Method for forecasting short-term power in wind power station

Abstract

The invention belongs to the technical field of electric power system forecasting and controlling, in particular relating to a method for forecasting short-term power in a wind power station. The method comprises the following steps: firstly, acquiring actual measured wind speed and power data, and processing the acquired data by adopting a differential autoregressive moving average model and a power forecasting model based on the combination of wavelet transformation and a neural network, thus obtaining a super short-term forecasting power; then acquiring the wind speed, wind direction, air temperature, humidity and atmosphere pressure data of different heights, processing the acquired data by adopting a BP (back propagation) neural network, a self-adaptive fuzzy neural inference system model and a least square support vector machine model through a power combination forecasting method based on a maximal information entropy principle, thus obtaining short-term forecast power; and finally processing the super short-term forecast power, the average error of the super short-term forecast power, the short-term forecast power and the average error of the short-term forecast power which are utilized as input by a combination forecasting method based on the BP neural network, thus obtaining the final short-term forecast power. According to the invention, the accuracy of forecasting power in 72 hours in the future in the wind power station is improved, and a reference is provided for the resonable dispatch of a power grid.

Description

technical field [0001] The invention belongs to the technical field of power system prediction and control, and in particular relates to a short-term power prediction method of a wind farm. Background technique [0002] Wind power generation is a clean and non-polluting renewable energy generation method, which has been paid more and more attention by countries all over the world. The installed capacity of wind power has grown rapidly, and its proportion in the power grid has continued to increase. However, wind power generation also has its disadvantages. Due to the characteristics of wind energy, such as volatility, intermittent, low energy density, and uncontrollability, wind power is also fluctuating and intermittent. The large-capacity wind power connected to the grid will bring some new problems to the safe and stable operation of the power system, especially the obvious impact on the operation and dispatch of the power system. The short-term forecast of wind farm po...

AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to provide a short-term power prediction method for wind farm

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