Short-term Wind Speed Forecasting Based on Local Gaussian Process

doi:10.3969/j.issn.1006-2475.2017.01.003

Abstract

Abstract: Wind speed forecasting is very important to the operation of wind power plants and power system. A short-term wind speed forecasting method based on local Gaussian process model is proposed. Firstly, the training sample set is divided into many sub training set according to the fixed length of time window. Secondly, the local Gaussian process model is used to forecast the wind speed of each sub training set. By minimizing prediction error of the training set as the optimization goal, the improved PSO algorithm is used to optimize the hyper parameters. The prediction results show that the proposed method can improve the prediction accuracy.

Key words: wind speed forecasting, short-term, local Gaussian process, improved PSO algorithm

CLC Number:

TP391

CHANG Chun1, LI De-sheng2. Short-term Wind Speed Forecasting Based on Local Gaussian Process[J]. Computer and Modernization, doi: 10.3969/j.issn.1006-2475.2017.01.003.

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