Abstract
As microgrids evolve, it is reasonable to expect that a variety of energy storage systems (ESSs) with different operational characteristics will be used simultaneously. Because each storage system has different capabilities and capacities, they will complement each other, and be able to achieve more efficient and reliable results than if only a single type of system were used. However, integrating multiple types of storage comes with several implementation challenges. Existing control techniques used to charge and discharge different technologies are not sufficient to accommodate the electrochemical (or mechanical) differences. In this paper, we propose an interconnection topology and a reinforcement learning-based algorithm to optimize the coordination of different ESSs in a microgrid.
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