基于行业聚类电量曲线分解的中期负荷预测  

Medium-Term Load Forecasting Based on Industry Clustering Electricity Curve Decomposition

作　　者：钟士元 张文锦 罗路平 王伟 肖异瑶 廖志伟[2] ZHONG Shiyuan;ZHANG Wenjin;LUO Luping;WANG Wei;XIAO Yiyao;LIAO Zhiwei(Institute of Economy and Technology,State Grid Jiangxi Electric Power Co.,Ltd.,Nanchang 330096,China;School of Electric Power Engineering,South China University of Technology,Guangzhou 510641,China)

机构地区：[1]国网江西省电力有限公司经济技术研究院,南昌市330096 [2]华南理工大学电力学院,广州市510641

出　　处：《电力建设》2022年第2期81-88,共8页Electric Power Construction

基　　金：国家自然科学基金重点项目(51437006)。

摘　　要：传统电量序列分解方法难以有效结合地区行业发展趋势分析,为此文章提出一种基于行业发展趋势的行业聚类电量曲线分解中期负荷预测模型。首先,采用动态时间规整算法计算行业电量周期性,从而分类发展趋势有无变化的行业;其次,通过k-means算法按照用电特性相似聚类预分类行业,并通过季节分解算法分解聚类行业电量序列;最后,针对各电量子序列建立支持向量回归模型,并以江西省某市电量数据作算例分析。算例分析结果表明,文章方法可以分离不同用电特性的行业电量,有助于分析当地行业经济发展状况,并提高地区中期负荷预测准确性。The traditional decomposition method of power consumption sequence is difficult to effectively combine with the analysis of regional industry development trend.Therefore,this paper proposes a medium-term load forecasting model based on the decomposition of the clustering industry electricity curve which combines with the industry development trend.Firstly,the dynamic time warping algorithm is used to calculate the periodicity of the industrial power consumption,to classify the industry which has changed development trend.Secondly,the k-means algorithm is used to cluster pre-classified industries according to similar electricity consumption characteristics,and the seasonal decomposition algorithm is used to decompose the power consumption sequence of the clustering industries.Finally,the support vector regression model is established for each power consumption sub-sequence,and the electricity data of a city in Jiangxi province is taken as an example.The results show that the proposed method can separate the industry power consumption with different electricity consumption characteristics,help to analyze the local industry economic development,and improve the accuracy of regional medium-term load forecasting.

关 键 词：中期负荷预测 行业分类 动态时间规整算法 分解预测 

分 类 号：TM715[电气工程—电力系统及自动化]