@inproceedings{b91c52830f514ce19cb652a807461da7,
title = "On Controlling Battery Degradation in Vehicle-to-Grid Energy Markets",
abstract = "Nowadays, power grids are facing reduced total system inertia as traditional generators are phased out in favor of renewable energy sources. This issue is expected to deepen with the increasing penetration of electric vehicles (EVs). The influence of a single EV on power networks is low; nevertheless, the aggregate impact becomes relevant when they are properly coordinated. In this context, we consider the frequent case of a group of EVs connected to a parking lot with a photovoltaic facility. We propose a novel strategy to optimally control their batteries during the parking session, which is able to satisfy their requirements and energy constraints. EVs participate in a noncooperative energy market based on a smart pricing mechanism that is designed in order to increase the predictability and flexibility of the aggregate parking load. Differently from the existing contributions, we employ a novel approach to minimize the degradation of batteries. The effectiveness of the proposed method is validated through numerical experiments based on a real scenario.",
keywords = "charging scheduling, Electric vehicles, model predictive control",
author = "Paolo Scarabaggio and Raffaele Carli and Alessandra Parisio and Mariagrazia Dotoli",
note = "Publisher Copyright: {\textcopyright} 2022 IEEE.; 18th IEEE International Conference on Automation Science and Engineering, CASE 2022 ; Conference date: 20-08-2022 Through 24-08-2022",
year = "2022",
doi = "10.1109/CASE49997.2022.9926729",
language = "English",
series = "IEEE International Conference on Automation Science and Engineering",
publisher = "IEEE Computer Society ",
pages = "1206--1211",
booktitle = "2022 IEEE 18th International Conference on Automation Science and Engineering, CASE 2022",
address = "United States",
}