Optimal Charging Power Tracking Control of Advanced Adiabatic Compressed Air Energy Storage over Wide Operation Ranges

The dynamic response characteristics and off-design performance of advanced adiabatic compressed air energy storage (AA-CAES) are crucial when it plays role in power system frequency regulation. This paper proposes a computationally efficient optimal control strategy of AA-CAES for set-point charging power tracking, where the objective considers the tracking accuracy, speed and efficiency. A simplified state-space model of AA-CAES compression subsystem is established, where the off-design features and dynamic behaviors are described in a way that considers both precision and computational efficiency. Then, the power tracking problem is modeled as a differential algebraic equations (DAE)-constrained optimization problem, which is solved by a simultaneous collocation method. The air and heat transfer fluid mass flow rates are controlled coordinately to improve the tracking performance within the strict operational boundary. Simulation results validate the accuracy of the simplified model and the effectiveness of the solution method.