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  • 标题:Optimal Placement and Sizing of Distributed Generators Based on Multiobjective Particle Swarm Optimization
  • 本地全文:下载
  • 作者:Deyu Yang ; Junqing Jia ; Wenli Wu
  • 期刊名称:Frontiers in Energy Research
  • 电子版ISSN:2296-598X
  • 出版年度:2021
  • 卷号:9
  • DOI:10.3389/fenrg.2021.770342
  • 语种:English
  • 出版社:Frontiers Media S.A.
  • 摘要:To solve the problems of environmental pollution and energy consumption, the development of renewable energy sources becomes the top priority of current energy transformation. Therefore, distributed power generation has received extensive attention from engineers and researchers. However, the output of distributed generation (DG) is generally random and intermittent, which will cause various degrees of impact on the safe and stable operation of power system when connected to different locations, different capacities, and different types of power grids. Thus, the impact of sizing, type, and location needs to be carefully considered when choosing the optimal DG connection scheme to ensure the overall operation safety, stability, reliability, and efficiency of power grid. This work proposes a distinctive objective function that comprehensively considers power loss, voltage profile, pollution emissions, and DG costs, which is then solved by the multiobjective particle swarm optimization (MOPSO). Finally, the effectiveness and feasibility of the proposed algorithm are verified based on the IEEE 33-bus and 69-bus distribution network.
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