Abstract-A novel compressed air energy storage system for wind turbine is proposed. It captures excess power prior to electricity generation so that electrical components can be downsized for demand instead of supply. Energy is stored in a high pressure dual chamber liquid-compressed air storage vessel. It takes advantage of the power density of hydraulics and the energy density of pneumatics in the "open accumulator" architecture. A liquid piston air compressor/expander is utilized to achieve near-isothermal compression/expansion for efficient operation. A dynamic system model as well as control laws for optimizing the turbine power, delivering required electrical power and maintaining system pressure are developed. A set of simulation case studies demonstrate the operation of the system.
Heat transfer during compression of air in a long, thin tube is studied by CFD. The tube represents one of the many in a honeycomb geometry inserted in a liquid piston air compressor to minimize temperature rise. A dimensionless number for the heat flow rate that includes the changing heat transfer area between the tube wall and air during compression is used. From the CFD results, alinear relation between the inverse of this dimensionless heat flow rate and the Stanton number is found. Using thisrelation, the transient volume-averaged temperature, and heat flow rate from the air can be well predicted by thermodynamic modeling.With the heat transfer model, a non-linear ODE is solved numerically todetermine the average temperature and pressure. The application of this study can be found in liquid piston air compressors for compressed air energy storage systems.
Abstract-The power density and efficiency of high compression ratio (∼200:1) air compressors/expanders are crucial for the economical viability of a Compressed Air Energy Storage (CAES) system such as the one proposed in [1]. There is a trade-off between power density and efficiency that is strongly dependent on the heat transfer capability within compressor/expander. In previous papers, we have shown that the compression or expansion trajectory can be optimized so that for a given power, the efficiency can be optimized and vice versa. Theoretically, for high compression ratios, the improvement over ad-hoc trajectories can be significant-for example, at the same efficiency of 90%, the power can be increased by 3-5 folds [2], [3], [4], [5]. Yet, the optimal trajectories depend on the heat transfer coefficient profile that is often unknown. In this paper, we focus on the experimental study of an iterative control algorithm to track a compression trajectory that optimizes the efficiency-power trade-off in a liquid piston air compressor. First, an adaptive controller is developed to track any desired compression trajectory characterized by the temperature-volume profile. The controller adaptively estimates the unknown heat transfer coefficient. Second, the estimated heat transfer coefficient from one iteration is then used to estimate the optimal compression trajectory for the next iteration. As the estimate of the heat transfer coefficient improves from one iteration to the next, the quality of the estimated optimal trajectory also improves. This leads to successively improved efficiency. The experimental results of optimal trajectories show up to 2% improvement in compression efficiency compared to linear trajectories in a same power density.
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