Stochastic modeling of EV on-board chargers for V2G services

Tools

Shi, Xiang and Bayram, I. Safak; (2025) Stochastic modeling of EV on-board chargers for V2G services. In: 2025 IEEE Transportation Electrification Conference and Expo (ITEC). IEEE Transportation Electrification Conference and Expo (ITEC) . IEEE, USA. (In Press)

[thumbnail of Shi-Bayram-IEEE-ITEC-2025-Stochastic-modeling-of-EV-on-board-chargers-for-V2G-services] Text. Filename: Shi-Bayram-IEEE-ITEC-2025-Stochastic-modeling-of-EV-on-board-chargers-for-V2G-services.pdf
Accepted Author Manuscript
Restricted to Repository staff only until 1 January 2099.
Download (968kB) | Request a copy

Abstract

Vehicle-to-Grid (V2G) applications offer significant potential to support power grids by providing ancillary services through the rapid charging and discharging of electric vehicles (EVs), often within a timeframe of a few seconds. This paper introduces a Markov-chain model to analyze EV on-board systems for V2G applications. The system’s states are designed to account for on-board charger communication delays and asymmetric ramping rates. The primary objective of the model is to evaluate the proportion of market signals successfully executed within a defined delay constraint. A case study based on real-world communication delay measurements taken from six distinct EV on-board chargers, as well as sample market signals from PJM, is presented. The findings reveal that communication delays have a considerable impact on the effectiveness of V2G applications, and not all EV models are suitable for providing ancillary services. Consequently, the proposed model serves as a valuable pre-evaluation tool for conducting vehicle-specific assessments, facilitating more effective integration of V2G capabilities in future applications.

ORCID iDs

Shi, Xiang and Bayram, I. Safak ORCID logoORCID: https://orcid.org/0000-0001-8130-5583;
CORE (COnnecting REpositories)