基于改进倍比平滑法的节假日短期负荷预测方法  

Prediction Method of Short-Term Load in Holidays Based on Improved Multiple Proportions Smoothing Method

作　　者：史文博[1] 王健[1] 沈添福 边瑞恩 

机构地区：[1]华南理工大学电力学院,广州市510640

出　　处：《电力建设》2014年第10期21-25,共5页Electric Power Construction

摘　　要：为了提高节假日短期负荷预测精度,提出了基值与归一化曲线结合并加入灰色关联度气象因素修正的负荷预测方法。基值预测时兼顾"重近轻远"的原则,将指数平滑预测改进后应用于节假日负荷预测中,并采用0.618优选法确定平滑系数,对关联日样本进行指数平滑处理;归一化曲线预测时考虑基于相同节假日负荷波动的相似性,引入灰色关联度法分析气象关联性。将该方法应用于广东省某市2011年96点节假日负荷预测,预测结果精度较好,验证了该法的可行性。本模型将正常日的基值与归一化曲线短期负荷预测方法用于节假日负荷预测中,克服了样本贫乏带来的预测精度不高问题,为电力部门节假日负荷预测提供参考。To improve the prediction accuracy of short-term load in holidays, this paper proposed a load prediction method based on the combination of base value and normalized curve, as well as the grey correlation degree of meteorological correction. The principle of ＂ near greater far smaller＂ was also taken into account in the base value prediction, and the index smoothing method was improved and used for the load forecasting in holidays. The smoothing factor was determined using 0. 618 optimization methods, and the samples in correlation days were processed with using index smoothing method. It was suggested that the similarity of load fluctuation in same holidays should be considered and the meteorological correlation should be analyzed with using grey correlation degree, during the prediction of normalized curve. According to 96 points holidays load forecasting for a city in Guangdong province, the accuracy of the prediction method was better, which verified the feasibility of this method. In this model, the base values of normal days and the short-term load forecasting method of normalized curve were used for the load prediction in holidays, which could overcome the problem of poor prediction accuracy caused by poor samples, and could be a reference for the power company to forecast holiday loads.

关 键 词：日负荷曲线 短期负荷预测 节假日 气象修正 归一化曲线 

分 类 号：TM715[电气工程—电力系统及自动化]