核主成分回归方法在电力负荷中期预测中的应用

在分析核主成分回归原理及其与最小二乘方法关系的基础上，针对电力负荷中期预测的影响变量间存在着的非线性关系信息，提出使用主成分网归方法进行电力负荷中期预测，一定程度上解决了误差传播的问题，系统的预测精度得到了提高。使用核主成分同归进行了模型实验，探讨了模型训练样本选取、数据处理、参数选择和训练方法等方面的问题，井对实验结果进行了分析讨论。实验表明，在模型不很复杂的情况下，可以使用直接搜索的方法有效地设置应提取的非线性主成分个数p的值。

Application of Kernel Principal Component Regression in Mid-term Load Forecasting

After investigating the mechanism of KPCR and its relation to least square method, this paper proposes mid-term load forecasting with KPCR, where error propagation exists. There are strong no-linear relations between influence factors in mid-term load forecasting. The simulation experiments are done with KPCR, good prediction accuracy is obtained. The paper puts emphasis on the matters about training sample selection, data disposition, model parameter selection, etc. Some explanations are presented on experiment results. In the experiment with simple model, the principal component number p can be set in feature space by way of direct searching.