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Combination Forecasting Model for Mid-long Term Load Based on Least Squares Support Vector Machines and a Mended Particle Swarm Optimization Algorithm

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3 Author(s)
Dongxiao Niu ; Sch. of Bus. & Manage., North China Electr. Power Univ., Beijing, China ; Haitao Lv ; Yunyun Zhang

Mid-long term load forecasting (MTLF) plays an important role in power system. With more factors involved, single forecasting method becomes hard to satisfy requirement. This paper proposes a new combination model for MTLF based on least squares support vector machines (LS-SVM) and particle swarm optimization (PSO) algorithm. LS-SVM is a new kind of SVM which regresses faster than standard, and a mended particle swarm optimization (MPSO) algorithm is employed to optimize the parameters of LS-SVM. With a real case test, the result shows proposed model outperforms tradition combination model.

Published in:

Bioinformatics, Systems Biology and Intelligent Computing, 2009. IJCBS '09. International Joint Conference on

Date of Conference:

3-5 Aug. 2009

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