Multi-Objective Optimization of Microgrids Based on Recent Metaheuristic Methods

As the technology develops in the modern world, the need for electrical energy has increased. Renewable energy sources have emerged as an alternative energy source to fossil energy sources. Micro grids are the hybrid energy sources for both renewable and non-renewable energy sources. The choice of t...

Descripción completa

Guardado en:

Detalles Bibliográficos
Autores principales:	Tuba Tanyildizi Ağir*, Zafer Aydoğmuş, Bilal Alataş
Formato:	article
Lenguaje:	EN
Publicado:	Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek 2021
Materias:	hybrid particle swallow swarm optimization meta heuristic algorithms microgrid particle swarm optimization swallow swarm optimization Engineering (General). Civil engineering (General) TA1-2040
Acceso en línea:	https://doaj.org/article/c53ae37dd75242bda58ec5c54e8b2d1c
Etiquetas:	Agregar Etiqueta Sin Etiquetas, Sea el primero en etiquetar este registro!

id	oai:doaj.org-article:c53ae37dd75242bda58ec5c54e8b2d1c
record_format	dspace
spelling	oai:doaj.org-article:c53ae37dd75242bda58ec5c54e8b2d1c2021-11-07T00:33:48ZMulti-Objective Optimization of Microgrids Based on Recent Metaheuristic Methods1330-36511848-6339https://doaj.org/article/c53ae37dd75242bda58ec5c54e8b2d1c2021-01-01T00:00:00Zhttps://hrcak.srce.hr/file/383546https://doaj.org/toc/1330-3651https://doaj.org/toc/1848-6339As the technology develops in the modern world, the need for electrical energy has increased. Renewable energy sources have emerged as an alternative energy source to fossil energy sources. Micro grids are the hybrid energy sources for both renewable and non-renewable energy sources. The choice of the microgrid depends on meeting the supply and low cost requirements while avoiding environmental pollution. Therefore, emission, reliability and sizing of a micro grid have been investigated in the present study. In addition, Swallow Swarm Optimization (SSO) and Hybrid Particle Swallow Swarm Optimization (HPSSO) algorithms were not found in micro grid related optimization studies. Performance of SSO and HPSSO algorithms was also evaluated. Particle Swarm Optimization (PSO), SSO, and HPSSO were adjusted in this study as multi-objective optimization method for increasing the reliability, decreasing emission and sizing energy resources of a microgrid feeding a 10 MW residence. A microgrid consisting of 8 MW solar panel, 4,5 MW wind turbine, 15 MW diesel generator, and 4 MW battery has been taken into consideration. The efficiencies of these algorithms were compared for different iterations and populations. In this study, the best results were obtained with the SSO algorithm. Loss of power supply probability (LPSP) = 0, Renewable factor (RF) = 1, with this algorithm our micro-grid has achieved a safe energy and minimum emission to feed the residence. In addition, a system that connects and disconnects the energy resources in varying load conditions was actualized with the SSO algorithm. With this algorithm LPSP = 0, RF = 1, Psize = 0,001. Maximum reliability, zero emission and minimum sizing of the energy sources in our microgrid were achieved with loads of up to 50%. Moreover, LPSP = 0.39, RF = 0.086, Psize = 0,21 values were obtained for loads 50% and above and good results were obtained for reliability, emission and sizing of energy sources.Tuba Tanyildizi Ağir*Zafer AydoğmuşBilal AlataşFaculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek articlehybrid particle swallow swarm optimizationmeta heuristic algorithmsmicrogridparticle swarm optimizationswallow swarm optimizationEngineering (General). Civil engineering (General)TA1-2040ENTehnički Vjesnik, Vol 28, Iss 6, Pp 1839-1848 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	hybrid particle swallow swarm optimization meta heuristic algorithms microgrid particle swarm optimization swallow swarm optimization Engineering (General). Civil engineering (General) TA1-2040
spellingShingle	hybrid particle swallow swarm optimization meta heuristic algorithms microgrid particle swarm optimization swallow swarm optimization Engineering (General). Civil engineering (General) TA1-2040 Tuba Tanyildizi Ağir* Zafer Aydoğmuş Bilal Alataş Multi-Objective Optimization of Microgrids Based on Recent Metaheuristic Methods
description	As the technology develops in the modern world, the need for electrical energy has increased. Renewable energy sources have emerged as an alternative energy source to fossil energy sources. Micro grids are the hybrid energy sources for both renewable and non-renewable energy sources. The choice of the microgrid depends on meeting the supply and low cost requirements while avoiding environmental pollution. Therefore, emission, reliability and sizing of a micro grid have been investigated in the present study. In addition, Swallow Swarm Optimization (SSO) and Hybrid Particle Swallow Swarm Optimization (HPSSO) algorithms were not found in micro grid related optimization studies. Performance of SSO and HPSSO algorithms was also evaluated. Particle Swarm Optimization (PSO), SSO, and HPSSO were adjusted in this study as multi-objective optimization method for increasing the reliability, decreasing emission and sizing energy resources of a microgrid feeding a 10 MW residence. A microgrid consisting of 8 MW solar panel, 4,5 MW wind turbine, 15 MW diesel generator, and 4 MW battery has been taken into consideration. The efficiencies of these algorithms were compared for different iterations and populations. In this study, the best results were obtained with the SSO algorithm. Loss of power supply probability (LPSP) = 0, Renewable factor (RF) = 1, with this algorithm our micro-grid has achieved a safe energy and minimum emission to feed the residence. In addition, a system that connects and disconnects the energy resources in varying load conditions was actualized with the SSO algorithm. With this algorithm LPSP = 0, RF = 1, Psize = 0,001. Maximum reliability, zero emission and minimum sizing of the energy sources in our microgrid were achieved with loads of up to 50%. Moreover, LPSP = 0.39, RF = 0.086, Psize = 0,21 values were obtained for loads 50% and above and good results were obtained for reliability, emission and sizing of energy sources.
format	article
author	Tuba Tanyildizi Ağir* Zafer Aydoğmuş Bilal Alataş
author_facet	Tuba Tanyildizi Ağir* Zafer Aydoğmuş Bilal Alataş
author_sort	Tuba Tanyildizi Ağir*
title	Multi-Objective Optimization of Microgrids Based on Recent Metaheuristic Methods
title_short	Multi-Objective Optimization of Microgrids Based on Recent Metaheuristic Methods
title_full	Multi-Objective Optimization of Microgrids Based on Recent Metaheuristic Methods
title_fullStr	Multi-Objective Optimization of Microgrids Based on Recent Metaheuristic Methods
title_full_unstemmed	Multi-Objective Optimization of Microgrids Based on Recent Metaheuristic Methods
title_sort	multi-objective optimization of microgrids based on recent metaheuristic methods
publisher	Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek
publishDate	2021
url	https://doaj.org/article/c53ae37dd75242bda58ec5c54e8b2d1c
work_keys_str_mv	AT tubatanyildiziagir multiobjectiveoptimizationofmicrogridsbasedonrecentmetaheuristicmethods AT zaferaydogmus multiobjectiveoptimizationofmicrogridsbasedonrecentmetaheuristicmethods AT bilalalatas multiobjectiveoptimizationofmicrogridsbasedonrecentmetaheuristicmethods
_version_	1718443637950382080

Multi-Objective Optimization of Microgrids Based on Recent Metaheuristic Methods

Ejemplares similares