A Distributed Online Algorithm for Promoting Energy Sharing Between EV Charging Stations

TL;DR

This paper introduces a distributed online algorithm for EV charging stations to share energy efficiently, minimizing costs without requiring predictions, and ensures privacy and constraint satisfaction through Lyapunov optimization and ADMM techniques.

Contribution

It develops a novel prediction-free online algorithm for energy sharing among EV charging stations, with theoretical guarantees and a distributed implementation approach.

Findings

Algorithm effectively reduces operating costs.

Maintains constraint satisfaction without predictions.

Demonstrates advantages over existing methods.

Abstract

In recent years, electric vehicle (EV) charging station has experienced an increasing supply-demand mismatch due to its fluctuating renewables and unpredictable charging demand. To reduce its operating cost, this paper proposes a distributed online algorithm to promote the energy sharing between charging stations. We begin with the offline and centralized version of the EV charging stations operation problem, whose objective is to minimize the long-term time-average total cost. Then, we develop an online implementation approach based on the Lyapunov optimization framework. Although the proposed online algorithm runs in a prediction-free manner, we prove that by properly choosing the parameters, the time-coupling constraints remain to be satisfied. We also provide a theoretical bound for the optimality gap between the offline and online optimums. Furthermore, an improved alternating direction method of multipliers (ADMM) algorithm with iteration truncation is proposed to enable distributed computation. The proposed algorithm can protect privacy while being suitable for online implementation. Case studies validate the effectiveness of the theoretical results. Comprehensive performance comparisons are carried out to demonstrate the advantages of the proposed method.