Tight Robust Formulation for Uncertain Reserve Activation of an Electric Vehicle Aggregator

摘要

Power system decarbonisation is closely followed by the liberalization of ancillary services to secure a sufficient volume of services at all times. In Europe, system operators are adjusting ancillary services markets to allow entrance of new players. Reserves are the first ones to be liberalized and one of their potential providers are electric vehicles. They can decrease their charging costs through reserve provision under negligible affect on users comfort. However, reserves are highly intertwined with uncertainty and depend on many parameters. To adequately address these uncertainties and safely bid in the markets, an aggregator must adequately integrate them in its optimal bidding algorithm. In this paper, a new robust model is proposed where a tight uncertainty set of reserve activation is created using a realistic reserve activation dataset. The tight robust framework is analysed on the electric vehicle feet operation under one aggregator. A sensitivity analysis is performed to find adequate boundaries of the uncertainty set. The results show that robust approach can be used to adequately address this uncertainty allowing the aggregator to choose its risk exposure and hedging strategy. Also, the results show that neglecting more than 1% of the most extreme activation volumes could lead towards too liberal models not securing the battery limits adequately.