Yazar "Alsharif, Abdulgader" seçeneğine göre listele

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    Effect of Fuel Cells on Voltage Sag Mitigation in Power Grids Using Advanced Equilibrium Optimizer and Particle Swarm Optimization
    (Tafila Technical Univ (Ttu), 2023) Khaleel, Mohamed Mohamed; Yusupov, Ziyodulla; Guneser, Muhammet; Ghandoori, Tahir Mohamed; Abulifa, Adel Ali; Ahmed, Abdussalam Ali; Alsharif, Abdulgader
    Integration of Proton Exchange Membrane Fuel Cell (PEMFC) with electrical power grid (EPG) can improve the power quality (PQ) of EPG by injecting the required power. However, this makes the PQ issue more complicated due to the negative impact of voltage sag on EPG. Unfortunately, the classical P-I controllers fail in eliminating the voltage sag. In this context, this paper, attempts to mitigate the voltage sag in an interconnected PEMFC-EPG system by utilizing advanced equilibrium optimizer (AEO) and particle swarm optimization (PSO) controllers, and their efficiency is demonstrated by comparison with conventional P- I controllers. To achieve this goal, the AEO-PEMFC and PSO-PEMFC are employed in the EPG line with different fault scenarios. The obtained results unveil that both AEO-PEMFC and PSO-PEMFC provide the needed boost of voltage in the single line-to-ground faults (SLGF) scenario by 100.00%. For double line- to-ground faults (DLGF) scenario, a voltage boost of 99.56% and 98.39% is achieved while a voltage boost of 98.50% and 97.45% for the three line- to-ground faults (TLGF) scenario is obtained by the AEO-PEMFC and PSO-PEMFC, respectively.
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    Impact of Electric Vehicle on Residential Power Distribution Considering Energy Management Strategy and Stochastic Monte Carlo Algorithm
    (Mdpi, 2023) Alsharif, Abdulgader; Tan, Chee Wei; Ayop, Razman; Al Smin, Ahmed; Ali Ahmed, Abdussalam; Kuwil, Farag Hamed; Khaleel, Mohamed Mohamed
    The area of a Microgrid (mu G) is a very fast-growing and promising system for overcoming power barriers. This paper examines the impacts of a microgrid system considering Electric Vehicle Grid Integration (EVGI) based on stochastic metaheuristic methods. One of the biggest challenges to slowing down global climate change is the transition to sustainable mobility. Renewable Energy Sources (RESs) integrated with Evs are considered a solution for the power and environmental issues needed to achieve Sustainable Development Goal Seven (SDG7) and Climate Action Goal 13 (CAG13). The aforementioned goals can be achieved by coupling Evs with the utility grid and other RESs using Vehicle-to-Grid (V2G) technology to form a hybrid system. Overloading is a challenge due to the unknown number of loads (unknown number of Evs). Thus, this study helps to establish the system impact of the uncertainties (arrival and departure Evs) by proposing Stochastic Monte Carlo Method (SMCM) to be addressed. The main objective of this research is to size the system configurations using a metaheuristic algorithm and analyze the impact of an uncertain number of Evs on the distribution of residential power in Tripoli-Libya to gain a cost-effective, reliable, and renewable system. The Improved Antlion Optimization (IALO) algorithm is an optimization technique used for determining the optimal number of configurations of the hybrid system considering multiple sources, while the Rule-Based Energy Management Strategy (RB-EMS) controlling algorithm is used to control the flow of power in the electric power system. The sensitivity analysis of the effect parameters has been taken into account to assess the expected impact in the future. The results obtained from the sizing, controlling, and sensitivity analyses are discussed.