Asymptotically optimal scenario-based multi-objective optimization for distributed generation allocation and sizing in distribution systems

doi:10.14257/ijgdc.2016.9.4.07

	Asymptotically optimal scenario-based multi-objective optimization for distributed generation allocation and sizing in distribution systems
	Wu, Lizhen 1; Yang, Xusheng 1; Zhou, Hu 2; Hao, Xiaohong 1
刊名	International Journal of Grid and Distributed Computing
	2016
卷号	9 期号:4 页码:75-86
关键词	Algorithms Decision trees Distributed power generation Food products Forestry Optimization Particle swarm optimization (PSO) Uncertainty analysis Voltage stabilizing circuits Asymptotically optimal Distribution systems Honey-bee mating optimization Model uncertainties Optimal scenario Voltage profile Voltage stability margins Wasserstein distance
ISSN号	20054262
DOI	10.14257/ijgdc.2016.9.4.07
英文摘要	Suitable location and optimal sizing are impact on voltage stability margin of the distributed system. It is important to accurately simulate the random output active power of Distributed Generation (DG). In order to model uncertainties of intermittent distributed generation and load, this paper proposes a multi-scenario tree model of wind-photovoltaic-load using multiple scenarios technique based on the Wasserstein distance metrics, which generates asymptotically optimal scenario. And in this paper, a multi-objective optimizes control model with scenario tree is presented, which including objectives that are the total active power losses and the voltage deviations of the bus. Moreover, a new hybrid Honey Bee Mating Optimization and Particle Swarm Optimization (HBMO-PSO) algorithm is proposed to solved the problems. In the HBMO-PSO algorithm, the mating process is corrected, which the PSO algorithm is combined with the HBMO algorithm to improve the performance of HBMO. Finally, a typical IEEE 33-bus distribution test system is used to investigate the feasibility and effectiveness of the proposed method. Simulation results illustrate the correctness and adaptability of the proposed model and the improved algorithm. © 2016 SERSC.
WOS研究方向	Computer Science
语种	英语
出版者	Science and Engineering Research Support Society
WOS记录号	WOS:000376347400007
内容类型	期刊论文
源URL	[http://ir.lut.edu.cn/handle/2XXMBERH/112687]
专题	电气工程与信息工程学院
作者单位	1.College of Electrical and Information Engineering of Lanzhou University of Technology, Lanzhou; Gansu, China; 2.Gansu Electric Power Corporation, Lanzhou; Gansu, China
推荐引用方式 GB/T 7714	Wu, Lizhen,Yang, Xusheng,Zhou, Hu,et al. Asymptotically optimal scenario-based multi-objective optimization for distributed generation allocation and sizing in distribution systems[J]. International Journal of Grid and Distributed Computing,2016,9(4):75-86.
APA	Wu, Lizhen,Yang, Xusheng,Zhou, Hu,&Hao, Xiaohong.(2016).Asymptotically optimal scenario-based multi-objective optimization for distributed generation allocation and sizing in distribution systems.International Journal of Grid and Distributed Computing,9(4),75-86.
MLA	Wu, Lizhen,et al."Asymptotically optimal scenario-based multi-objective optimization for distributed generation allocation and sizing in distribution systems".International Journal of Grid and Distributed Computing 9.4(2016):75-86.