Impact of charging Electric Vehicles in residential network on the voltage profile using Matlab

Neagoe-Stefana, Andreea-Georgiana; Eremia, Mircea; Toma, Lucian; Neagoe, Angela

doi:10.1109/atee.2015.7133909

Cited by 7 publications

(2 citation statements)

References 6 publications

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“…The EV parameters, arrival time (when the EV is available to be charged), and departure time (when the consumer must use the EV) are known and shown in Figure 2 [29].…”

Section: Figure 2 Electric Vehicles Profilesmentioning

confidence: 99%

Energy Management System for Hybrid Microgrids

Attou¹,

Zidi²,

Khatir³

et al. 2021

EEA

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Energy management in grid-connected Micro-grids (MG) has undergone rapid evolution in recent times due to several factors such as environmental issues, increasing energy demand and the opening of the electricity market. The Energy Management System (EMS) allows the optimal scheduling of energy resources and energy storage systems in MG in order to maintain the balance between supply and demand at low cost. The aim is to minimize peaks and fluctuations in the load and production profile on the one hand, and, on the other hand, to make the most of renewable energy sources and energy exchanges with the utility grid. In this paper, our attention has been focused on a Rule-based energy management system (RB EMS) applied to a residential multi-source grid-connected MG. A Microgrid model has been implemented that combines distributed energy sources (PV, WT, BESS), a number of EVs equipped with the Vehicle to Grid technology (V2G) and variable load. Different operational scenarios were developed to see the behaviour of the implemented management system during the day, including the random demand profile of EV users, the variation in load and production, grid electricity price variation. The simulation results presented in this paper demonstrate the efficacy of the suggested EMS and confirm the strategy's feasibility as well as its ability to properly share power among different sources, loads and vehicles by obeying constraints on each element.

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“…The EV parameters, arrival time (when the EV is available to be charged), and departure time (when the consumer must use the EV) are known and shown in Figure 2 [29].…”

Section: Figure 2 Electric Vehicles Profilesmentioning

confidence: 99%

Energy Management System for Hybrid Microgrids

Attou¹,

Zidi²,

Khatir³

et al. 2021

EEA

View full text Add to dashboard Cite

show abstract

“…Thus, reducing the potential overloading of the grid or voltage dips during charging. The impact of EV charging on the distribution network voltage is investigated in [16] where the arrival and departure times, and initial State of Charge (SOC) of EVs are considered for determining the charging current. The user requirements are not considered and it is assumed that the EV is charged to its maximum capacity with no consideration to battery degradation.…”

Section: Introductionmentioning

confidence: 99%