Microgrids can effectively integrate distributed generation (DG) to supply power to local loads. However, uncertainties from renewable DG and loads may lead to increased operating costs or operating constraint violations. To solve these issues, this paper proposes a two-stage coordination approach of price-based demand response (PBDR) and battery energy storage systems (BESSs) to minimize the total operating cost and enhance operational reliability. In the first stage, day-ahead PBDR is scheduled, aiming to shift loads to improve renewable energy utilization efficiency. Considering limited prediction horizon of uncertainties when dispatching BESSs, hourly state of charge (SoC) limits are also optimized over the whole-day horizon with consideration of BESS degradation cost in the day-ahead stage. Then in the second stage, the BESSs are dispatched hourly within the optimized SoC limits to track uncertainty realization and compensate the first-stage PBDR decisions. Furthermore, a two-stage interval optimization (TSIO) method is proposed to formulate the problem. Accordingly, a solution algorithm is developed to coordinately solve the two operation stages under the uncertainties. The proposed coordination approach is verified with uncertainty realization scenarios. The results indicate the high energy utilization efficiency and strong operational reliability of the proposed coordination approach.

中文翻译：

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基于间隔优化的微电网SOC管理的需求响应与电池储能系统协调

微电网可以有效地集成分布式发电（DG），以向本地负载供电。但是，可再生DG和负荷的不确定性可能导致运行成本增加或违反运行约束。为了解决这些问题，本文提出了基于价格的需求响应（PBDR）和电池能量存储系统（BESS）的两阶段协调方法，以最大程度地降低总运营成本并提高运营可靠性。在第一阶段，计划提前一天的PBDR，旨在转移负载以提高可再生能源的利用效率。考虑到在分发BESS时不确定性的有限预测范围，因此还考虑了提前一天的BESS降级成本，从而在全天范围内优化了小时计费状态（SoC）限制。然后在第二阶段 BESS在优化的SoC限制内每小时进行调度，以跟踪不确定性的实现并补偿第一阶段PBDR决策。此外，提出了一种两阶段间隔优化（TSIO）方法来解决该问题。因此，开发了一种求解算法来协调不确定性下的两个操作阶段。通过不确定性实现场景验证了所提出的协调方法。结果表明，该协调方法具有较高的能源利用效率和较强的运行可靠性。提出了求解算法来协调求解不确定性下的两个操作阶段。通过不确定性实现场景验证了所提出的协调方法。结果表明，该协调方法具有较高的能源利用效率和较强的运行可靠性。提出了求解算法来协调求解不确定性下的两个操作阶段。通过不确定性实现场景验证了所提出的协调方法。结果表明，该协调方法具有较高的能源利用效率和较强的运行可靠性。