Severe disruptions caused by natural disasters have highlighted the significance of enhancing the distribution system resilience in recent years. However, due to severe uncertain characteristics of natural disasters, there exists an insufficient level of information to evaluate their behavior and consequences. Lack of information such as proper distribution functions for probabilistic methods or known intervals for robust optimization techniques may provide Distribution System Planners (DSPs) with inaccurate designs. This paper presents a new strategy based on Information Gap Decision Theory (IGDT) to facilitate decision making for DSPs in the face of extreme events. Moreover, a detailed analysis is performed to find a trade-off between the DG allocation and the hardening schemes, and to determine the best conservativeness degree in the IGDT approach. The presented resilience model is implemented on 33-bus and 94-bus distribution systems, and numerical case studies are analyzed to demonstrate the merits of the proposed approach. The results indicate that with a limited planning budget, the proposed trade-off analysis can optimally find the best DG allocation and hardening schemes to keep the load shedding level below a desired threshold following a severely uncertain extreme event.

中文翻译：

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基于信息鸿沟决策理论的主动分配系统规划以增强抵御能力

自然灾害造成的严重破坏突显了近年来增强配电系统弹性的重要性。但是，由于自然灾害的严重不确定性，因此评估其行为和后果的信息水平不足。缺少诸如概率方法的适当分配函数或鲁棒性优化技术的已知间隔之类的信息，可能会给分配系统计划者（DSP）提供不正确的设计。本文提出了一种基于信息鸿沟决策理论（IGDT）的新策略，以帮助DSP在面对极端事件时做出决策。此外，进行了详细的分析，以找到DG分配和强化方案之间的权衡，并确定IGDT方法的最佳保守度。所提出的弹性模型在33总线和94总线配电系统上实现，并通过数值案例研究分析以证明该方法的优点。结果表明，在规划预算有限的情况下，建议的权衡分析可以最佳地找到最佳的DG分配和硬化方案，以在严重不确定的极端事件之后将负荷削减水平保持在所需阈值以下。