Frequency Response From Aggregated V2G Chargers With Uncertain EV Connections

Fast frequency response (FR) is highly effective at securing frequency dynamics after a generator outage in lowinertia systems. Electric vehicles (EVs) equippedwith vehicle to grid (V2G) chargers could offer an abundant source of FR in future. However, the uncertainty associated with V2G aggregation, driven by the uncertain number of connected EVs at the time of an outage, has not been fully understood and prevents its participation in the existing service provision framework. To tackle this limitation, this paper, for the first time, incorporates such uncertainty into system frequency dynamics, from which probabilistic nadir and steady state frequency requirements are enforced via a derived moment-based distributionally-robust chance constraint. Field data from over 25,000 chargers is analysed to provide realistic parameters and connection forecasts to examine the value of FR from V2G chargers in annual operation of the GB 2030 system. The case study demonstrates that uncertainty of EV connections can be effectively managed through the proposed scheduling framework, which results in annual savings of 6,300 pound or 37.4 tCO(2) per charger. The sensitivity of this value to renewable capacity and FR delays is explored, with V2G capacity shown to be a third as valuable as the same grid battery capacity.

Automated summary

Fast frequency response (FR) is important in low-inertia systems to maintain frequency dynamics after a generator outage. This paper explores the potential of utilizing electric vehicles (EVs) with vehicle-to-grid (V2G) chargers as a source of FR. The uncertainty associated with V2G aggregation, caused by the unknown number of connected EVs during an outage, is addressed by incorporating it into the system's frequency dynamics. Field data from over 25,000 chargers is analyzed to evaluate the value of FR from V2G chargers in the GB 2030 system. The study shows that managing the uncertainty of EV connections through a proposed scheduling framework results in significant cost and carbon savings.