Short-Term Power Load Forecasting Based on LS-SVM

Bin Liu; Xu Guang

doi:10.1109/isme.2010.86

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JOURNAL ARTICLE

Short-Term Power Load Forecasting Based on LS-SVM

Bin Liu Xu Guang

Year: 2010 Pages: 311-314

DOI: 10.1109/isme.2010.86

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Abstract

In order to solve the Short-term Load Forecasting problems in Power Systems, this article puts forward the Least Squares Support Vector Machine's improved model by selecting the appropriate Gauss kernel function and proposing the error calculation analytical method, thus reduces the computational complicate problems when large amount of data is input in Short-term Power Load Forecasting. An example is given to prove the validity of the algorithm.

Keywords:

Term (time) Support vector machine Computer science Least squares support vector machine Kernel (algebra) Electric power system Power (physics) Gauss Function (biology) Wind power forecasting Mathematical optimization Algorithm Artificial intelligence Mathematics

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Energy Load and Power Forecasting

Physical Sciences → Engineering → Electrical and Electronic Engineering

Advanced Algorithms and Applications

Physical Sciences → Engineering → Control and Systems Engineering

Geoscience and Mining Technology

Physical Sciences → Engineering → Safety, Risk, Reliability and Quality

Short-Term Power Load Forecasting Based on LS-SVM

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