Chance-Constrained Microgrid Energy Management with Flexibility Constraints Provided by Battery Storage
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abstract
Battery storage devices can potentially provide multiple services to microgrids. However, concurrent modeling and formulation of multiple services in grid management is a challenging problem. This paper proposes an energy management approach for microgrids including electrical and thermal forms of energy sources. The proposed approach takes advantage of battery storage devices for providing multiple services by applying chance-constrained optimization. The battery storage is deployed for 5-minute load following and energy arbitrage purposes. In addition, we have formulated a set of flexibility constraints, taking advantage of battery's fast ramping capabilities, to enhance microgrid reliability in response to short-term solar power and load fluctuations. That is, the battery is deployed for load following, energy arbitrage, and regulation reserve procurement. Chance constraints are implemented to handle uncertainties of solar generation and load forecasting errors. Interdependencies between thermal and electrical energies are taken into account in the proposed approach. Numerical results show the effectiveness of the proposed approach to handle uncertainties, alleviate the short-term fluctuations, and enhance grid flexibility and reliability.
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2019 IEEE Texas Power and Energy Conference (TPEC)
