论文标题

SA-HMTS:使用社区微电网的安全和自适应分层的多时间尺度框架

SA-HMTS: A Secure and Adaptive Hierarchical Multi-timescale Framework for Resilient Load Restoration Using A Community Microgrid

论文作者

Shirsat, Ashwin, Muthukaruppan, Valliappan, Hu, Rongxing, Paduani, Victor, Xu, Bei, Song, Lidong, Li, Yiyan, Lu, Ning, Baran, Mesut, Lubkeman, David, Tang, Wenyuan

论文摘要

分配系统集成的社区微电网(CMG)可以在延长持续时间中恢复负载。在这种情况下,CMG的资源可用性有限,缺乏强大的网格支持以及增加需求供应不确定性的挑战。本文提出了一个安全且适应性的三阶段分层多时间尺度框架,用于调度和实时(RT)与混合光伏系统的CMG调度,以应对这些挑战。该框架使CMG能够动态扩展其边界以支持相邻的网格部分,并适应不断变化的预测错误影响。第一阶段解决了随机的延长持续时间调度(ED)问题,以获取最佳资源配给的推荐计划。中级近实时(NRT)调度阶段更新EDS时间表,使用新获得的预测更接近调度时间,然后进行RT调度阶段。为了使派遣决定更加安全和强大,以预测错误,提出了一个名为“延迟追索”的新颖概念。该方法通过修改后的IEEE 123-BUS系统上的数值模拟进行评估,并使用Opendss/opendss/coldware-In-in-op-In-In-In-In-In-in-op仿真进行了验证。结果表明,在众多操作场景下,在最大化负载供应和连续的安全CMG操作方面表现出了卓越的性能。

Distribution system integrated community microgrids (CMGs) can partake in restoring loads during extended duration outages. At such times, the CMG is challenged with limited resource availability, absence of robust grid support, and heightened demand-supply uncertainty. This paper proposes a secure and adaptive three-stage hierarchical multi-timescale framework for scheduling and real-time (RT) dispatch of CMGs with hybrid PV systems to address these challenges. The framework enables the CMG to dynamically expand its boundary to support the neighboring grid sections and is adaptive to the changing forecast error impacts. The first stage solves a stochastic extended duration scheduling (EDS) problem to obtain referral plans for optimal resource rationing. The intermediate near-real-time (NRT) scheduling stage updates the EDS schedule closer to the dispatch time using newly obtained forecasts, followed by the RT dispatch stage. To make the dispatch decisions more secure and robust against forecast errors, a novel concept called delayed recourse is proposed. The methodology is evaluated via numerical simulations on a modified IEEE 123-bus system and validated using OpenDSS/hardware-in-loop simulations. The results show superior performance in maximizing load supply and continuous secure CMG operation under numerous operating scenarios.

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