A Boosted Particle Swarm Method for Energy Efficiency Optimization of PRO Systems

The analytical solutions of complex dynamic PRO systems pose challenges to ensuring that maximum power can be harvested in stable, rapid, and efficient ways in response to varying operational environments. In this paper, a boosted particle swarm optimization (BPSO) method with enhanced essential coe...

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Autores principales:	Yingxue Chen, Linfeng Gou
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	pressure retarded osmosis (PRO) metaheuristic algorithms boosted particle swarm optimization optimization Technology T
Acceso en línea:	https://doaj.org/article/9061df3167b74af18037ecf10b98c119
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spelling	oai:doaj.org-article:9061df3167b74af18037ecf10b98c1192021-11-25T17:27:56ZA Boosted Particle Swarm Method for Energy Efficiency Optimization of PRO Systems10.3390/en142276881996-1073https://doaj.org/article/9061df3167b74af18037ecf10b98c1192021-11-01T00:00:00Zhttps://www.mdpi.com/1996-1073/14/22/7688https://doaj.org/toc/1996-1073The analytical solutions of complex dynamic PRO systems pose challenges to ensuring that maximum power can be harvested in stable, rapid, and efficient ways in response to varying operational environments. In this paper, a boosted particle swarm optimization (BPSO) method with enhanced essential coefficients is proposed to enhance the exploration and exploitation stages in the optimization process. Moreover, several state-of-the-art techniques are utilized to evaluate the proposed BPSO of scaled-up PRO systems. The competitive results revealed that the proposed method improves power density by up to 88.9% in comparison with other algorithms, proving its ability to provide superior performance with complex and computationally intensive derivative problems. The analysis and comparison of the popular and recent metaheuristic methods in this study could provide a reference for the targeted selection method for different applications.Yingxue ChenLinfeng GouMDPI AGarticlepressure retarded osmosis (PRO)metaheuristic algorithmsboosted particle swarm optimizationoptimizationTechnologyTENEnergies, Vol 14, Iss 7688, p 7688 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	pressure retarded osmosis (PRO) metaheuristic algorithms boosted particle swarm optimization optimization Technology T
spellingShingle	pressure retarded osmosis (PRO) metaheuristic algorithms boosted particle swarm optimization optimization Technology T Yingxue Chen Linfeng Gou A Boosted Particle Swarm Method for Energy Efficiency Optimization of PRO Systems
description	The analytical solutions of complex dynamic PRO systems pose challenges to ensuring that maximum power can be harvested in stable, rapid, and efficient ways in response to varying operational environments. In this paper, a boosted particle swarm optimization (BPSO) method with enhanced essential coefficients is proposed to enhance the exploration and exploitation stages in the optimization process. Moreover, several state-of-the-art techniques are utilized to evaluate the proposed BPSO of scaled-up PRO systems. The competitive results revealed that the proposed method improves power density by up to 88.9% in comparison with other algorithms, proving its ability to provide superior performance with complex and computationally intensive derivative problems. The analysis and comparison of the popular and recent metaheuristic methods in this study could provide a reference for the targeted selection method for different applications.
format	article
author	Yingxue Chen Linfeng Gou
author_facet	Yingxue Chen Linfeng Gou
author_sort	Yingxue Chen
title	A Boosted Particle Swarm Method for Energy Efficiency Optimization of PRO Systems
title_short	A Boosted Particle Swarm Method for Energy Efficiency Optimization of PRO Systems
title_full	A Boosted Particle Swarm Method for Energy Efficiency Optimization of PRO Systems
title_fullStr	A Boosted Particle Swarm Method for Energy Efficiency Optimization of PRO Systems
title_full_unstemmed	A Boosted Particle Swarm Method for Energy Efficiency Optimization of PRO Systems
title_sort	boosted particle swarm method for energy efficiency optimization of pro systems
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/9061df3167b74af18037ecf10b98c119
work_keys_str_mv	AT yingxuechen aboostedparticleswarmmethodforenergyefficiencyoptimizationofprosystems AT linfenggou aboostedparticleswarmmethodforenergyefficiencyoptimizationofprosystems AT yingxuechen boostedparticleswarmmethodforenergyefficiencyoptimizationofprosystems AT linfenggou boostedparticleswarmmethodforenergyefficiencyoptimizationofprosystems
_version_	1718412362361339904

A Boosted Particle Swarm Method for Energy Efficiency Optimization of PRO Systems

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