Online battery-protective vehicle to grid behavior management. (15th March 2022)

• Record Type: Journal Article
• Authors: Li, Shuangqi; Zhao, Pengfei; Gu, Chenghong; Huo, Da; Zeng, Xianwu; Pei, Xiaoze; Cheng, Shuang; Li, Jianwei
• Is Part Of: Energy. Volume 243(2022)
• Publication Date: 2022-03-15
• Subjects: Battery degradation -- Battery protective strategy -- Electric vehicle -- Energy management -- Energy storage system -- Transportation electrification -- Vehicle to grid; Power resources -- Periodicals; Power (Mechanics) -- Periodicals; Energy consumption -- Periodicals; 333.7905
• DOI: 10.1016/j.energy.2021.123083
• Languages: English
• ISSNs: 0360-5442

Abstract

Abstract: With the popularization of electric vehicles, vehicle-to-grid (V2G) has become an indispensable technology to improve grid economy and reliability. However, battery aging should be mitigated while providing V2G services so as to protect customer benefits and mobilize their positivity. Conventional battery anti-aging V2G scheduling methods mainly offline operates and can hardly be deployed online in hardware equipment. This paper proposes a novel online battery anti-aging V2G scheduling method based on a novel two-stage parameter calibration framework. In the first stage, the V2G scheduling is modeled as an optimization problem, where the objective is to reduce grid peak-valley difference and mitigate battery aging. The online deployment of the developed optimization-based V2G scheduling is realized by a rule-based V2G coordinator in the second stage, and a novel parameter calibration method is developed to adjust controller hyper-parameters. With the parameter calibration process, the global optimality and real-time performance of V2G strategies can be simultaneously realized. The effectiveness of the proposed methodologies is verified on a practical UK distribution network. Simulation results indicate that it can effectively mitigate battery aging in providing V2G services while guaranteeing algorithm real-time performance. Highlights: Battery-protective V2G scheduling method with online deployment capability. Grid peak-shaving and battery anti-aging are considered in an optimization model. A rule-based coordinator is built to deploy the derived optimal strategies online. A practical UK distribution network is employed to verify the performances. 37.8% battery life loss can be reduced while providing auxiliary power in real-time.