[1]苏士美,王明霞,姚猛,等.基于WHAC-E组合预测模型的短期电力负荷预测[J].郑州大学学报(工学版),2014,35(03):86-90.[doi:10.3969/j.issn.1671-6833.2014.03.021]
　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]
点击复制

基于WHAC-E组合预测模型的短期电力负荷预测()
分享到：

《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
35
期数:
2014年03期
页码:
86-90
栏目:
出版日期:
2014-06-30

文章信息/Info

Title:
Short-term Load Forecasting Based on WHAC-E Combination Model
作者:
苏士美; 王明霞; 姚猛; 张建华
Author(s):
SU Shimei; WANG Mingxia; YAO Meng; ZHANG Jianhua
1. Shool of Electrieal Engineering, Zhengzhou Wnivesity, 2hengzhou 450001, China; 2. Xinxiang Power Supply Company,Xinxiang 450003.China
Keywords:
load foreeasting;  sngle prediction model;  entropy;  wighted harmonie average;  combination fore-casting
分类号:
TM715
DOI:
10.3969/j.issn.1671-6833.2014.03.021
文献标志码:
A
Abstract:
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.
更新日期/Last Update: