Distributionally robust bidding of a hybrid high-temperature thermal and compressed air energy storage system in power markets under wind power uncertainty

Compressed Air Energy Storage is a large-scale energy storage technology capable of participating in power markets while being integrated with power systems to facilitate higher levels of wind power integration. This paper investigates the potential of a new hybrid High-temperature thermal and Compressed Air Energy Storage (Hi-CAES) system to participate in energy and reserve markets to present its commercial value while supporting power system operation and wind power integration. A bidding model is proposed and formulated as a bi-level distributionally robust optimisation (DRO) problem. The upper-level problem aims to maximise Hi-CAES's financial gains through strategic bidding, while the lower-level problem models the energy and reserve markets clearing as well as power system scheduling subject to the integration of variable wind power. A multi-stage Wasserstein DRO method is developed to capture the non-anticipative wind uncertainty during the scheduling process. In addition, the bidding model incorporates a novel adaptive reserve requirement (ARR) mechanism, which adaptively sets reserve requirements for market participants to maintain system power balance under wind power uncertainty. Case studies on the UK regional 45-bus system validate the effectiveness of the proposed model and demonstrate the operational and economic advantages of the Hi-CAES system and ARR mechanism.