【摘要】 根据电力负荷的周期性与随机性,提出了基于二维小波变换和最小二乘支持向量机的电力系统短期负荷预测方法。首先构造负荷序列二维矩阵,利用二维小波变换将负荷矩阵分解为基荷低频、每天变化的高频、每个时刻变化的高频、随机干扰四个分量,根据重构后负荷分量的特点,构造不同的最小二乘支持向量机模型进行预测;最后将预测后的数据进行叠加得到预测结果。实际预测结果表明该方法具有较高的预测精度和较强的适应能力。更多还原

【Abstract】 According to randomness and periodicity of power load,a new method for short-term load forecasting is proposed based on 2-D wavelet transform and least square support vector machine(LS-SVM).At first,the load series matrix is decomposed into 4 components based on 2-D wavelet transform,then every component is reconstructed and according to the characteristics of the series,the different LS-SVM models are established to forecast load,finally the ultimate forecasting result is obtained after the forecasted load is superposed.The real forecasting result shows that the proposed method is much more accurate and validate,and it also can decrease the risk of the forecasting,so it is an effective method for short-term load forecasting.更多还原