Improved antlion sizing optimization for vehicle-to-grid considering rule-based energy management schemes

Renewable Energy Sources (RESs) integration with Electric Vehicles (EVs) and microgrids has become a popular system for providing an economic and green environment. In order to address power challenges, RESs such as solar and wind are exploited and integrated into a microgrid. EVs play a key role in...

Full description

Saved in:

Bibliographic Details
Main Author:	Alsharif, Abdulgader H. Abdulgader
Format:	Thesis
Language:	English
Published:	2023
Subjects:	TK Electrical engineering Electronics Nuclear engineering
Online Access:	http://eprints.utm.my/102786/1/AbdulGaderHPSKE2023.pdf.pdf
Tags:	Add Tag No Tags, Be the first to tag this record!

id	my-utm-ep.102786
record_format	uketd_dc
spelling	my-utm-ep.1027862023-09-20T04:09:25Z Improved antlion sizing optimization for vehicle-to-grid considering rule-based energy management schemes 2023 Alsharif, Abdulgader H. Abdulgader TK Electrical engineering. Electronics Nuclear engineering Renewable Energy Sources (RESs) integration with Electric Vehicles (EVs) and microgrids has become a popular system for providing an economic and green environment. In order to address power challenges, RESs such as solar and wind are exploited and integrated into a microgrid. EVs play a key role in reducing emissions and energy saving due to their free carbon nature, reducing fuel consumption, and can be used as storage or load. Tripoli-Libya (latitude 32.8872° N and longitude 13.1913° E) located in Northern Africa is one of the oils and natural gas producers that has been selected as the study area. However, the country is bedeviled with electric power problems. Microgrids are faced with planning issues, challenges associated with designing a proper model system, as well as stability which results in low power quality. The issue can be addressed by using metaheuristic algorithms combined with Energy Management Strategy (EMS). However, the conventional metaheuristic algorithms face premature convergence and acquire local optima quickly which needs to be improved. Thus, choosing suitable sizing metaheuristic algorithms is recommended to find the global optimum. Therefore, Improved Antlion Optimization (IALO) coupled with the Rule-Based Energy Management Strategy (RB-EMS) is proposed. An RB-EMS is used to control and monitor the flow of energy in the system using simple mathematical equations. Furthermore, in the literature review, rule-based is recommended due to the decision-making and providing the appropriate result. This study examines a grid-connected system aimed at addressing the current power challenges by integrating RESs into Electric Vehicle Charging Facility (EVCF) using Vehicle-to-Grid (V2G) technology. An objective function for the proposed grid-connected system mainly depends on measuring the per unit of generated electricity as Cost of Energy (COE), and reduction in Losses Power Supply Probability (LPSP) as means of stabilizing the system and maximizing the Renewable Energy Fraction (REF). Mathematical modeling for the Photovoltaic (PV), Wind Turbine (WT), EV, inverter, and Battery (BT) as the microgrid components for the case study (Tripoli-Libya) is adopted. The acquired result has been validated with other algorithms Antlion Optimization (ALO), Particle Swarm Optimization (PSO), and Cuckoo Search Algorithm (CSA). The obtained simulation result indicates that the proposed method IALO contributed lower COE ($0.0936 /kWh), and high REF (99.40%) as compared to the counterpart algorithms. The IALO coupled with RB-EMS fills the gap in sizing and planning a cost-effective system to address the sizing limitations. The results affirm the low-cost nature of the proposed model of a grid-connected microgrid system using V2G technology. A further economic assessment is made using the Stochastic Monte Carlo Method (SMCM) used to estimate the load impact by integrating various numbers of EVs and the payback period. Sensitivity analysis was utilized to demonstrate the impact performance of the proposed components under various scenarios. 2023 Thesis http://eprints.utm.my/102786/ http://eprints.utm.my/102786/1/AbdulGaderHPSKE2023.pdf.pdf application/pdf en public http://dms.library.utm.my:8080/vital/access/manager/Repository/vital:152265 phd doctoral Universiti Teknologi Malaysia Faculty of Engineering - School of Electrical Engineering
institution	Universiti Teknologi Malaysia
collection	UTM Institutional Repository
language	English
topic	TK Electrical engineering Electronics Nuclear engineering
spellingShingle	TK Electrical engineering Electronics Nuclear engineering Alsharif, Abdulgader H. Abdulgader Improved antlion sizing optimization for vehicle-to-grid considering rule-based energy management schemes
description	Renewable Energy Sources (RESs) integration with Electric Vehicles (EVs) and microgrids has become a popular system for providing an economic and green environment. In order to address power challenges, RESs such as solar and wind are exploited and integrated into a microgrid. EVs play a key role in reducing emissions and energy saving due to their free carbon nature, reducing fuel consumption, and can be used as storage or load. Tripoli-Libya (latitude 32.8872° N and longitude 13.1913° E) located in Northern Africa is one of the oils and natural gas producers that has been selected as the study area. However, the country is bedeviled with electric power problems. Microgrids are faced with planning issues, challenges associated with designing a proper model system, as well as stability which results in low power quality. The issue can be addressed by using metaheuristic algorithms combined with Energy Management Strategy (EMS). However, the conventional metaheuristic algorithms face premature convergence and acquire local optima quickly which needs to be improved. Thus, choosing suitable sizing metaheuristic algorithms is recommended to find the global optimum. Therefore, Improved Antlion Optimization (IALO) coupled with the Rule-Based Energy Management Strategy (RB-EMS) is proposed. An RB-EMS is used to control and monitor the flow of energy in the system using simple mathematical equations. Furthermore, in the literature review, rule-based is recommended due to the decision-making and providing the appropriate result. This study examines a grid-connected system aimed at addressing the current power challenges by integrating RESs into Electric Vehicle Charging Facility (EVCF) using Vehicle-to-Grid (V2G) technology. An objective function for the proposed grid-connected system mainly depends on measuring the per unit of generated electricity as Cost of Energy (COE), and reduction in Losses Power Supply Probability (LPSP) as means of stabilizing the system and maximizing the Renewable Energy Fraction (REF). Mathematical modeling for the Photovoltaic (PV), Wind Turbine (WT), EV, inverter, and Battery (BT) as the microgrid components for the case study (Tripoli-Libya) is adopted. The acquired result has been validated with other algorithms Antlion Optimization (ALO), Particle Swarm Optimization (PSO), and Cuckoo Search Algorithm (CSA). The obtained simulation result indicates that the proposed method IALO contributed lower COE ($0.0936 /kWh), and high REF (99.40%) as compared to the counterpart algorithms. The IALO coupled with RB-EMS fills the gap in sizing and planning a cost-effective system to address the sizing limitations. The results affirm the low-cost nature of the proposed model of a grid-connected microgrid system using V2G technology. A further economic assessment is made using the Stochastic Monte Carlo Method (SMCM) used to estimate the load impact by integrating various numbers of EVs and the payback period. Sensitivity analysis was utilized to demonstrate the impact performance of the proposed components under various scenarios.
format	Thesis
qualification_name	Doctor of Philosophy (PhD.)
qualification_level	Doctorate
author	Alsharif, Abdulgader H. Abdulgader
author_facet	Alsharif, Abdulgader H. Abdulgader
author_sort	Alsharif, Abdulgader H. Abdulgader
title	Improved antlion sizing optimization for vehicle-to-grid considering rule-based energy management schemes
title_short	Improved antlion sizing optimization for vehicle-to-grid considering rule-based energy management schemes
title_full	Improved antlion sizing optimization for vehicle-to-grid considering rule-based energy management schemes
title_fullStr	Improved antlion sizing optimization for vehicle-to-grid considering rule-based energy management schemes
title_full_unstemmed	Improved antlion sizing optimization for vehicle-to-grid considering rule-based energy management schemes
title_sort	improved antlion sizing optimization for vehicle-to-grid considering rule-based energy management schemes
granting_institution	Universiti Teknologi Malaysia
granting_department	Faculty of Engineering - School of Electrical Engineering
publishDate	2023
url	http://eprints.utm.my/102786/1/AbdulGaderHPSKE2023.pdf.pdf
_version_	1783729217355120640

Improved antlion sizing optimization for vehicle-to-grid considering rule-based energy management schemes

Similar Items