PV-Powered Charging Station: Energy Management with V2G Operation and Energy Cost Analysis

Cheikh-Mohamad, Saleh; Sechilariu, Manuela; Locment, Fabrice

doi:10.23919/splitech55088.2022.9854343

Cited by 3 publications

(2 citation statements)

References 16 publications

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“…Additionally, EV users arrive arbitrarily at the PVCS, and their arrivals are unpredictable. In [43], the authors presented a control mechanism aimed at minimizing the discomfort of EV users for a charging station equipped with PV sources and connected to a public grid, but without a stationary storage system. However, their study differs from ours in several ways.…”

Section: Introductionmentioning

confidence: 99%

PV-Powered Charging Station with Energy Cost Optimization via V2G Services

et al. 2023

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Satisfying the increased power demand of electric vehicles (EVs) charged by clean energy sources will become an important aspect that impacts the sustainability and the carbon emissions of the smart grid. A photovoltaic (PV)-powered charging station (PVCS) formed by PV modules and a stationary storage system with a public grid connection can provide cost-efficient and reliable charging strategies for EV batteries. Moreover, the utilization of vehicle-to-grid (V2G) service is a promising solution, as EVs spend most of their time idle in charging stations. As a result, V2G services have the potential to provide advantages to both public grid operators and EV users. In this paper, an energy management algorithm of a PVCS formulated with mixed-integer linear programming is presented to minimize the total energy cost of the participation of EV users in V2G service. Simulation results demonstrate that the proposed optimization method satisfies EV user demands while providing V2G service and highlights the benefits of the V2G service where the determined costs of the proposed algorithm perform significantly better compared to the baseline scenario (simulation without optimization).

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Section: Introductionmentioning

confidence: 99%

PV-Powered Charging Station with Energy Cost Optimization via V2G Services

et al. 2023

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“…In [18], a new approach was taken, which prepared the system so that it could offer to the users of the charging station different charging speeds, presenting them the possibility of utilizing the V2G technology, developed for obtaining data and testing its robustness. After the energy flow in the system occurred, the overall system was priced based on the resulting energy exchanged between the vehicle and the grid.…”

Section: Introductionmentioning

confidence: 99%

Differential Evolution and Fuzzy-Logic-Based Predictive Algorithm for V2G Charging Stations

et al. 2023

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This work proposes a differential evolution algorithm to control a vehicle-to-grid (V2G) system based on photovoltaic generation and energy cost curves, and constraints associated with the power converters’ operation, battery charging strategy, and initial budgets. The algorithm is designed to trade off the batteries’ state of charge and the profits gained from selling energy to the grid. To achieve this balance, a fuzzy controller is employed and acts based on forecasts of the photovoltaic generation and the cost of electricity, within prediction windows of 120 min, adapting the batteries’ rate of charging or discharging. Simulation results show that for different curves and different initial budgets, the target state of charge is reached at the end of the time horizon. By evaluating the proposed scheme under different scenarios, the algorithm’s performance is proven to be suitable for future practical deployment.

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