[1]SU Shimei,WANG Mingxia,YAO Meng,et al.Short-term Load Forecasting Based on WHAC-E Combination Model[J].Journal of Zhengzhou University (Engineering Science),2014,35(03):86-90.[doi:10.3969/j.issn.1671-6833.2014.03.021]
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Journal of Zhengzhou University (Engineering Science)[ISSN
1671-6833/CN
41-1339/T] Volume:
35
Number of periods:
2014 03
Page number:
86-90
Column:
Public date:
2014-06-30
- Title:
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Short-term Load Forecasting Based on WHAC-E Combination Model
- Author(s):
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SU Shimei; WANG Mingxia; YAO Meng; ZHANG Jianhua
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1. Shool of Electrieal Engineering, Zhengzhou Wnivesity, 2hengzhou 450001, China; 2. Xinxiang Power Supply Company,Xinxiang 450003.China
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- Keywords:
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load foreeasting; sngle prediction model; entropy; wighted harmonie average; combination fore-casting
- CLC:
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TM715
- DOI:
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10.3969/j.issn.1671-6833.2014.03.021
- Abstract:
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This paper proposes four single models, and they are regressive moving averag model, neural net.work model, support vector machine model and partiele swarm oplimization support vector machine model. Wemake use of the thought of non oplimal combination foreeast in operation research, linear combination, theweighted geometrie means combination and the weighted harmonie average portfolio 3 combinations of modelsand other rights law ,a simple weighted average method , the mean square error countdown Franee and entropy4 combinations model weights solving methods are used; Supported by some power company original load logdata and real-time meteorologieal data of some three day, numerieal example analyse and verily that proposedeombination foreeasting model has validity and aeeuraney when it’s used short-term load and it provide a refer.ence for the short-lerm load forecast.