Development of Charging, Discharging Scheduling Algorithm for Economical and Energy Efficient Operation of Multi EV Charging Station

TL;DR

This paper proposes a novel EV charging/discharging scheduling algorithm integrated with a microgrid to optimize energy efficiency and reduce costs at PV-based charging stations, considering local load and PV production forecasts.

Contribution

It introduces a new scheduling algorithm that maximizes EV utilization, minimizes operating costs, and enhances energy efficiency using multi-objective optimization and predictive load forecasting.

Findings

Operating cost decreased by 167.71% compared to existing algorithms.

Maximized EV utilization while satisfying charging requirements.

Enhanced energy efficiency of PV-based charging stations.

Abstract

As the number of electric vehicles (EVs) significantly increases, the excessive charging demand of parked EVs in the charging station may incur an instability problem to the electricity network during peak hours. For the charging station to take a microgrid (MG) structure, an economical and energy-efficient power management scheme is required for the power provision of EVs while considering the local load demand of the MG. For these purposes, this study presents the power management scheme of interdependent MG and EV fleets aided by a novel EV charg-ing/discharging scheduling algorithm. In this algorithm, the maximum amount of discharging power from parked EVs is determined based on the difference between local load demand and photovoltaic (PV) power production to alleviate imbalances occurred between them. For the power management of the MG with charging/discharging scheduling of parked EVs in the PV-based charging station, multi-objective optimization is performed to minimize the operating cost and grid dependency. In addition, the proposed scheme maximizes the utilization of EV charging/discharging while satisfying the charging requirements of parked EVs. Moreover, a more economical and energy-efficient PV-based charging station is established using the future trends of local load demand and PV power production predicted by a gated recurrent unit (GRU) network. With the proposed EV charging/discharging scheduling algorithm, the operating cost of PV-based charging station is decreased by 167.71% and 28.85% compared with the EV charg-ing scheduling algorithm and the conventional EV charging/discharging scheduling algorithm, respectively. It is obvious that the economical and energy-efficient operation of PV-based charging station can be accomplished by applying the power management scheme with the proposed EV charging/discharging scheduling strategy.