Abstract
Due to their capacities and quick response, Electric Vehicle (EV) batteries can be used to support a number of power grid services and form a Vehicle-to-Grid (V2G) system. When aggregated and properly managed EV batteries can provide important ancillary services such as peak load levelling and frequency regulation. EVs can also provide various demand response services and help in renewable energy integration. The major challenge for having a wide-scale V2G system to effectively provide the above services is the availability of power which is limited by the battery degradation and the battery cycle life. The battery cycle life is inversely proportional to the charge/discharge cycles the battery goes through during its operation. Therefore, the charge/discharge operation should be optimized to maximize the benefit for both the EV owners and the grid operator. In this paper, we develop an EV charge/discharge optimization model that incorporates frequency regulation and electricity prices from both real and forecasting models into the objective function of the model. We develop a prediction and optimization model to reflect the effects of dynamic and static electricity and regulation prices on the battery cycle life. We present a case study for the charge/discharge scheduling problem utilizing real, predicted regulation and electricity hourly pricing.
Highlights
The state of the art in the electrified transportation system is a standard shift from conventional Internal Combustion Engine (ICE)-based vehicles to more reliable, efficient and cleaner electrified vehicles [1]
As previously discussed, we focus on the impact of frequency regulation signals on the cost of providing V2G services
We briefly describe how we obtained different frequency regulation price signals for the Electric Vehicle (EV) charge scheduling optimization model and how the frequency regulation signals interact with the optimization model
Summary
The state of the art in the electrified transportation system is a standard shift from conventional Internal Combustion Engine (ICE)-based vehicles to more reliable, efficient and cleaner electrified vehicles [1]. Based on several feasibility studies, Electric Vehicle (EV) batteries can be used to deliver power back to the grid and provide support when the vehicles are parked and connected to the grid [2], [3]. The power from EV batteries can be aggregated and fed back to the grid to participate in demand-side management programs and provide various ancillary services such as frequency regulation, Volt-VAR control and renewable energy integration in a distributed Vehicle-to-Grid (V2G) infrastructure [4]. V2G involves algorithms and techniques that can be implemented in the EVs, the charging stations, user control systems, grid control centers, grid generation, and distribution systems. These V2G sub-systems exchange information and data required to implement the techniques
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