Optimal Design of Photovoltaic Power Plant Using Hybrid Optimisation: A Case of South Algeria

Considering the recent drop (up to 86%) in photovoltaic (PV) module prices from 2010 to 2017, many countries have shown interest in investing in PV plants to meet their energy demand. In this study, a detailed design methodology is presented to achieve high benefits with low installation, maintenanc...

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Main Authors: Zidane, Tekai Eddine Khalil, Adzman, Mohd Rafi, Tajuddin, Mohammad Faridun Naim, Zali, Samila Mat, Durusu, Ali, Mekhilef, Saad
Format: Article
Published: MDPI 2020
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Online Access:http://eprints.um.edu.my/25695/
https://doi.org/10.3390/en13112776
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Institution: Universiti Malaya
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spelling my.um.eprints.256952021-01-20T04:14:25Z http://eprints.um.edu.my/25695/ Optimal Design of Photovoltaic Power Plant Using Hybrid Optimisation: A Case of South Algeria Zidane, Tekai Eddine Khalil Adzman, Mohd Rafi Tajuddin, Mohammad Faridun Naim Zali, Samila Mat Durusu, Ali Mekhilef, Saad TK Electrical engineering. Electronics Nuclear engineering Considering the recent drop (up to 86%) in photovoltaic (PV) module prices from 2010 to 2017, many countries have shown interest in investing in PV plants to meet their energy demand. In this study, a detailed design methodology is presented to achieve high benefits with low installation, maintenance and operation costs of PV plants. This procedure includes in detail the semi-hourly average time meteorological data from the location to maximise the accuracy and detailed characteristics of different PV modules and inverters. The minimum levelised cost of energy (LCOE) and maximum annual energy are the objective functions in this proposed procedure, whereas the design variables are the number of series and parallel PV modules, the number of PV module lines per row, tilt angle and orientation, inter-row space, PV module type, and inverter structure. The design problem was solved using a recent hybrid algorithm, namely, the grey wolf optimiser-sine cosine algorithm. The high performance for LCOE-based design optimisation in economic terms with lower installation, maintenance and operation costs than that resulting from the use of maximum annual energy objective function by 12%. Moreover, sensitivity analysis showed that the PV plant performance can be improved by decreasing the PV module annual reduction coefficient. © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). MDPI 2020 Article PeerReviewed Zidane, Tekai Eddine Khalil and Adzman, Mohd Rafi and Tajuddin, Mohammad Faridun Naim and Zali, Samila Mat and Durusu, Ali and Mekhilef, Saad (2020) Optimal Design of Photovoltaic Power Plant Using Hybrid Optimisation: A Case of South Algeria. Energies, 13 (11). p. 2776. ISSN 1996-1073 https://doi.org/10.3390/en13112776 doi:10.3390/en13112776
institution Universiti Malaya
building UM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaya
content_source UM Research Repository
url_provider http://eprints.um.edu.my/
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Zidane, Tekai Eddine Khalil
Adzman, Mohd Rafi
Tajuddin, Mohammad Faridun Naim
Zali, Samila Mat
Durusu, Ali
Mekhilef, Saad
Optimal Design of Photovoltaic Power Plant Using Hybrid Optimisation: A Case of South Algeria
description Considering the recent drop (up to 86%) in photovoltaic (PV) module prices from 2010 to 2017, many countries have shown interest in investing in PV plants to meet their energy demand. In this study, a detailed design methodology is presented to achieve high benefits with low installation, maintenance and operation costs of PV plants. This procedure includes in detail the semi-hourly average time meteorological data from the location to maximise the accuracy and detailed characteristics of different PV modules and inverters. The minimum levelised cost of energy (LCOE) and maximum annual energy are the objective functions in this proposed procedure, whereas the design variables are the number of series and parallel PV modules, the number of PV module lines per row, tilt angle and orientation, inter-row space, PV module type, and inverter structure. The design problem was solved using a recent hybrid algorithm, namely, the grey wolf optimiser-sine cosine algorithm. The high performance for LCOE-based design optimisation in economic terms with lower installation, maintenance and operation costs than that resulting from the use of maximum annual energy objective function by 12%. Moreover, sensitivity analysis showed that the PV plant performance can be improved by decreasing the PV module annual reduction coefficient. © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
format Article
author Zidane, Tekai Eddine Khalil
Adzman, Mohd Rafi
Tajuddin, Mohammad Faridun Naim
Zali, Samila Mat
Durusu, Ali
Mekhilef, Saad
author_facet Zidane, Tekai Eddine Khalil
Adzman, Mohd Rafi
Tajuddin, Mohammad Faridun Naim
Zali, Samila Mat
Durusu, Ali
Mekhilef, Saad
author_sort Zidane, Tekai Eddine Khalil
title Optimal Design of Photovoltaic Power Plant Using Hybrid Optimisation: A Case of South Algeria
title_short Optimal Design of Photovoltaic Power Plant Using Hybrid Optimisation: A Case of South Algeria
title_full Optimal Design of Photovoltaic Power Plant Using Hybrid Optimisation: A Case of South Algeria
title_fullStr Optimal Design of Photovoltaic Power Plant Using Hybrid Optimisation: A Case of South Algeria
title_full_unstemmed Optimal Design of Photovoltaic Power Plant Using Hybrid Optimisation: A Case of South Algeria
title_sort optimal design of photovoltaic power plant using hybrid optimisation: a case of south algeria
publisher MDPI
publishDate 2020
url http://eprints.um.edu.my/25695/
https://doi.org/10.3390/en13112776
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