基于半参数分析的电力需求预测算法

市场经济对电力需求预测提出了更高的要求。在简要介绍和评论以往国内外常用电力需求预测方法优缺点基础上,为了提高电力需求预测的准确度及预测方法的适应性,建立半参数回归模型预测电力需求。半参数回归模型分为线性和非线性两部分。线性部分反映了负荷预测可知的部分规律,非线性部分反映了负荷预测的不确定因素的影响。用偏残差方法估计半参数回归模型,估计结果由两步得到。首先估计线性参数部分,然后再估计非线性参数部分。通过示例计算,半参数回归模型对电力需求预测的估计误差数值小于二元线性回归法对电力需求预测的估计误差。结果表明:利用半参数回归法预测电力需求是一种预测精度高、计算容易、普适性强的算法。

Predictive Calculation Technique for Electric Power Demand Based on Analysis of Semi-parametric Regression

Market economy highly requires more precise prediction of electric power demand. The advantage and disadvantage of prediction models previous used both at home and abroad were briefly introduced. In order to make the prediction more precise and feasible, a semi-parametric model for predicting the electric power demand composed of linear parameter and non-linear parameter was established. Linear parameter reflected the understandable regularity of load prediction while the non-linear parameter reflected the impact of uncertain factors of the load prediction. The semi-parametric model was estimated by the method of partial residual deviation. Estimation was obtained by two steps. The part of linear parameter was estimated first followed by the estimation of the part of non-linear parameter. The exemplified calculation showed that the estimation deviation by sinai-parametric model regression is rather mall, and even mailer than that obtained from binary linear regression. The result showed that this method is more precise, and easy-to-calculate with good adaptability.