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  • 标题:Asymptotically Optimal Scenario-based Multi-objective Optimization for Distributed Generation Allocation and Sizing in Distribution Systems
  • 本地全文:下载
  • 作者:Lizhen Wu ; Xusheng Yang ; Hu Zhou
  • 期刊名称:International Journal of Grid and Distributed Computing
  • 印刷版ISSN:2005-4262
  • 出版年度:2016
  • 卷号:9
  • 期号:4
  • 页码:75-86
  • DOI:10.14257/ijgdc.2016.9.4.07
  • 出版社:SERSC
  • 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.
  • 关键词:Multi-objective optimization; Honey Bee Mating Optimization (HBMO); ; Distributed Generation (DG); Optimal Scenario; Voltage Profile
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