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This paper1 proposes a methodology of real-time supervision which allows maximizing ancillary services and contributing to the profitability of the Advanced Adiabatic Compressed Air Energy Storage (CAES). A real-time multi-objectives supervisor based on fuzzy logic is developed in order to maximize the economic gain of the storage, taking into account the buy/sell action and ancillary services (imperative and additional) of the storage, such as frequency control, congestion management and covering renewable energy production. The proposed supervisor is tested on the IEEE 14 bus test system. The results of the simulation show a significant economic gain of the storage when participating in ancillary services and in others additional services which need a real-time management.
adiabatic compressed Air energy storage, ancillary services, transmission network, energy supervision.
This study received funding from the ANR through the SACRE project whose partners are EDF, Géostock, Laboratories LMS, PROMES and L2EP.
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