基于改进粒子群算法的分布式电源优化配置

Abstract
Figure/Table
References
Related Citation (15)

Download: PDF (4451 KB) HTML (1 KB)
Export: BibTeX | EndNote (RIS)

Abstract The optimal configuration of location and capacity of the distributed generation（DG）can ensure its better technical and economic utility. Based on the detailed analysis on peculiarity of DG, This paper establishes a model of DG which takes the minimal active network loss of DG into consideration. In order to overcome the defect that the Particle Swarm Optimization algorithm depends strongly on the parameter, it this paper uses the Second-selection technology and a novel self-tuned meta heuristic algorithm to adjust the Particle Swarm Optimization algorithm parameters. Finally, the effectiveness of the proposed algorithm are illustrated by experiments.

Key words： distributed generation multi-objective optimization improved particle swarm optimization

Published: 09 December 2015

	Service

	E-mail this article
	Add to my bookshelf
	Add to citation manager
	E-mail Alert
	RSS
	Articles by authors
	Xu Weixing

Cite this article:

Xu Weixing. Optimal Allocation of Distributed Generation based on improved PSO[J]. Electrical Engineering, 2015, 16(12): 71-75.

URL:

https://dqjs.cesmedia.cn/EN/Y2015/V16/I12/71

[1] 余琼, 余胜, 李晓晖. 含分布式电源的配网自适应保护方案[J]. 电力系统保护与控制, 2012, 40(5): 110-115.
[2] 邵珂, 蒋铁铮. 基于细菌菌落优化算法的分布式电源优化配置[J]. 电力学报, 2014, 29(3): 201-205.
[3] H. Ouafa, K. Nadhir, S. Linda and B. Tarek, “Optimal Power Flow with Emission Controlled using Firefly Algorithm”, ICMSAO Tunisia, 978-1-4673-5814-9/13, IEEE, (2013).
[4] Celli G, Pilo F. Optimal distributed Generation allocation in MV distribution networks[C]//Power Industry Computer Applications, 2001. PICA 2001. Innovative Computing for Power-Electric Energy Meets the Market. 22nd IEEE Power Engineering
Society International Conference on, 2, 2001: 81-86.
[5] 刘波, 张焰, 杨娜. 改进的粒子群优化算法在分布式电源选址和定容中的应用[J]. 电工技术学报, 2008, 23(2): 103-108.
[6] 王瑞琪, 李珂, 张承慧, 等. 基于多目标混沌量子遗传算法的分布式电源规划[J]. 电网技术, 2011, 35(12): 183-189.
[7] 杨文荣, 吴海燕, 李练兵, 等. 配电网中基于人工鱼群算法的分布式发电规划[J]. 电力系统保护与控制, 2010, 38(21): 156-161.
[8] 孔涛, 程浩忠, 许童羽. 基于组件式GIS网络分析与多目标遗传算法的城市中压配电网规划[J]. 中国电机工程学报, 2008, 28(19): 49-55.
[9] 李振坤, 陈星莺, 余昆, 等. 配电网重构的混合粒子群算法[J]. 中国电机工程学报, 2008, 28(31): 35-41.
[10] Kennedy J, Eberhart R C. A discrete binary version of the particle swarm algorithm[C]//Systems, Man, and Cybernetics, 1997. Computational Cybernetics and Simulation., 1997 IEEE International Conference on, 5. Orlando, USA, 1997(5): 4104-4108.
[11] 许立雄, 吕林, 刘俊勇. 基于改进粒子群优化算法的配电网络重构[J]. 电力系统自动化, 2006, 30(7): 27-30, 79.
[12] 麻秀范, 崔换君. 改进遗传算法在含分布式电源的配电网规划中的应用[J]. 电工技术学报, 2011, 26(3): 175-181.
[13] 姜文, 严正. 基于一种改进粒子群算法的含风电场电力系统动态经济调度[J]. 电力系统保护与控制, 2010, 38(21): 173-178, 183.