A Two-phase On-line Joint Scheduling for Welfare Maximization of Charging Station

TL;DR

This paper proposes a two-phase online algorithm for joint pricing and charging control in EV charging stations, maximizing social welfare by considering uncertainties and driver sensitivities.

Contribution

It introduces a novel two-phase online policy learning algorithm combining event-based policy iteration and scenario-based model predictive control for EV charging station management.

Findings

The proposed method improves social welfare in numerical simulations.

The algorithm effectively balances pricing and charging control under uncertainty.

Theoretical analysis confirms the optimality of the approach.

Abstract

The large adoption of EVs brings practical interest to the operation optimization of the charging station. The joint scheduling of pricing and charging control will achieve a win-win situation both for the charging station and EV drivers, thus enhancing the operational capability of the station. We consider this important problem in this paper and make the following contributions. First, a joint scheduling model of pricing and charging control is developed to maximize the expected social welfare of the charging station considering the Quality of Service and the price fluctuation sensitivity of EV drivers. It is formulated as a Markov decision process with variance criterion to capture uncertainties during operation. Second, a two-phase on-line policy learning algorithm is proposed to solve this joint scheduling problem. In the first phase, it implements event-based policy iteration to find the optimal pricing scheme, while in the second phase, it implements scenario-based model predictive control for smart charging under the updated pricing scheme. Third, by leveraging the performance difference theory, the optimality of the proposed algorithm is theoretically analyzed. Numerical experiments for a charging station with distributed generation and energy storage demonstrate the effectiveness of the proposed method and the improved social welfare of the charging station.