基于多智能体遗传算法的配电网节能降耗综合管理系统  被引量:7

Energy Saving Management System of Distribution Network Based on Multi-agent Genetic Algorithm

在线阅读下载全文

作  者:方璐[1] 詹军[1] 徐先勇[2] 方厚辉[1] 

机构地区:[1]湖南大学现代工程训练中心,湖南长沙410082 [2]国网湖南省电力公司电力科学研究院,湖南长沙410007

出  处:《湖南大学学报(自然科学版)》2016年第4期105-112,共8页Journal of Hunan University:Natural Sciences

基  金:国家自然科学基金资助项目(51507057)~~

摘  要:针对目前企业配电网节能技术的不足,提出了一种基于多智能体遗传算法的配电网节能降耗综合管理系统.结合遗传算法(Genetic algorithm,GA)和多智能体系统(Multi-Agentsystem,MAS)技术构造了一种GA-MAS算法,每一个多智能体相当于遗传算法中一个个体,相邻的多智能体相互作用,并结合遗传算法的进化机理进行全局最优求解.提出了该系统各节能设备智能体结构模型和高压/低压多智能体系结构模型,运用GAMAS算法,得出各个节能设备的最佳调节力度,使节能设备以最小的调节代价获得最大的节能效益.具体算例仿真及工程实际应用表明本文提出的配电网节能降耗综合管理系统能使总有功网损降低,电容器投入总组数减少,实现节能设备的最佳调节,同时表明GA-MAS算法收敛速度较快.Aiming at the deficiency of energy saving technology in enterprise distribution network,an energy saving management system of distribution network based on multi-agent genetic algorithm was proposed.Combined with genetic algorithm and multi-agent system,a GA-MAS algorithm was proposed.Each multi-agent was equivalent to an individual of genetic algorithm,and the adjacent multi-agent was in interaction.The GA-MAS algorithm was combined with the evolutionary mechanism of the genetic algorithm for global optimal solution.The agent structure model of the energy saving equipment and the intelligent architecture model of high/low voltage system were presented.Using the proposed GA-MAS algorithm,the optimal regulation of energy-saving equipment was obtained,so the least cost of the energy-saving equipment had the biggest energy saving profit.The simulation and practical application have shown that the proposed energy saving management system of distribution network can reduce the total active power loss and the total number of capacitors,and achieve the best regulation of energy-saving device.It has also been shown that the proposed GA-MAS algorithm has faster convergence speed.

关 键 词:综合管理系统 节能降耗 节能设备多智能体 遗传算法 

分 类 号:TM92[电气工程—电力电子与电力传动]

 

参考文献:

正在载入数据...

 

二级参考文献:

正在载入数据...

 

耦合文献:

正在载入数据...

 

引证文献:

正在载入数据...

 

二级引证文献:

正在载入数据...

 

同被引文献:

正在载入数据...

 

相关期刊文献:

正在载入数据...

相关的主题
相关的作者对象
相关的机构对象