Optimal Placement and Sizing of Distributed Generators Based on Multiobjective Particle Swarm Optimization

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...

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Autores principales:	Deyu Yang, Junqing Jia, Wenli Wu, Wenchao Cai, Dong An, Ke Luo, Bo Yang
Formato:	article
Lenguaje:	EN
Publicado:	Frontiers Media S.A. 2021
Materias:	distribution network distributed generation optimal sizing and placement multiobjective particle swarm optimization metaheuistic optimization General Works A
Acceso en línea:	https://doaj.org/article/5550abacef684930be559bb07ed44269
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spelling	oai:doaj.org-article:5550abacef684930be559bb07ed442692021-12-01T20:05:30ZOptimal Placement and Sizing of Distributed Generators Based on Multiobjective Particle Swarm Optimization2296-598X10.3389/fenrg.2021.770342https://doaj.org/article/5550abacef684930be559bb07ed442692021-11-01T00:00:00Zhttps://www.frontiersin.org/articles/10.3389/fenrg.2021.770342/fullhttps://doaj.org/toc/2296-598XTo 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.Deyu YangJunqing JiaWenli WuWenchao CaiDong AnKe LuoBo YangFrontiers Media S.A.articledistribution networkdistributed generationoptimal sizing and placementmultiobjective particle swarm optimizationmetaheuistic optimizationGeneral WorksAENFrontiers in Energy Research, Vol 9 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	distribution network distributed generation optimal sizing and placement multiobjective particle swarm optimization metaheuistic optimization General Works A
spellingShingle	distribution network distributed generation optimal sizing and placement multiobjective particle swarm optimization metaheuistic optimization General Works A Deyu Yang Junqing Jia Wenli Wu Wenchao Cai Dong An Ke Luo Bo Yang Optimal Placement and Sizing of Distributed Generators Based on Multiobjective Particle Swarm Optimization
description	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.
format	article
author	Deyu Yang Junqing Jia Wenli Wu Wenchao Cai Dong An Ke Luo Bo Yang
author_facet	Deyu Yang Junqing Jia Wenli Wu Wenchao Cai Dong An Ke Luo Bo Yang
author_sort	Deyu Yang
title	Optimal Placement and Sizing of Distributed Generators Based on Multiobjective Particle Swarm Optimization
title_short	Optimal Placement and Sizing of Distributed Generators Based on Multiobjective Particle Swarm Optimization
title_full	Optimal Placement and Sizing of Distributed Generators Based on Multiobjective Particle Swarm Optimization
title_fullStr	Optimal Placement and Sizing of Distributed Generators Based on Multiobjective Particle Swarm Optimization
title_full_unstemmed	Optimal Placement and Sizing of Distributed Generators Based on Multiobjective Particle Swarm Optimization
title_sort	optimal placement and sizing of distributed generators based on multiobjective particle swarm optimization
publisher	Frontiers Media S.A.
publishDate	2021
url	https://doaj.org/article/5550abacef684930be559bb07ed44269
work_keys_str_mv	AT deyuyang optimalplacementandsizingofdistributedgeneratorsbasedonmultiobjectiveparticleswarmoptimization AT junqingjia optimalplacementandsizingofdistributedgeneratorsbasedonmultiobjectiveparticleswarmoptimization AT wenliwu optimalplacementandsizingofdistributedgeneratorsbasedonmultiobjectiveparticleswarmoptimization AT wenchaocai optimalplacementandsizingofdistributedgeneratorsbasedonmultiobjectiveparticleswarmoptimization AT dongan optimalplacementandsizingofdistributedgeneratorsbasedonmultiobjectiveparticleswarmoptimization AT keluo optimalplacementandsizingofdistributedgeneratorsbasedonmultiobjectiveparticleswarmoptimization AT boyang optimalplacementandsizingofdistributedgeneratorsbasedonmultiobjectiveparticleswarmoptimization
_version_	1718404572871917568

Optimal Placement and Sizing of Distributed Generators Based on Multiobjective Particle Swarm Optimization

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