Sizing of standalone photovoltaic-battery-diesel hybrid system with a rule-based energy management strategy using particle swarm optimization

This project proposes an optimal sizing of standalone pv-battery-diesel hybrid system using particle swarm optimization (pso) algorithm. generally, standalone system generates power using diesel generator offers a continuous and reliable source of energy. however, diesel generator is only operating...

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Main Author: Siew, Hon Chong
Format: Thesis
Language:English
Published: 2021
Subjects:
Online Access:http://eprints.utm.my/id/eprint/99503/1/SiewHonChongMKE2021.pdf
http://eprints.utm.my/id/eprint/99503/
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spelling my.utm.995032023-02-27T07:58:17Z http://eprints.utm.my/id/eprint/99503/ Sizing of standalone photovoltaic-battery-diesel hybrid system with a rule-based energy management strategy using particle swarm optimization Siew, Hon Chong TK Electrical engineering. Electronics Nuclear engineering This project proposes an optimal sizing of standalone pv-battery-diesel hybrid system using particle swarm optimization (pso) algorithm. generally, standalone system generates power using diesel generator offers a continuous and reliable source of energy. however, diesel generator is only operating efficiently for a considerable load demand but have low performance when the load is well below its rated capacity. in addition to that, the system operating & maintenance costs and co2 emission level are high. the main objective of this project is to determine an optimal configuration of the proposed standalone hybrid system to meet the targeted reliability index of the system while having the lowest cost of energy (coe). in this project, electrical load demand profile and meteorological data over a year are collected to form input parameters for the proposed hybrid system. a function of rule-based energy management strategy (ems) of the hybrid system, incorporating all the mathematical modelling of the system components is developed using matlab scripts. this function ties back to the main program of particle swarm optimization (pso), a renowned stochastic optimization algorithm that is also developed using matlab scripts. this project uses loss of power supply probability (lpsp) and cost of energy (coe) as objective functions. optimal sizing was performed using pso algorithm and the result shows the optimal configuration obtained has satisfied the targeted lpsp of 1% with the lowest coe of s$0.65 kwh. 2021 Thesis NonPeerReviewed application/pdf en http://eprints.utm.my/id/eprint/99503/1/SiewHonChongMKE2021.pdf Siew, Hon Chong (2021) Sizing of standalone photovoltaic-battery-diesel hybrid system with a rule-based energy management strategy using particle swarm optimization. Masters thesis, Universiti Teknologi Malaysia. http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:149847
institution Universiti Teknologi Malaysia
building UTM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknologi Malaysia
content_source UTM Institutional Repository
url_provider http://eprints.utm.my/
language English
topic TK Electrical engineering. Electronics Nuclear engineering
spellingShingle TK Electrical engineering. Electronics Nuclear engineering
Siew, Hon Chong
Sizing of standalone photovoltaic-battery-diesel hybrid system with a rule-based energy management strategy using particle swarm optimization
description This project proposes an optimal sizing of standalone pv-battery-diesel hybrid system using particle swarm optimization (pso) algorithm. generally, standalone system generates power using diesel generator offers a continuous and reliable source of energy. however, diesel generator is only operating efficiently for a considerable load demand but have low performance when the load is well below its rated capacity. in addition to that, the system operating & maintenance costs and co2 emission level are high. the main objective of this project is to determine an optimal configuration of the proposed standalone hybrid system to meet the targeted reliability index of the system while having the lowest cost of energy (coe). in this project, electrical load demand profile and meteorological data over a year are collected to form input parameters for the proposed hybrid system. a function of rule-based energy management strategy (ems) of the hybrid system, incorporating all the mathematical modelling of the system components is developed using matlab scripts. this function ties back to the main program of particle swarm optimization (pso), a renowned stochastic optimization algorithm that is also developed using matlab scripts. this project uses loss of power supply probability (lpsp) and cost of energy (coe) as objective functions. optimal sizing was performed using pso algorithm and the result shows the optimal configuration obtained has satisfied the targeted lpsp of 1% with the lowest coe of s$0.65 kwh.
format Thesis
author Siew, Hon Chong
author_facet Siew, Hon Chong
author_sort Siew, Hon Chong
title Sizing of standalone photovoltaic-battery-diesel hybrid system with a rule-based energy management strategy using particle swarm optimization
title_short Sizing of standalone photovoltaic-battery-diesel hybrid system with a rule-based energy management strategy using particle swarm optimization
title_full Sizing of standalone photovoltaic-battery-diesel hybrid system with a rule-based energy management strategy using particle swarm optimization
title_fullStr Sizing of standalone photovoltaic-battery-diesel hybrid system with a rule-based energy management strategy using particle swarm optimization
title_full_unstemmed Sizing of standalone photovoltaic-battery-diesel hybrid system with a rule-based energy management strategy using particle swarm optimization
title_sort sizing of standalone photovoltaic-battery-diesel hybrid system with a rule-based energy management strategy using particle swarm optimization
publishDate 2021
url http://eprints.utm.my/id/eprint/99503/1/SiewHonChongMKE2021.pdf
http://eprints.utm.my/id/eprint/99503/
http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:149847
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score 13.188404