Accurate self-scheduling model of adiabatic compressed air energy storage

Compressed air energy storage (CAES) has garnered significant attention as a promising technology for grid-scale energy storage that enhances the flexibility of power systems. However, the non-negligible off-design characteristics of a CAES system bring forth difficulties in ensuring accurate scheduling. This paper proposes an accurate and concise linear self-scheduling model for advanced adiabatic CAES systems that takes into account its off-design performance. The proposed model leverages the thermodynamic characteristics of CAES systems to formulate a hyperplane approximation. Importantly, this model accurately describes the off-design performance without requiring additional binary variables, and it exhibits strong agreement with thermodynamic models. The proposed model is found to have smaller errors than both direct linear and step models. By utilizing this model, an efficient self-scheduling decision was obtained, resulting in improved revenue. Finally, a comparison of selfscheduling revenues for different CAES systems with varying degrees of flexibility was conducted to evaluate the economy of off-design performance improvement. The most flexible configuration resulted in an 18 % increase in revenue for the electricity and reserve markets.