Quantifying the Aggregate Flexibility of Electric Vehicle Charging Stations for Market-based Congestion Management Services

Abstract: Electric vehicles (EVs) play a crucial role in the transition towards sustainable modes of transportation and thus are critical to the energy transition. As their number grows, managing the aggregate power of EV charging is crucial to maintain grid stability and mitigate congestion. This study analyses more than 500 thousand real charging transactions in the Netherlands to explore the challenge and opportunity for the energy system presented by EV growth and smart charging flexibility. Specifically, it analyses the collective ability to provide congestion management services according to the specifications of those services in the Netherlands. In this study, a data-driven model of charging behaviour is created to explore the implications of delivering dependable congestion management services at various aggregation levels and types of service. The probabilistic ability to offer different flexibility products, namely, redispatch and capacity limitation, for congestion management, is assessed for different categories of charging stations (CS) and dispatch strategies. These probabilities can help EV aggregators, such as charging point operators, make informed decisions about offering congestion mitigation products per relevant regulations and distribution system operators to assess their potential. Further, it is shown how machine learning models can be incorporated to predict the day-ahead consumption, followed by operationally predicting redispatch flexibility. The findings demonstrate that the timing of EV arrivals, departures, and connections plays a crucial role in determining the feasibility of product offerings, and dependable services can generally be delivered using a sufficiently large number of CSs.