Heterogeneous Energy Storage Optimization for Microgrids
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.
X. Qiu et al., "Heterogeneous Energy Storage Optimization for Microgrids," IEEE Transactions on Smart Grid, vol. 7, no. 3, pp. 1453-1461, Institute of Electrical and Electronics Engineers (IEEE), May 2016.
The definitive version is available at https://doi.org/10.1109/TSG.2015.2461134
Electrical and Computer Engineering
National Science Foundation (U.S.)
United States. Department of Energy
Keywords and Phrases
Energy storage; Reinforcement learning; Charge and discharge; Control techniques; Energy Storage Systems (ESSs); Interconnection topologies; Operational characteristics; Reliable results; Storage optimization; Storage systems; Electric power distribution; Batteries; Energy management; Energy storage; Renewable energy sources
International Standard Serial Number (ISSN)
Article - Journal
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