期刊
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY
卷 13, 期 1, 页码 44-55出版社
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSTE.2021.3103444
关键词
Uncertainty; Microgrids; Optimization; Batteries; State of charge; Load flow; Generators; Battery energy storage system; hybrid interval-robust optimization; microgrid; SoC interval management; second-order cone three-phase branch flow; uncertainty
资金
- ARC Research Hub for Integrated Energy Storage Solutions [IH180100020]
- UNSW Digital Grid Futures Institute
- ARC [DP200101197, DE210100274]
- Australian Research Council [DE210100274] Funding Source: Australian Research Council
This paper proposes an adaptive BESS dispatch method with SoC interval management for unbalanced three-phase microgrids. The method dispatches BESS within the SoC interval using a rolling horizon procedure and utilizes a hybrid interval-robust optimization method to solve the scheduling problem. Simulation results demonstrate the high efficiency and solution robustness of the proposed method.
Battery energy storage systems (BESSs) have been widely deployed in microgrids to deal with uncertain output power of renewable distributed generation (DG) and improve renewable energy utilization efficiency. However, due to the short-term dispatch mode and BESS capacity limitation, current BESS dispatch decisions may not be efficient from a whole-day perspective, leading to an inadequate/excessive state of charge (SoC) for subsequent dispatch. To address this issue, an adaptive BESS dispatch method with SoC interval management is proposed for unbalanced three-phase microgrids, aiming to minimize the operating cost. In a day-ahead stage, an SoC interval is optimized considering the uncertainties of renewable DG, loads and market prices. During the day, the BESS is dispatched inside the SoC interval with a rolling horizon procedure to track uncertainty realization. Accordingly, a hybrid interval-robust optimization method is developed to solve the proposed scheduling problem under the uncertainties and procure the optimal SoC interval. Particularly, a decomposing and alternating solution algorithm is developed to identify the pessimistic case based on robust optimization while the SoC interval is determined on the basis of interval optimization. Simulation results verify high efficiency and solution robustness of the proposed hybrid interval-robust adaptive BESS scheduling method.
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