequence; utilizing the parameters for carrying out treatment on the time sequence of the historical wind speed after the normalization treatment, and obtaining a training sample set required by a support vector regression model for wind speed forecasting; adopting the training sample set for training the support vector regression model; utilizing the support vector regression model after training for carrying out short-term wind speed forecasting on the wind farm, and obtaining the normalized result of the short-term wind speed forecasting of the wind farm; and carrying out anti-normalization treatment on the obtained normalized result of the short-term wind speed forecasting of the wind farm, and obtaining the short-term wind speed forecasting result of the wind farm.

Description

technical field [0001] The invention relates to a short-term wind speed prediction method of a wind farm, which belongs to the technical field of electric power information. Background technique [0002] Wind power is the most competitive renewable energy source in the coming years. The wind energy reserves are huge, and the use of wind energy to generate electricity can not only reduce environmental pollution, but also reduce the fuel cost of the power system, bringing considerable economic benefits. However, wind energy is random and intermittent, and is an unstable energy source. The grid-connection of large-scale wind turbines will bring some negative impacts on the operation of the power system, such as the traditional power system scheduling and optimization of power flow will encounter difficulties. Accurate forecasting of wind power can reduce the impact of wind power on the power grid, and the higher the forecast accuracy, the more negative impacts can be reduced....

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01P5/00
Inventor 王扬郭创新吴栋梁郑晓白峪豪李彦柳
Owner ZHEJIANG UNIV
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