Universiti Teknologi Malaysia Institutional Repository

Optimization of PV size for off-grid connected PV system considering uncertainties using differential evolution algorithm

Naji, Saif Aldeen Muqdad (2020) Optimization of PV size for off-grid connected PV system considering uncertainties using differential evolution algorithm. Masters thesis, Universiti Teknologi Malaysia, Faculty of Engineering - School of Electrical Engineering.

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Abstract

Increase in global energy demand has made renewable energy systems more attractive. In the past decade the utilization of PV systems has tremendously increased due to global warming phenomena and the rapid depletion of fossil fuel reserve. However, the intermittency and inconsistency of energy supply are some of the main drawback associated associate with the PV technologies. The hybridization of PV system with battery storage system improves the reliability and efficiency of the PV supply. In the past decade, standalone PV system become one of the systems that has been widely used. In this dissertation, the optimization of the PV system with battery storage is performed. The objective is to optimize PV system with battery, considering temperature and solar irradiance in order to maximize the output. The proposed system is designed to supply the energy demand of Al-Mamoon University College. This project considers yearly temperature and solar irradiance. The sizing optimization is performed using differential evolution (DE). Two key criteria are considered during the optimization process i.e., reliability and price of electricity. The proposed methodology is implemented using MATLAB software. The proposed approach based on (DE) is compared with particle swarm optimization technique in terms of fast convergence, accuracy.

Item Type:Thesis (Masters)
Additional Information:Thesis (Sarjana Kejuruteraan (Elektrik Kuasa)) - Universiti Teknologi Malaysia, 2020; Supervisors : Dr. Madihah Md. Rasid
Subjects:T Technology > TK Electrical engineering. Electronics Nuclear engineering
Divisions:Electrical Engineering
ID Code:93017
Deposited By: Yanti Mohd Shah
Deposited On:07 Nov 2021 06:00
Last Modified:07 Nov 2021 06:00

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