Maintaining the accumulator pressure regardless of its energy level and tracking the power demanded by the electrical grid are two potential advantages of the Compressed Air Energy Storage (CAES) system proposed in [1, 2]. In order to achieve these goals, a nonlinear controller is designed motivated by an energy-based Lyapunov function. The control inputs of the storage system include displacement of the pump/motor in the hydraulic transformer and displacement of the liquid piston air compressor/expander. While the latter has a relatively low bandwidth, the former is a faster actuator with a higher bandwidth. In addition, the pneumatic path of the storage vessel that is connected to the liquid piston air compressor/expander has a high energy density, whereas the hydraulic path of the storage vessel is power dense. The nonlinear controller is then modified to achieve a better performance for the entire system according to these properties. In the proposed approach, the control effort is distributed between the two pump/motors based on their bandwidths: the hydraulic transformer reacts to high frequency events, while the liquid piston air compressor/expander performs a steady storage/regeneration task. As a result, the liquid piston air compressor/expander will loosely maintain the accumulator pressure ratio and the pump/motor in the hydraulic transformer will precisely track the desired generator power. This control scheme also allows the accumulator to function as a damper in the storage system by absorbing power disturbances from the hydraulic path generated by wind gusts.
- Dynamic Systems and Control Division
Nonlinear Controller Design With Bandwidth Consideration for a Novel Compressed Air Energy Storage System
Saadat, M, Shirazi, FA, & Li, PY. "Nonlinear Controller Design With Bandwidth Consideration for a Novel Compressed Air Energy Storage System." Proceedings of the ASME 2013 Dynamic Systems and Control Conference. Volume 3: Nonlinear Estimation and Control; Optimization and Optimal Control; Piezoelectric Actuation and Nanoscale Control; Robotics and Manipulators; Sensing; System Identification (Estimation for Automotive Applications, Modeling, Therapeutic Control in Bio-Systems); Variable Structure/Sliding-Mode Control; Vehicles and Human Robotics; Vehicle Dynamics and Control; Vehicle Path Planning and Collision Avoidance; Vibrational and Mechanical Systems; Wind Energy Systems and Control. Palo Alto, California, USA. October 21–23, 2013. V003T49A006. ASME. https://doi.org/10.1115/DSCC2013-4069
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