Optimal sizing of a renewable energy hybrid system in Libya using integrated crow and particle swarm algorithms

Abdurazaq Elbaz; Muhammet Tahir Güneşer

doi:10.25046/aj060130

Optimal sizing of a renewable energy hybrid system in Libya using integrated crow and particle swarm algorithms

Abdurazaq Elbaz^*, Muhammet Tahir Güneşer

^*Corresponding author for this work

Karabuk University

Research output: Contribution to journal › Article › peer-review

2 Citations (Scopus)

Abstract

Sizing optimization should be used to design an efficient, sustainable, and feasible hybrid system. In this paper, a hybrid power plant consisting of an off-grid photovoltaic and wind energy system was planned to supply the demand of residential houses in Libya. To minimize installation and operational costs by sizing each part of the hybrid system, the crow search technique was applied. We optimized the number of photovoltaic modules, wind turbine power, and battery capacity and then we compared the performance of the crow algorithm with the particle swarm optimization algorithm for hybrid system design. The results of the crow algorithm suggest better efficiency for sizing lower-cost hybrid power plants consisting of photovoltaic and wind systems.

Original language	English
Pages (from-to)	264-268
Number of pages	5
Journal	Advances in Science, Technology and Engineering Systems
Volume	6
Issue number	1
DOIs	https://doi.org/10.25046/aj060130
Publication status	Published - 2021
Externally published	Yes

Bibliographical note

Publisher Copyright:
© 2021 ASTES Publishers. All rights reserved.

Keywords

Crow algorithm
Off-grid PV
PSO algorithm
Renewable energy system
Wind energy

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.25046/aj060130

Cite this

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abstract = "Sizing optimization should be used to design an efficient, sustainable, and feasible hybrid system. In this paper, a hybrid power plant consisting of an off-grid photovoltaic and wind energy system was planned to supply the demand of residential houses in Libya. To minimize installation and operational costs by sizing each part of the hybrid system, the crow search technique was applied. We optimized the number of photovoltaic modules, wind turbine power, and battery capacity and then we compared the performance of the crow algorithm with the particle swarm optimization algorithm for hybrid system design. The results of the crow algorithm suggest better efficiency for sizing lower-cost hybrid power plants consisting of photovoltaic and wind systems.",

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AU - Elbaz, Abdurazaq

AU - Güneşer, Muhammet Tahir

PY - 2021

Y1 - 2021

N2 - Sizing optimization should be used to design an efficient, sustainable, and feasible hybrid system. In this paper, a hybrid power plant consisting of an off-grid photovoltaic and wind energy system was planned to supply the demand of residential houses in Libya. To minimize installation and operational costs by sizing each part of the hybrid system, the crow search technique was applied. We optimized the number of photovoltaic modules, wind turbine power, and battery capacity and then we compared the performance of the crow algorithm with the particle swarm optimization algorithm for hybrid system design. The results of the crow algorithm suggest better efficiency for sizing lower-cost hybrid power plants consisting of photovoltaic and wind systems.

AB - Sizing optimization should be used to design an efficient, sustainable, and feasible hybrid system. In this paper, a hybrid power plant consisting of an off-grid photovoltaic and wind energy system was planned to supply the demand of residential houses in Libya. To minimize installation and operational costs by sizing each part of the hybrid system, the crow search technique was applied. We optimized the number of photovoltaic modules, wind turbine power, and battery capacity and then we compared the performance of the crow algorithm with the particle swarm optimization algorithm for hybrid system design. The results of the crow algorithm suggest better efficiency for sizing lower-cost hybrid power plants consisting of photovoltaic and wind systems.

KW - Crow algorithm

KW - Off-grid PV

KW - PSO algorithm

KW - Renewable energy system

KW - Wind energy

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JO - Advances in Science, Technology and Engineering Systems

JF - Advances in Science, Technology and Engineering Systems

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Optimal sizing of a renewable energy hybrid system in Libya using integrated crow and particle swarm algorithms

Abstract

Bibliographical note

Keywords

UN SDGs

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