Optimal sizing of stand-alone photovoltaic system by minimizing the loss of power supply probability

This paper presents Firefly Algorithm-based Sizing Algorithm (FASA) for sizing optimization of a Stand-Alone Photovoltaic (SAPV) system. Firefly Algorithm (FA) was used to optimally select the model of each system component such that a technical performance indicator is consequently optimized. Prior...

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Published in:Solar Energy
Main Author: Abdul Aziz N.I.; Sulaiman S.I.; Shaari S.; Musirin I.; Sopian K.
Format: Article
Language:English
Published: Elsevier Ltd 2017
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-85018771332&doi=10.1016%2fj.solener.2017.04.021&partnerID=40&md5=55b7ac74350441b128534d97cb77e686
id 2-s2.0-85018771332
spelling 2-s2.0-85018771332
Abdul Aziz N.I.; Sulaiman S.I.; Shaari S.; Musirin I.; Sopian K.
Optimal sizing of stand-alone photovoltaic system by minimizing the loss of power supply probability
2017
Solar Energy
150

10.1016/j.solener.2017.04.021
https://www.scopus.com/inward/record.uri?eid=2-s2.0-85018771332&doi=10.1016%2fj.solener.2017.04.021&partnerID=40&md5=55b7ac74350441b128534d97cb77e686
This paper presents Firefly Algorithm-based Sizing Algorithm (FASA) for sizing optimization of a Stand-Alone Photovoltaic (SAPV) system. Firefly Algorithm (FA) was used to optimally select the model of each system component such that a technical performance indicator is consequently optimized. Prior to implementation of FASA, an Iterative-based Sizing Algorithms known as ISA had been developed to determine the optimal solutions which were used as benchmark for FASA. Although ISA was capable in determining the optimal design solutions when there are numerous models for each system component being considered, the computation time of ISA can be very long as ISA tested every possible combination of PV module, battery, charge controller and inverter during sizing process. Therefore, FASA was introduced to accelerate the sizing optimization for SAPV system. FA was incorporated into sizing algorithm with the technical performance indicator was set to optimize the Loss of Power Supply Probability (LPSP). Besides that, two design cases of PV-battery system, i.e. system with standard charge controller denoted as Case 1 and system with MPPT-based charge controller denoted as Case 2 were investigated. The results showed that FASA had successfully found the optimal LPSP in all design cases. In addition, sizing algorithm with FA was also discovered to outperform sizing algorithm with selected computational intelligence in producing the lowest computation time in the sizing optimization. © 2017 Elsevier Ltd
Elsevier Ltd
0038092X
English
Article

author Abdul Aziz N.I.; Sulaiman S.I.; Shaari S.; Musirin I.; Sopian K.
spellingShingle Abdul Aziz N.I.; Sulaiman S.I.; Shaari S.; Musirin I.; Sopian K.
Optimal sizing of stand-alone photovoltaic system by minimizing the loss of power supply probability
author_facet Abdul Aziz N.I.; Sulaiman S.I.; Shaari S.; Musirin I.; Sopian K.
author_sort Abdul Aziz N.I.; Sulaiman S.I.; Shaari S.; Musirin I.; Sopian K.
title Optimal sizing of stand-alone photovoltaic system by minimizing the loss of power supply probability
title_short Optimal sizing of stand-alone photovoltaic system by minimizing the loss of power supply probability
title_full Optimal sizing of stand-alone photovoltaic system by minimizing the loss of power supply probability
title_fullStr Optimal sizing of stand-alone photovoltaic system by minimizing the loss of power supply probability
title_full_unstemmed Optimal sizing of stand-alone photovoltaic system by minimizing the loss of power supply probability
title_sort Optimal sizing of stand-alone photovoltaic system by minimizing the loss of power supply probability
publishDate 2017
container_title Solar Energy
container_volume 150
container_issue
doi_str_mv 10.1016/j.solener.2017.04.021
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-85018771332&doi=10.1016%2fj.solener.2017.04.021&partnerID=40&md5=55b7ac74350441b128534d97cb77e686
description This paper presents Firefly Algorithm-based Sizing Algorithm (FASA) for sizing optimization of a Stand-Alone Photovoltaic (SAPV) system. Firefly Algorithm (FA) was used to optimally select the model of each system component such that a technical performance indicator is consequently optimized. Prior to implementation of FASA, an Iterative-based Sizing Algorithms known as ISA had been developed to determine the optimal solutions which were used as benchmark for FASA. Although ISA was capable in determining the optimal design solutions when there are numerous models for each system component being considered, the computation time of ISA can be very long as ISA tested every possible combination of PV module, battery, charge controller and inverter during sizing process. Therefore, FASA was introduced to accelerate the sizing optimization for SAPV system. FA was incorporated into sizing algorithm with the technical performance indicator was set to optimize the Loss of Power Supply Probability (LPSP). Besides that, two design cases of PV-battery system, i.e. system with standard charge controller denoted as Case 1 and system with MPPT-based charge controller denoted as Case 2 were investigated. The results showed that FASA had successfully found the optimal LPSP in all design cases. In addition, sizing algorithm with FA was also discovered to outperform sizing algorithm with selected computational intelligence in producing the lowest computation time in the sizing optimization. © 2017 Elsevier Ltd
publisher Elsevier Ltd
issn 0038092X
language English
format Article
accesstype
record_format scopus
collection Scopus
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