摘要
利用混沌动力学的随机性和遍历设计群体运动模式,提出一种改进的微粒群算法.以运行成本和网络损耗为目标,对分布式发电的优化选址与定容问题加以求解,获取最优的分布式电源安装位置和容量,并针对标准测试系统进行了仿真计算与分析,仿真结果验证了所提方法的有效性.
An improved particle swarm optimization (PSO) algorithm is proposed by designed particles' movement patterns on the basis of the randomness and ergodic property of chaotic dynamics. With the presented PSO algorithm, the optimal position and capacity of distributed generations in power network could be computed and the objective of minimizing operation cost and network loss could be realized. Simulations based on a standard test system were carried out and its result verified the validity of the proposed method.
出处
《北京理工大学学报》
EI
CAS
CSCD
北大核心
2012年第5期517-521,共5页
Transactions of Beijing Institute of Technology
基金
国家自然科学基金资助项目(61034004
61005090
61075064)
教育部新世纪人才计划项目
国家教育部高等学校博士学科点专项科研基金资助课题(20100072110038)
关键词
微粒群算法
分布式发电
优化配置
particle swarm optimization distributed generation(DG) optimal allocation