A new approach to identify the optimum frequency ranges of the constituent storage devices of a hybrid energy storage system using the empirical mode decomposition technique. (July 2022) - Hettiarachchi, Dilum; Rajakaruna, Sumedha; Choi, San Shing; Ghosh, Arindam
Abstract: Empirical mode decomposition technique is used to extract the implicit mode components contained in the net power of a photovoltaic-powered nanogrid embedded within a microgrid. Statistical analysis of the magnitudes, instantaneous frequencies and energy contents of the components shows the dominance of the daily and yearly cyclic modes. Taking into consideration the frequency range of the modes, smoothing of the high- and low-frequency mode components is then realized through the respective buffering actions of a supercapacitor and a battery in a hybrid energy storage system. The optimum frequency ranges of the supercapacitor and the battery to achieve the lowest cost per kWh storage capacity for the designed hybrid energy storage system are then determined in a direct and closed form. The proposed approach requires much reduced computational efforts, in comparison to existing methods which involve iterative search procedures. Highlights: The empirical mode decomposition identifies the dominant oscillating components in the net power of PV-powered prosumer. Based on the storage capacity-frequency characteristics of supercapacitor and Li-ion battery, the optimum operating frequency ranges of the two storages are determined. The novel approach to determine the cut-off frequency ensures the cost-effective HESS design. The proposed HESS design approach is direct and requires much less computation time compared to the existing optimization-based methods.