Capacity Estimation for Vehicle-to-Grid Frequency Regulation Services with Smart Charging Mechanism

TL;DR

This paper proposes a method to estimate the regulation capacity of vehicle-to-grid systems using a queueing model and introduces a smart charging mechanism to align real system performance with the model, aiding regulation contracts.

Contribution

It extends previous work by developing an adaptive smart charging mechanism that improves the accuracy of capacity estimation in V2G systems.

Findings

The queueing model effectively estimates regulation capacities.

The smart charging mechanism adapts to EV characteristics.

System performance aligns with the analytical model.

Abstract

Due to various green initiatives, renewable energy will be massively incorporated into the future smart grid. However, the intermittency of the renewables may result in power imbalance, thus adversely affecting the stability of a power system. Frequency regulation may be used to maintain the power balance at all times. As electric vehicles (EVs) become popular, they may be connected to the grid to form a vehicle-to-grid (V2G) system. An aggregation of EVs can be coordinated to provide frequency regulation services. However, V2G is a dynamic system where the participating EVs come and go independently. Thus it is not easy to estimate the regulation capacities for V2G. In a preliminary study, we modeled an aggregation of EVs with a queueing network, whose structure allows us to estimate the capacities for regulation-up and regulation-down, separately. The estimated capacities from the V2G system can be used for establishing a regulation contract between an aggregator and the grid operator, and facilitating a new business model for V2G. In this paper, we extend our previous development by designing a smart charging mechanism which can adapt to given characteristics of the EVs and make the performance of the actual system follow the analytical model.