基于Hilbert-Huang变换和最小二乘支持向量机的电力市场出清电价预测

随着世界各国电力工业改革的发展趋势,我国于20世纪90年代也开始了以打破垄断、引入竞争、放松管制为目标的电力市场化改革。如何合理制定相应的运营模式以及怎样根据电力市场的相关历史数据准确的预测出未来的市场出清电价,对于市场中的各个参与者都具有十分重要的意义。而实际电力市场的出清电价数据具有很强的非平稳性,Hilbert-Huang变换是分析处理非平稳性信号数据非常有效的方法,本文应用Hilbert-Huang变换首先对电力市场出清电价数据进行平稳化处理,然后运用最小二乘支持向量机（LS-SVM）对处理后的数据进行预测。预测结果表明,此模型显著的提高了出清电价预测的精度。

Market clearing price forecasting using Hilbert-Huang transform and least squares support vector machine

Nowadays,in the word,a profound change of electric power industry mechanisms is taking place.China attempted to have a reformation of electric power market in 1990s,Breaking the traditional integrative management mode,and carrying out separation of net and plant,Transition and distribution.How to establish corresponding electricity market operation mode rationally and how to use the relative historic data to forecast the future market clearing electricity price is a very meaningful work for every participator in the power market.But,because of the non-stationary of Market Clearing price,the method for nonlinear and non-stationary data processing,the Hilbert-Huang Transform（HHT）,is applied to analyze a typical nonlinear system of Market Clearing price.The least squares support vector machine is used to predict the processed data of Market Clearing price in this paper.The simulation result showed that this model improve the forecasting accurate of Market Clearing price remarkablly.