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中国管理科学 ›› 2007, Vol. 15 ›› Issue (1): 69-73.

• 论文 • 上一篇    下一篇

粒子群优化灰色模型在负荷预测中的应用

牛东晓, 赵磊, 张博, 王海峰   

  1. 华北电力大学经济管理系, 河北保定071003
  • 收稿日期:2005-10-07 修回日期:2006-01-10 出版日期:2007-02-28 发布日期:2007-02-28
  • 作者简介:牛东晓(1962- ),男(汉族),安徽省宿州市人,华北电力大学工商管理学院院长,博士生导师,教授,研究方向:电力市场.
  • 基金资助:

    国家自然科学基金资助项目(50077007);高等学校博士点专项基金资助项目(20040079008)

The Application of Particle Swarm Optimization Based Grey Model to Power Load Forecasting

NIU Dong-xiao, ZHAO Lei, ZHANG Bo, WANG Hai-feng   

  1. Department of Business Administration, North China Electric Power University, Beijing 102206, China
  • Received:2005-10-07 Revised:2006-01-10 Online:2007-02-28 Published:2007-02-28

摘要: 针对电力系统负荷特性,分析灰色模型GM(1,1)的应用局限性,引入向量α改进灰色模型背景值序列的计算公式,从而构建了适应性更强的GM(1,1,α)模型。应用粒子群优化算法非线性全局寻优能力来求解最优α值,提出了基于粒子群优化算法的灰色模型PSOGM,并给出了电力负荷预测的应用实例。实例证明PSOGM模型具有较高的预测精度和较广的应用范围。

关键词: 负荷预测, 灰色模型, 背景值, 粒子群优化

Abstract: According to the load characteristic of power system and the application limitation of grey model GM(1,1),vector is introduced into the computing formula of background value array. A new model GM (1,1,)which bears higher adaptability is constructed. Particle swarm optimization algorithm is adopted in order to solve the value of a as it has the virtue of optimum-seeking. Then a particle-swarm-optimization-based grey model PSOGM is proposed and practical examples are given. The simulation results indicate that PSOGM model gives better precision and has wider application field.

Key words: power load forecasting, grey model, background value, particle swarm optimization

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