Abstract
The spread of electric vehicles (EV) contributes substantial stress to the present overloaded utility grid which creates new chaos for the distribution network. To relieve the grid from congestion, this paper deeply focused on the control and operation of a charging station for a PV/Battery powered workplace charging facility. This control was tested by simulating the fast charging station when connected to specified EVs and under variant solar irradiance conditions, parity states and seasonal weather. The efficacy of the proposed algorithm and experimental results are validated through simulation in Simulink/Matlab. The results showed that the electric station operated smoothly and seamlessly, which confirms the feasibility of using this supervisory strategy. The optimum cost is calculated using heuristic algorithms in compliance with the meta-heuristic barebones Harris hawk algorithm. In order to long run of charging station the sizing components of the EV station is done by meta-heuristic barebones Harris hawk optimization with profit of USD 0.0083/kWh and it is also validated by swarm based memetic grasshopper optimization algorithm (GOA) and canonical particle swarm optimization (PSO).
Highlights
Rising energy demand in the transportation sector is one of the most challenging tasks to meet carbon dioxide (CO2) reduction targets and Green House Gases emission (GHGs)
This paper presents and develops a supervisory controller for the battery-enabled DC fast charging station based on the Supervisory Control Theory (SCT) of discrete event systems
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Summary
Rising energy demand in the transportation sector is one of the most challenging tasks to meet carbon dioxide (CO2) reduction targets and Green House Gases emission (GHGs). EV exposure brings merits to power systems, such as load leveling, increasing generation capacity during high load periods, likely investment deferment, voltage regulation, spinning reserve services, reduction of oil dependence, Appl. Sci. 2021, 11, 9118 systems, such as load leveling, increasing generation capacity during high load periods, likely investment deferment, voltage regulation, spinning reserve services, reduction of yoiiel lddeipngenhdigenhceec,oynieolmdiincganhdigehnevcioronnommeicnatanldbeennvefiirtosn. In the studied paper the heuristic supervisory rule-based energy ma3noafg28ement scheme is applied to manage the electric vehicle loads from stochastic PV generators in addition to battery storage buffer for seamless daylight charging operation with a facility at awliothwsemraprtricchearagsincgomscpheamreed. This paper presents and develops a supervisory controller for the battery-enabled DC fast charging station based on the Supervisory Control Theory (SCT) of discrete event systems. The supervisory control can use a Finite State Machine (FSM) for the implementation of complex supervisory control logics which is transparent and readily implementable on industrial controllers
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