Development of DC Microgrid Integrated Electric Vehicle Charging Station With Fuzzy Logic Controller

Hadero, Mathewos; Khan, Baseem

doi:10.3389/fenrg.2022.922384

Cited by 9 publications

(2 citation statements)

References 19 publications

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“…The authors of [32] describe a microgrid with high penetration of renewable energy sources and management employing hybrid invasive weed optimization for the most cost-effective charging. The authors of [33] proposed a DC microgrid with EV charging by coordinating the power flow using fuzzy logic, with PV Battery and Grid as energy sources. Power management in the variation of solar power and pricing are discussed.…”

Section: Literature Reviewmentioning

confidence: 99%

Renewable Energy-Based DC Microgrid with Hybrid Energy Management System Supporting Electric Vehicle Charging System

Mohan

Dash

2023

Systems

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Growing Electric vehicle (EV) ownership leads to an increase in charging stations, which raises load demand and causes grid outages during peak hours. Microgrids can significantly resolve these issues in the electrical distribution system by implementing an effective energy management approach. The suggested hybrid optimization approach aims to provide constant power regardless of the generation discrepancy and should prevent the early deterioration of the storage devices. This study suggests using a dynamic control system based on the Fuzzy-Sparrow Search Algorithm (SSA) to provide a reliable power balance for microgrid (MG) operation. The proposed DC microgrid integrating renewable energy sources (RES) and battery storage system (BSS) as sources are designed and evaluated, and the findings are further validated using MATLAB Simulink simulation. In comparing the hybrid SSA strategy with the most widely used Particle Swarm Optimization (PSO)-based power management, it was observed that the hybrid SSA approach was superior in terms of convergence speed and stability. The effectiveness of the given energy management system is evaluated using two distinct modes, the variation of solar irradiation and the variation of battery state of charge, ensuring the microgrid’s cost-effective operation. The enhanced response characteristics indicate that the Fuzzy-SSA can optimise power management of the DC microgrid, making better use of energy resources. These results show the relevance of algorithm configuration for cost-effective power management in DC microgrids, as it saves approximately 7.776% in electricity expenses over a year compared to PSO.

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Section: Literature Reviewmentioning

confidence: 99%

Renewable Energy-Based DC Microgrid with Hybrid Energy Management System Supporting Electric Vehicle Charging System

Mohan

Dash

2023

Systems

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“…Charging of connected EVs is regulated based on the amount of power produced from RES and energy stored in battery storage. Power flow management with a fuzzy logic controller in [18] is used for voltage stabilization in a DC microgrid for EVCS. The proposed controller is used to coordinate power flow between the PV power plant, BSS, and the utility grid based on variations in EVCS demand and intermittent power generation.…”

Section: Power Flow Control Of Microgridsmentioning

confidence: 99%

A Review of Advanced Control Strategies of Microgrids with Charging Stations

Tkac,

Kajanova,

Bracinik

2023

Energies

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In the context of the global drive towards sustainability and rapid integration of renewables, electric vehicles, and charging infrastructure, the need arises for advanced operational strategies that support the grid while managing the intermittent nature of these resources. Microgrids emerge as a solution, operating independently or alongside the main grid to facilitate power flow management among interconnected sources and different loads locally. This review paper aims to offer a comprehensive overview of the different control strategies proposed in the literature to control microgrids with electric vehicle charging stations. The surveyed research is primarily categorized according to the employed control algorithms, although distinctions are also made based on defined microgrid architecture, utilization of specific power sources, and charging stations configurations. Additionally, this paper identifies research gaps in the current research. These gaps encompass the use of oversimplified models for charging stations and/or renewable sources operation, limited simulation time periods, or lack of experimental testing of proposed approaches. In the light of these identified shortcomings, this manuscript presents recommendations for guiding future research.

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Development of Rule-Based Control Algorithm for DC Charging Stations and Simulation Results

Üstünsoy,

Hüseyin Sayan

2023

Lecture Notes in Mechanical Engineering

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Development of DC Microgrid Integrated Electric Vehicle Charging Station With Fuzzy Logic Controller

Cited by 9 publications

References 19 publications

Renewable Energy-Based DC Microgrid with Hybrid Energy Management System Supporting Electric Vehicle Charging System

Renewable Energy-Based DC Microgrid with Hybrid Energy Management System Supporting Electric Vehicle Charging System

A Review of Advanced Control Strategies of Microgrids with Charging Stations

Development of Rule-Based Control Algorithm for DC Charging Stations and Simulation Results

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