A Nudge-Based Approach for Day-Ahead Optimal Scheduling of Destination Charging Station With Flexible Regulation Capacity

被引：0
作者：
Zhang, Ziqi [1 ]
Chen, Zhong [1 ]
Guemruekcu, Erdem [2 ]
Xing, Qiang [3 ,4 ]
Ponci, Ferdinanda [2 ]
Monti, Antonello [2 ]
机构：
[1] Southeast Univ, Sch Elect Engn, Nanjing 210096, Peoples R China
[2] Rhein Westfal TH Aachen, Inst Automat Complex Power Syst, EON Energy Res Ctr, D-52074 Aachen, Germany
[3] Nanjing Univ Posts & Telecommun, Sch Automat, Nanjing 210023, Peoples R China
[4] Nanjing Univ Posts & Telecommun, Sch Artificial Intelligence, Nanjing 210023, Peoples R China
来源：
IEEE TRANSACTIONS ON TRANSPORTATION ELECTRIFICATION | 2024年 / 10卷 / 04期
基金：
中国国家自然科学基金;
关键词：
Vehicle-to-grid; Optimization; Costs; Transportation; Regulation; Charging stations; Biological system modeling; Destination charging scheduling; flexible regulation capacity (FRC); nudge; twin delayed deep deterministic policy gradient (TD3); ELECTRIC VEHICLES; STORAGE; SYSTEM;
D O I：
10.1109/TTE.2024.3350052
中图分类号：
TM [电工技术]; TN [电子技术、通信技术];
学科分类号：
0808 ; 0809 ;
摘要：
This work introduces the nudge theory of behavioral economics in electric vehicle (EV) charging schedules. Nudges emphasize guiding user choice through noncoercive means that go beyond economics. First, we conduct the surveys of EV users to verify the effectiveness of nudges in guiding charging behavior and establish user response models for day-ahead simulation. Then, we build a charging agent that can realize the rapid optimization of a single EV to reduce the electricity cost and improve the flexible regulation capacity (FRC). This agent is modeled and trained based on twin delayed deep deterministic policy gradient (TD3) algorithm. Next, we perform Monte Carlo (MC) simulations with this agent to calculate the day-ahead variability range of power consumption and FRCs involving various EVs. Finally, we set the price difference of the charging options with nudges as the control variable and utilize discrete particle swarm optimization (DPSO) to obtain its optimal value with the objective of the revenue of the charging station operator (CSO). The case study is based on over 1500 questionnaires. The results highlight that the nudges can improve the percentage of users participating in scheduled charging, thereby helping CSO achieve more revenue and offer reliable FRCs to the grid.
引用
收藏
页码：8498 / 8512
页数：15
相关论文
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