Abstract

In this study, we deal with the problem of scheduling charging periods of electrical vehicles (EVs) to satisfy the users’ demands for energy consumption as well as to optimally utilize the available power. We assume three-phase EV charging stations, each equipped with two charging ports (links) that can serve up to two EVs in the scheduling period but not simultaneously. Considering such a specification, we propose an on–off scheduling scheme wherein control over an energy flow is achieved by flexibly switching the ports in each station on and off in a manner such as to satisfy the energy demand of each EV, flatten the high energy-consuming load on the whole farm, and to minimize the number of switching operations. To satisfy these needs, the on–off scheduling scheme is formulated in terms of a binary linear programming problem, which is then extended to a quadratic version to incorporate the smoothness constraints. Various algorithmic approaches are used for solving a binary quadratic programming problem, including the Frank–Wolfe algorithm and successive linear approximations. The numerical simulations demonstrate that the latter is scalable, efficient, and flexible in a charging procedure, and it shaves the load peak while maintaining smooth charging profiles.

Highlights

  • The electrification of transportation offers multiple benefits, including the reduction of noise pollution, fumes, and GHG emissions [1,2]

  • The selected single-run results are shown in Figures 2–4, while the Monte Carlo (MC) statistics are presented in Tables 2–4, and in Figures 5 and 6

  • The distributions of energy demand (ED) after using the correction procedure and available time (AT), which were used to obtain the results in Figure 2, are illustrated in Figure 3a in the form of time slot bars

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Summary

Introduction

The electrification of transportation offers multiple benefits, including the reduction of noise pollution, fumes, and GHG emissions [1,2]. There is a great need to develop an EV charging station infrastructure while maintaining a balanced load of power supply lines [3] To pursue this goal, EV charging technology must be developed for fast charging systems and for balanced overnight charging strategies with smart management of accessible energy, user energy demands, and cost savings. We tackle the problem of smart coordination of the EV charging process in such farms, considering power supply constraints, balanced and smooth load expectations, energy demands, and user transportation habits and needs. The designed system should ensure a balanced power load over the entire accessible period Performing this task is difficult because we expect cumulations for energy demands.

Related Works
Scheduling Problem
Problem Formulation
Algorithmic Approach
Frank—Wolfe Algorithm
Successive Linear Approximations
Numerical Simulations
Results
Discussion
Engineering Aspects
Conclusions
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