A photovoltaic power generation power prediction method based on support vector machine regression

Abstract

The invention discloses a photovoltaic power generation power prediction method based on support vector machine regression, and the method comprises the steps: firstly, obtaining the historical outputdata and numerical weather forecast data of a target station; Screening out meteorological factors with high correlation from the meteorological factors; Secondly, preprocessing the historical data set, selecting appropriate input parameters, and performing data normalization to construct an input vector of a support vector machine; Calculating correlation degrees between the historical data setand four typical days day by day by using a grey correlation coefficient method; Clustering correlation degree calculation results so as to divide the historical data into four training sets accordingto weather types; Carrying out training modeling on the classified historical samples by adopting a support vector machine regression algorithm to obtain a prediction model; Determining the weather type of the to-be-predicted day through correlation calculation, and calling a corresponding prediction model; And finally, prediction day value weather forecast parameters are input, and a power prediction result is obtained based on a support vector machine regression algorithm and a prediction model.

Description

technical field [0001] The invention relates to the technical field of photovoltaic power generation forecasting, in particular to a photovoltaic power generation power forecasting method based on support vector machine regression. Background technique [0002] Photovoltaic power generation has been widely used due to its advantages of low pollution and flexible scale. However, since the photovoltaic power generation system is significantly affected by environmental factors and has characteristics such as uncertainty, volatility, and intermittency, connecting it to the grid is not conducive to the safe dispatch and energy management of the grid, and increases operational risks. [0003] In view of the above characteristics of photovoltaic power generation, photovoltaic power prediction plays an important role in ensuring the stable operation of the power grid, and many scholars at home and abroad have carried out research on this. At present, the widely used and relatively ...

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Problems solved by technology

[0006] The purpose of the present invention is to provide a photovoltaic power prediction method based on support vector machine regression, aiming at solving the problem that the existing photovoltaic power prediction method adopts the time series method to predict that the prediction accuracy is not ideal, and the artificial neural network takes a long time to train and needs training. Technical issues with high sample similarity

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