| 含有压缩因子的粒子群优化灰色模型在智能电网中的应用 |
| |
| 引用本文： | 王晓佳,张宝霆,徐达宇.含有压缩因子的粒子群优化灰色模型在智能电网中的应用[J].运筹与管理,2012,21(3):114-118. |
| |
| 作者姓名： | 王晓佳 张宝霆 徐达宇 |
| |
| 作者单位： | 1. 合肥工业大学过程优化与智能决策教育部重点实验室,安徽合肥,230009
2. 安徽医科大学,安徽合肥,230032 |
| |
| 基金项目： | 国家863计划重点项目，国家自然科学基金项目，合肥工业大学基金项目 |
| |
| 摘 要： | 针对智能电网对用电量预测的需求和电力系统的负荷特性,在分析了灰色模型GM(1,1)的局限性以及基本粒子群算法在优化GM(1,1)背景值时所出现的不足的基础上,构建了具有压缩因子K的粒子群算法,以此来改进灰色模型的背景值,提出了含有压缩因子的粒子群优化灰色模型KPSO-GM,并把它用于智能电网中用电量预测。实例证明,该算法具有较高的预测精度,有利于提高智能电网的质量。
|
| 关 键 词： | 智能电网 KPSO-GM模型 粒子群 用电量预测 |
Compression Factor with Gray Model of Particle Swarm Optimization and its Application in Smart Grid |
| |
| WANG Xiao-jia
,
ZHANG Bao-ting
,
XU Da-yu.Compression Factor with Gray Model of Particle Swarm Optimization and its Application in Smart Grid[J].Operations Research and Management Science,2012,21(3):114-118. |
| |
| Authors: | WANG Xiao-jia ZHANG Bao-ting XU Da-yu |
| |
| Institution: | 1 (1.Hefei University of Technology,Key Laboratory of Process Optimization and Intelligent Decision-making,Hefei 230009;2.Anhui Medical Univercity,Hefei 230032,China) |
| |
| Abstract: | In connection with the demand of consumption forecasting for smart grid,consider the load characteristics of the power system,this paper analyze the limitation of the GM(1,1)model and the deficiency of particle swarm optimization algorithm when optimizing the grey background value.In order to improve the structural form of background value,this paper utilizes the KPSO-GM model which accordance with compression factor,and it is also used for electricity consumption prediction.Example shows that this model has higher prediction accuracy and can help to improve the quality of smart grid. |
| |
| Keywords: | smart grid KPSO-GM model particle swarm electricity consumption forecasting |
| 本文献已被 CNKI 万方数据 等数据库收录！ |
|
