Sizing optimization of large-scale grid connected photovoltaic system using dolphin echolocation algorithm / Muhammad Zakyizzuddin Rosselan

Despite being used as large-scale power plant, a common issue of Grid-Connected Photovoltaic (GCPV) system is the system sizing. As numerous models of system components are commercially available, the selection of optimal components has frequently become tedious and time consuming for system designe...

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Main Author:	Rosselan, Muhammad Zakyizzuddin
Format:	Thesis
Language:	English
Published:	2018
Online Access:	https://ir.uitm.edu.my/id/eprint/85811/1/85811.pdf
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id	my-uitm-ir.85811
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spelling	my-uitm-ir.858112023-11-23T05:14:40Z Sizing optimization of large-scale grid connected photovoltaic system using dolphin echolocation algorithm / Muhammad Zakyizzuddin Rosselan 2018 Rosselan, Muhammad Zakyizzuddin Despite being used as large-scale power plant, a common issue of Grid-Connected Photovoltaic (GCPV) system is the system sizing. As numerous models of system components are commercially available, the selection of optimal components has frequently become tedious and time consuming for system designers. Hence, optimization methods are regularly incorporated in the sizing algorithm for such system. This study presents the development of Dolphin Echolocation Algorithm (DEA)-based sizing algorithm for sizing optimization of large-scale GCPV systems. DEA was used to select the optimal combination of the system components which are PV module and inverter such that either the Performance Ratio (PR) or Net Present Value (NPV) is correspondingly optimized. Before incorporating the optimization methods, a sizing algorithm for large-scale GCPV systems was developed. Later, an Iterative-based Sizing Algorithm (ISA) was developed to determine the optimal sizing solution which was later used as benchmark for sizing algorithms using optimization methods. Besides DEA, Evolutionary Programming (EP), Firefly Algorithm (FA) and Cuckoo Search Algorithm (CS) were also incorporated in the sizing algorithm for performance comparison. For each sizing algorithm using these optimization methods, the optimal population size and the number of iterations for convergence were investigated. The results showed that the DEA-based sizing algorithm had successfully found the optimal PR and NPV for the system. Apart from that, sizing algorithm with DEA was also discovered to outperform sizing algorithms with selected computational intelligence, i.e. EP, FA and CS in producing the lowest computation time in finding the optimal sizing solution. Besides having more than 200 times faster than ISA, DEA was found to be approximately 2, 2, 13 times faster than EP, FA and CS respectively. Moreover, DEA was the only Computational Intelligence that is capable of finding the optimal PR and NPV as suggested by the benchmarked algorithm ISA. 2018 Thesis https://ir.uitm.edu.my/id/eprint/85811/ https://ir.uitm.edu.my/id/eprint/85811/1/85811.pdf text en public masters Universiti Teknologi MARA (UiTM) Faculty of Electrical Engineering Sulaiman, Shahril Irwan
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Sulaiman, Shahril Irwan
description	Despite being used as large-scale power plant, a common issue of Grid-Connected Photovoltaic (GCPV) system is the system sizing. As numerous models of system components are commercially available, the selection of optimal components has frequently become tedious and time consuming for system designers. Hence, optimization methods are regularly incorporated in the sizing algorithm for such system. This study presents the development of Dolphin Echolocation Algorithm (DEA)-based sizing algorithm for sizing optimization of large-scale GCPV systems. DEA was used to select the optimal combination of the system components which are PV module and inverter such that either the Performance Ratio (PR) or Net Present Value (NPV) is correspondingly optimized. Before incorporating the optimization methods, a sizing algorithm for large-scale GCPV systems was developed. Later, an Iterative-based Sizing Algorithm (ISA) was developed to determine the optimal sizing solution which was later used as benchmark for sizing algorithms using optimization methods. Besides DEA, Evolutionary Programming (EP), Firefly Algorithm (FA) and Cuckoo Search Algorithm (CS) were also incorporated in the sizing algorithm for performance comparison. For each sizing algorithm using these optimization methods, the optimal population size and the number of iterations for convergence were investigated. The results showed that the DEA-based sizing algorithm had successfully found the optimal PR and NPV for the system. Apart from that, sizing algorithm with DEA was also discovered to outperform sizing algorithms with selected computational intelligence, i.e. EP, FA and CS in producing the lowest computation time in finding the optimal sizing solution. Besides having more than 200 times faster than ISA, DEA was found to be approximately 2, 2, 13 times faster than EP, FA and CS respectively. Moreover, DEA was the only Computational Intelligence that is capable of finding the optimal PR and NPV as suggested by the benchmarked algorithm ISA.
format	Thesis
qualification_level	Master's degree
author	Rosselan, Muhammad Zakyizzuddin
spellingShingle	Rosselan, Muhammad Zakyizzuddin Sizing optimization of large-scale grid connected photovoltaic system using dolphin echolocation algorithm / Muhammad Zakyizzuddin Rosselan
author_facet	Rosselan, Muhammad Zakyizzuddin
author_sort	Rosselan, Muhammad Zakyizzuddin
title	Sizing optimization of large-scale grid connected photovoltaic system using dolphin echolocation algorithm / Muhammad Zakyizzuddin Rosselan
title_short	Sizing optimization of large-scale grid connected photovoltaic system using dolphin echolocation algorithm / Muhammad Zakyizzuddin Rosselan
title_full	Sizing optimization of large-scale grid connected photovoltaic system using dolphin echolocation algorithm / Muhammad Zakyizzuddin Rosselan
title_fullStr	Sizing optimization of large-scale grid connected photovoltaic system using dolphin echolocation algorithm / Muhammad Zakyizzuddin Rosselan
title_full_unstemmed	Sizing optimization of large-scale grid connected photovoltaic system using dolphin echolocation algorithm / Muhammad Zakyizzuddin Rosselan
title_sort	sizing optimization of large-scale grid connected photovoltaic system using dolphin echolocation algorithm / muhammad zakyizzuddin rosselan
granting_institution	Universiti Teknologi MARA (UiTM)
granting_department	Faculty of Electrical Engineering
publishDate	2018
url	https://ir.uitm.edu.my/id/eprint/85811/1/85811.pdf
_version_	1783736380244885504

Sizing optimization of large-scale grid connected photovoltaic system using dolphin echolocation algorithm / Muhammad Zakyizzuddin Rosselan

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