Optimal Scheduling of Electric Vehicles Charging in low-Voltage Distribution Systems

TL;DR

This paper investigates optimal EV charging strategies in China's distribution systems, proposing incentive mechanisms and pricing schemes to mitigate load peaks and improve system efficiency.

Contribution

It introduces novel incentive and pricing schemes for centralized and decentralized EV charging, enhancing load management in distribution networks.

Findings

Simulated tests confirm the effectiveness of the proposed scheduling methods.

Incentive mechanisms reduce load peaks under TOU pricing.

Rolling-update pricing improves decentralized charging efficiency.

Abstract

Uncoordinated charging of large-scale electric vehicles (EVs) will have a negative impact on the secure and economic operation of the power system, especially at the distribution level. Given that the charging load of EVs can be controlled to some extent, research on the optimal charging control of EVs has been extensively carried out. In this paper, two possible smart charging scenarios in China are studied: centralized optimal charging operated by an aggregator and decentralized optimal charging managed by individual users. Under the assumption that the aggregators and individual users only concern the economic benefits, new load peaks will arise under time of use (TOU) pricing which is extensively employed in China. To solve this problem, a simple incentive mechanism is proposed for centralized optimal charging while a rolling-update pricing scheme is devised for decentralized optimal charging. The original optimal charging models are modified to account for the developed schemes. Simulated tests corroborate the efficacy of optimal scheduling for charging EVs in various scenarios.