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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Bibliographic Details
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/
http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:149847
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Summary: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.