Firefly algorithm for optimal sizing of Standalone Photovoltaic System / Nurizzati Abdul Aziz

Although Stand-Alone Photovoltaic (SAPV) systems are frequently used as a mode of electrification in rural areas which are deprived of conventional grid electricity, a common issue of such systems is the system sizing. If the system is poorly designed, the system operation would be interrupted, thus...

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Main Author: Abdul Aziz, Nurizzati
Format: Thesis
Language:English
Published: 2016
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Online Access:https://ir.uitm.edu.my/id/eprint/18844/1/TM_NUR%20IZZATI%20ABDUL%20AZIZ%20EE%2016_5.pdf
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spelling my-uitm-ir.188442018-02-04T02:28:58Z Firefly algorithm for optimal sizing of Standalone Photovoltaic System / Nurizzati Abdul Aziz 2016 Abdul Aziz, Nurizzati Photovoltaic power systems Although Stand-Alone Photovoltaic (SAPV) systems are frequently used as a mode of electrification in rural areas which are deprived of conventional grid electricity, a common issue of such systems is the system sizing. If the system is poorly designed, the system operation would be interrupted, thus reducing the overall reliability of the system as a power supply entity. In addition, as there are numerous models of system components in the market, selection of the optimal model for each component has always become a tedious and time consuming for system designers. Therefore, optimization methods are often used in the sizing algorithms for such systems. This study presents the development of Firefly Algorithm-based Sizing Algorithm, known as FASA for sizing optimization of SAPV systems. The sizing algorithm utilized Firefly Algorithm (FA) to optimally select the model of each system component such that a system technical performance indicator is consequently optimized. FA was incorporated in two sizing approaches, i.e. the intuitive method and the hybrid intuitive-deterministic method with the technical performance indicator set as Performance Ratio (PR) and Loss of Power Supply Probability (LPSP) respectively. Besides that, two design cases of PV-battery system, i.e. system with standard charge controller and system with MPPT-based charge controller were investigated. Apart from that, Iterative-based Sizing Algorithms (ISA) for each design case with the two sizing approaches were developed to determine the optimal solutions which were used as benchmark for FASA. The results showed that FASA had successfully found the optimal PR and LPSP in all design cases using both intuitive and hybrid intuitive-deterministic methods. In addition, sizing algorithm with FA was also discovered to outperform sizing algorithm with selected computational intelligence, i.e. Genetic Algorithm, Evolutionary Programming and Particle Swarm Optimization in producing the lowest computation time in the sizing optimization. 2016 Thesis https://ir.uitm.edu.my/id/eprint/18844/ https://ir.uitm.edu.my/id/eprint/18844/1/TM_NUR%20IZZATI%20ABDUL%20AZIZ%20EE%2016_5.pdf text en public mphil masters Universiti Teknologi MARA Faculty of Electrical Engineering
institution Universiti Teknologi MARA
collection UiTM Institutional Repository
language English
topic Photovoltaic power systems
spellingShingle Photovoltaic power systems
Abdul Aziz, Nurizzati
Firefly algorithm for optimal sizing of Standalone Photovoltaic System / Nurizzati Abdul Aziz
description Although Stand-Alone Photovoltaic (SAPV) systems are frequently used as a mode of electrification in rural areas which are deprived of conventional grid electricity, a common issue of such systems is the system sizing. If the system is poorly designed, the system operation would be interrupted, thus reducing the overall reliability of the system as a power supply entity. In addition, as there are numerous models of system components in the market, selection of the optimal model for each component has always become a tedious and time consuming for system designers. Therefore, optimization methods are often used in the sizing algorithms for such systems. This study presents the development of Firefly Algorithm-based Sizing Algorithm, known as FASA for sizing optimization of SAPV systems. The sizing algorithm utilized Firefly Algorithm (FA) to optimally select the model of each system component such that a system technical performance indicator is consequently optimized. FA was incorporated in two sizing approaches, i.e. the intuitive method and the hybrid intuitive-deterministic method with the technical performance indicator set as Performance Ratio (PR) and Loss of Power Supply Probability (LPSP) respectively. Besides that, two design cases of PV-battery system, i.e. system with standard charge controller and system with MPPT-based charge controller were investigated. Apart from that, Iterative-based Sizing Algorithms (ISA) for each design case with the two sizing approaches were developed to determine the optimal solutions which were used as benchmark for FASA. The results showed that FASA had successfully found the optimal PR and LPSP in all design cases using both intuitive and hybrid intuitive-deterministic methods. In addition, sizing algorithm with FA was also discovered to outperform sizing algorithm with selected computational intelligence, i.e. Genetic Algorithm, Evolutionary Programming and Particle Swarm Optimization in producing the lowest computation time in the sizing optimization.
format Thesis
qualification_name Master of Philosophy (M.Phil.)
qualification_level Master's degree
author Abdul Aziz, Nurizzati
author_facet Abdul Aziz, Nurizzati
author_sort Abdul Aziz, Nurizzati
title Firefly algorithm for optimal sizing of Standalone Photovoltaic System / Nurizzati Abdul Aziz
title_short Firefly algorithm for optimal sizing of Standalone Photovoltaic System / Nurizzati Abdul Aziz
title_full Firefly algorithm for optimal sizing of Standalone Photovoltaic System / Nurizzati Abdul Aziz
title_fullStr Firefly algorithm for optimal sizing of Standalone Photovoltaic System / Nurizzati Abdul Aziz
title_full_unstemmed Firefly algorithm for optimal sizing of Standalone Photovoltaic System / Nurizzati Abdul Aziz
title_sort firefly algorithm for optimal sizing of standalone photovoltaic system / nurizzati abdul aziz
granting_institution Universiti Teknologi MARA
granting_department Faculty of Electrical Engineering
publishDate 2016
url https://ir.uitm.edu.my/id/eprint/18844/1/TM_NUR%20IZZATI%20ABDUL%20AZIZ%20EE%2016_5.pdf
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