Online Charging Scheduling Algorithms of Electric Vehicles in Smart Grid: An Overview

TL;DR

This paper reviews online electric vehicle charging scheduling algorithms in smart grids, emphasizing how they handle uncertainty in future events to improve grid stability and efficiency.

Contribution

It provides an overview of various online EV charging algorithms, analyzing their approaches to managing future uncertainties and highlighting future research directions.

Findings

Online algorithms adapt to uncertain future events.

Charging strategies improve grid stability and renewable integration.

Identifies key challenges and research gaps in EV charging control.

Abstract

As an environment-friendly substitute for conventional fuel-powered vehicles, electric vehicles (EVs) and their components have been widely developed and deployed worldwide. The large-scale integration of EVs into power grid brings both challenges and opportunities to the system performance. On one hand, the load demand from EV charging imposes large impact on the stability and efficiency of power grid. On the other hand, EVs could potentially act as mobile energy storage systems to improve the power network performance, such as load flattening, fast frequency control, and facilitating renewable energy integration. Evidently, uncontrolled EV charging could lead to inefficient power network operation or even security issues. This spurs enormous research interests in designing charging coordination mechanisms. A key design challenge here lies in the lack of complete knowledge of events that occur in the future. Indeed, the amount of knowledge of future events significantly impacts the design of efficient charging control algorithms. This article focuses on introducing online EV charging scheduling techniques that deal with different degrees of uncertainty and randomness of future knowledge. Besides, we highlight the promising future research directions for EV charging control.