Optimal Sizing of a Hybrid Renewable Photovoltaic-Wind System-Based Microgrid Using Harris Hawk Optimizer

Hybrid renewable energy microgrid has become an attractive solution to electrify urban areas. This research proposes a microgrid design problem including photovoltaic (PV) arrays, wind turbine, diesel, and batteries for which Harris hawk optimization (HHO), a metaheuristic technique, is applied. Bas...

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Main Authors: Abdullrahman A. Al-Shamma’a, Hassan M. Hussein Farh, Abdullah M. Noman, Abdullah M. Al-Shaalan, Abdulaziz Alkuhayli
Format: Article
Language:English
Published: Wiley 2022-01-01
Series:International Journal of Photoenergy
Online Access:http://dx.doi.org/10.1155/2022/4825411
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author Abdullrahman A. Al-Shamma’a
Hassan M. Hussein Farh
Abdullah M. Noman
Abdullah M. Al-Shaalan
Abdulaziz Alkuhayli
author_facet Abdullrahman A. Al-Shamma’a
Hassan M. Hussein Farh
Abdullah M. Noman
Abdullah M. Al-Shaalan
Abdulaziz Alkuhayli
author_sort Abdullrahman A. Al-Shamma’a
collection DOAJ
description Hybrid renewable energy microgrid has become an attractive solution to electrify urban areas. This research proposes a microgrid design problem including photovoltaic (PV) arrays, wind turbine, diesel, and batteries for which Harris hawk optimization (HHO), a metaheuristic technique, is applied. Based on a long-term techno-economic assessment, the HHO approach is used to determine the best hybrid microgrid size for a community in Saudi Arabia’s northern region. The efficacy of HHO is investigated, and its performance was compared with seven metaheuristic techniques, grasshopper optimization algorithm (GOA), cuckoo search optimizer (CSO), genetic algorithm (GA), Big Bang–Big Crunch (BBBC), coyote optimizer, crow search, and butterfly optimization algorithm (BOA), to attain the HRE microgrid optimal sizing based on annualized system cost (ASC) reduction. Some benchmarks (optimum and worst solutions, mean, median, standard deviation, and rate of convergence) are used to distinguish and analyze the performance of these eight metaheuristic-based approaches. The HHO surpassed the other seven metaheuristic techniques in achieving the best HRE microgrid solution with the lowest ASC (USD 149229.9) followed by GOA (USD 149380.5) and CSO (USD 149382.5). The findings revealed that the HHO, GOA, CSO, and coyote have acceptable performance in terms of capturing the global solution and the speed of convergence, with only minimal oscillations. The BBBC, crow search, GA, and BA, on the other hand, have unacceptably poor performance, trapping to the local solution, oscillations, and a long convergence time. In terms of optimal solution and convergence rate, the BBBC and GA both perform poorly when compared to the other metaheuristic techniques.
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spelling doaj-art-5d08b952c20246aeaf661c870475d3982025-02-03T06:05:01ZengWileyInternational Journal of Photoenergy1687-529X2022-01-01202210.1155/2022/4825411Optimal Sizing of a Hybrid Renewable Photovoltaic-Wind System-Based Microgrid Using Harris Hawk OptimizerAbdullrahman A. Al-Shamma’a0Hassan M. Hussein Farh1Abdullah M. Noman2Abdullah M. Al-Shaalan3Abdulaziz Alkuhayli4Department of Electrical EngineeringDepartment of Electrical EngineeringDepartment of Electrical EngineeringDepartment of Electrical EngineeringDepartment of Electrical EngineeringHybrid renewable energy microgrid has become an attractive solution to electrify urban areas. This research proposes a microgrid design problem including photovoltaic (PV) arrays, wind turbine, diesel, and batteries for which Harris hawk optimization (HHO), a metaheuristic technique, is applied. Based on a long-term techno-economic assessment, the HHO approach is used to determine the best hybrid microgrid size for a community in Saudi Arabia’s northern region. The efficacy of HHO is investigated, and its performance was compared with seven metaheuristic techniques, grasshopper optimization algorithm (GOA), cuckoo search optimizer (CSO), genetic algorithm (GA), Big Bang–Big Crunch (BBBC), coyote optimizer, crow search, and butterfly optimization algorithm (BOA), to attain the HRE microgrid optimal sizing based on annualized system cost (ASC) reduction. Some benchmarks (optimum and worst solutions, mean, median, standard deviation, and rate of convergence) are used to distinguish and analyze the performance of these eight metaheuristic-based approaches. The HHO surpassed the other seven metaheuristic techniques in achieving the best HRE microgrid solution with the lowest ASC (USD 149229.9) followed by GOA (USD 149380.5) and CSO (USD 149382.5). The findings revealed that the HHO, GOA, CSO, and coyote have acceptable performance in terms of capturing the global solution and the speed of convergence, with only minimal oscillations. The BBBC, crow search, GA, and BA, on the other hand, have unacceptably poor performance, trapping to the local solution, oscillations, and a long convergence time. In terms of optimal solution and convergence rate, the BBBC and GA both perform poorly when compared to the other metaheuristic techniques.http://dx.doi.org/10.1155/2022/4825411
spellingShingle Abdullrahman A. Al-Shamma’a
Hassan M. Hussein Farh
Abdullah M. Noman
Abdullah M. Al-Shaalan
Abdulaziz Alkuhayli
Optimal Sizing of a Hybrid Renewable Photovoltaic-Wind System-Based Microgrid Using Harris Hawk Optimizer
International Journal of Photoenergy
title Optimal Sizing of a Hybrid Renewable Photovoltaic-Wind System-Based Microgrid Using Harris Hawk Optimizer
title_full Optimal Sizing of a Hybrid Renewable Photovoltaic-Wind System-Based Microgrid Using Harris Hawk Optimizer
title_fullStr Optimal Sizing of a Hybrid Renewable Photovoltaic-Wind System-Based Microgrid Using Harris Hawk Optimizer
title_full_unstemmed Optimal Sizing of a Hybrid Renewable Photovoltaic-Wind System-Based Microgrid Using Harris Hawk Optimizer
title_short Optimal Sizing of a Hybrid Renewable Photovoltaic-Wind System-Based Microgrid Using Harris Hawk Optimizer
title_sort optimal sizing of a hybrid renewable photovoltaic wind system based microgrid using harris hawk optimizer
url http://dx.doi.org/10.1155/2022/4825411
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