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《Automation of Electric Power Systems》 2017-03
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Spatial Load Clustering and Integrated Forecasting Method of Distribution Network Considering Regional Difference

LIU Si;FU Xuhua;YE Chengjin;HUANG Minxiang;College of Electrical Engineering,Zhejiang University;Economic Research Institute of State Grid Zhejiang Electric Power Company;  
In view of the load density method based on intelligent algorithm heavily dependent on the sample and hardly applicable, a spatial load clustering and integrated forecasting method of distribution network considering regional difference is proposed. Firstly,power users and regional information on different cities and different types are obtained through massive investigation. Secondly,according to an analysis of the inadequacy of the current load classification mode, a method based on typical daily load curves is put forward to check the sample load classification label and select the proper samples. Thirdly, a full sample space is constructed by the selected samples, which is further classified into a hierarchical sub-sample space according to a two-level partition of regional property and checked classification label. Finally, a support vector machine( SVM) is built with the most similar sub-sample space to the plot to be predicted, thus the spatial load distribution is obtained. An actual case shows the practicality and effectiveness of the proposed method, which meets the accuracy requirements.
【Fund】: 国家电网公司科技项目(5211JY150016)~~
【CateGory Index】: TM715
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【Citations】
Chinese Journal Full-text Database 10 Hits
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【Co-citations】
Chinese Journal Full-text Database 9 Hits
1 XIA Yan;LI Gengyin;State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources(North China Electric Power University);;Day-ahead Interaction Mode and Simulation in Distribution Network Based on Composite Price[J];电力系统自动化;2017-13
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