期刊
IEEE TRANSACTIONS ON SMART GRID
卷 12, 期 4, 页码 3353-3363出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSG.2021.3066998
关键词
Charging stations; Pricing; Schedules; Optimization; Vehicles; Decision making; Real-time systems; Electric vehicles; charging stations; overstay; discrete choice modeling; multi-block convex; block coordinate descent
资金
- Total SE
The study introduces an innovative optimization framework for charging stations, enhancing service accessibility through pricing policies and charge scheduling while considering human behavior. The model effectively captures drivers' charging decisions, leading to benefits in net profits, reduction in overstays, and improvement in service quality.
Plug-in electric vehicle (PEV) charging station service capability is physically limited by the charger availability and local transformer capacity. However, the station operation performance has become an increasingly important factor for enhancing charging service accessibility. In this work, we propose an innovative station-level optimization framework to operate charging station with optimal pricing policy and charge scheduling. This model incorporates human behaviors to explicitly and effectively capture drivers' charging decision process. We propose a menu of price-differentiated charging services, which differ in both the per-unit prices and the energy delivery schedule. Involving human in the loop, the operation model also exploits the capability to alleviate the overstay issue that occurs when a PEV's charging session has completed. We then propose a muli-block convex transformation methodology to reformulate the resulted non-convex problem via Fenchel-Young Inequality; the Block Coordinate Descent algorithm is applied to solve the overall problem and the efficiency enables real-time implementation. As a result, our simulation demonstrates that the proposed control polices can realize benefits in three aspects: (i) net profits gains, (ii) overstay reduction, and (iii) quality-of-service increase.
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