Online battery-protective vehicle to grid behavior management

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. (c) 2022 Elsevier Ltd. All rights reserved.

Automated summary

With the popularization of electric vehicles, vehicle-to-grid (V2G) technology has become essential for improving grid economy and reliability. This paper proposes an online battery anti-aging V2G scheduling method that mitigates battery aging while providing V2G services through parameter calibration. The method is verified on a practical UK distribution network and shows effectiveness in reducing battery aging while maintaining real-time performance.