Although extreme natural disasters have occurred all over the world throughout history, power systems planners do not usually recognize them within network investment methodologies. Moreover, planners had historically focused on reliability approaches based on average (rather than risk) performance indicators, undermining the effects of high impact and low probability events on investment decisions. To move towards a resilience centred approach, we propose a practical framework that can be used to identify network investments that offer the highest level of hedge against risks caused by natural hazards. In a first level, our framework proposes network enhancements and, in a second level, uses a simulation to evaluate the resilience level improvements associated with the network investment propositions. The simulator includes 4 phases: threat characterization, vulnerability of systems components, system response, and system restoration, which are simulated in a sequential Monte Carlo fashion. We use this modeling framework to find optimal portfolio solutions for resilient network enhancements. Through several case studies with applications to earthquakes, we distinguish the fundamental differences between reliability- and resilience-driven enhancements, and demonstrate the advantages of combining transmission investments with installation of backup distributed generation.

中文翻译：

---

确定针对自然灾害的弹性网络投资的最佳组合，并将其应用于地震

尽管历史上世界各地都发生过极端自然灾害，但电力系统规划人员通常不会在网络投资方法中认识到它们。此外，规划人员历来专注于基于平均（而非风险）绩效指标的可靠性方法，削弱了高影响和低概率事件对投资决策的影响。为了转向以恢复力为中心的方法，我们提出了一个实用的框架，可用于识别网络投资，以对自然灾害引起的风险提供最高水平的对冲。在第一级，我们的框架提出网络增强，在第二级，使用模拟来评估与网络投资主张相关的弹性水平改进。模拟器包括4个阶段：威胁特征、系统组件的脆弱性、系统响应和系统恢复，以顺序蒙特卡罗方式模拟。我们使用此建模框架来寻找用于弹性网络增强的最佳投资组合解决方案。通过几个应用于地震的案例研究，我们区分了可靠性驱动和弹性驱动增强之间的根本区别，并展示了将输电投资与安装备用分布式发电相结合的优势。