文章基本信息

标题：Research of Short-Term Load Forecasting Using DWT and LSSVM Optimized by QDE
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作者：Wei Sun ; Jingyi Sun
期刊名称：International Journal of Smart Home
印刷版ISSN：1975-4094
出版年度：2016
卷号：10
期号：11
页码：133
出版社：SERSC
摘要：To evaluate short-term power load properly and efficiently, this paper proposes a modified DWT-QDE-LSSVM (Discrete wavelet transform (DWT) and least squares support vector machine (LSSVM) optimized by quantum differential evolution (QDE)) model combined with input selected. The load data series of the previous days are first decomposed into an approximation component and a detail component. Then LSSVM is built to model the approximation component and QDE algorithm is applied to overcome the problems faced by LSSVM in selecting parameters. In order to raise forecasting accuracy, this paper proposes the refinement of related factors. The empirical results show that the proposed DWT-QDE-LSSVM model is feasible and can satisfy the short-term load forecasting requirements in China.
关键词：Short-term load forecasting; Quantum differential evolution; Wavelet ;transform; Least squares support vector machine; Refinement