Heterogeneous Energy Storage Optimization for Microgrids

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.

Department(s)

Electrical and Computer Engineering

Sponsor(s)

National Science Foundation (U.S.)
United States. Department of Energy

Comments

This work was supported in part by the U.S. National Science Foundation under Engineering Research Centers Award EEC-08212121, and in part by the U.S. Department of Energy under SunShot Award DE-0006341. Paper no. TSG-01055-2014

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)

1949-3053; 1949-3061

Document Type

Article - Journal

Document Version

Citation

File Type

text

Language(s)

English

Rights

© 2016 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

Publication Date

01 May 2016

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