Hybrid Energy Storage Implementation in DC and AC Power System for Efficiency, Power Quality and Reliability Improvements

Abstract

Battery storage devices have been widely utilized for different applications. However, for high power applications, battery storage systems come with several challenges, such as the thermal issue, low power density, low life span and high cost. Compared with batteries, supercapacitors have a lower energy density but their power density is very high, and they offer higher cyclic life and efficiency even during fast charge and discharge processes. In this dissertation, new techniques for the control and energy management of the hybrid battery-supercapacitor storage system are developed to improve the performance of the system in terms of efficiency, power quality and reliability. To evaluate the findings of this dissertation, a laboratory-scale DC microgrid system is designed and implemented. The developed microgrid utilizes a hybrid lead-acid battery and supercapacitor energy storage system and is loaded under various grid conditions. The developed microgrid has also real-time monitoring, control and energy management capabilities. A new control scheme and real-time energy management algorithm for an actively controlled hybrid DC microgrid is developed to reduce the adverse impacts of pulsed power loads. The developed control scheme is an adaptive current-voltage controller that is based on the moving average measurement technique and an adaptive proportional compensator. Unlike conventional energy control methods, the developed controller has the advantages of controlling both current and voltage of the system. This development is experimentally tested and verified. The results show significant improvements achieved in terms of enhancing the system efficiency, reducing the AC grid voltage drop and mitigating frequency fluctuation. Moreover, a novel event-based protection scheme for a multi-terminal DC power system has been developed and evaluated. In this technique, fault identification and classifications are performed based on the current derivative method and employing an artificial inductive line impedance. The developed scheme does not require high speed communication and synchronization and it transfers much less data when compared with the traditional method such as the differential protection approach. Moreover, this scheme utilizes less measurement equipment since only the DC bus data is required.