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

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 that can adapt to given characteristics of the EVs and make the performance of the actual system follow the analytical model. Index Terms-Capacity, frequency regulation, queueing model, vehicle-to-grid (V2G).

Integrated Coordination of Electric Vehicle Operations and Renewable Energy Generation in a Microgrid

“…Its ideal control goal is to make power generation and consumption equal at all times [11]. However, in the real world, the goal is compromised to minimize the mismatch between them, overcoming unpredictable behaviors of grid entities.…”

Architecture of Energy Internet and Its Technologies in Application Reviewed

“…Recently, aggregation of V2G availability to provide ancillary service to System Operator is proposed as a new way of V2G [29]. Aided with advanced capacity estimation algorithm, aggregators can pool the dispersed dynamic availability of EVs and sum up to a contracted volume of ancillary service.…”

Real-time vehicle-to-grid control for frequency regulation with high frequency regulating signal

“…In [16], an approach for estimating achievable power capacity was proposed in a probabilistic manner, where capacity probability distribution was obtained by classifying EV groups and analyzing historical data. In [17], a queueing network of EVs was modeled to estimate the capacity for regulation up during under-frequency and regulation down during over-frequency. In [18], achievable V2G capacity was evaluated by calculating energy and power boundaries.…”