Power supply network is one of the most critical infrastructure networks of urban communities, but prone to the risk of cascading failures. In efforts toward disaster risk reduction of urban communities, it is thus important to identify critical cascading failure scenarios of the power supply networks and prepare effective countermeasures based on the identified scenarios. While addressing these issues, previous research efforts focused on cascading failure scenarios induced by a single component although those induced by multiple components may occur under natural or man-made disaster events. A major challenge in this problem is high computational cost required for simulating cascading failure scenarios and solving large-size optimization problems. This paper first presents an effective method to identify multi-component failure combinations entailing critical cascading failures in the network by using the overload cascading model, the multi-group non-dominated sorting genetic algorithm (MG-NSGA), and the concept of critical zone. Based on the identified critical scenarios, cost-effective retrofit combinations against the risk of cascading failures are also identified using the proposed ‘elite set updating’ method. The proposed disaster risk reduction decision-making methods are demonstrated and tested by numerical examples of two complex power supply networks.

供电网络是城市社区最关键的基础设施网络之一，但容易出现级联故障的风险。因此，在减少城市社区的灾难风险的过程中，重要的是确定电源网络的关键级联故障场景并根据确定的场景制定有效的对策。在解决这些问题时，先前的研究工作集中在由单个组件引起的级联故障场景，尽管由多个组件引起的故障场景可能在自然或人为灾难事件下发生。该问题的主要挑战是模拟级联故障场景和解决大型优化问题所需的高计算成本。本文首先提出了一种有效的方法，该方法利用过载级联模型，多组非支配排序遗传算法（MG-NSGA）和关键区域的概念来识别导致网络中严重级联故障的多组件故障组合。 。根据确定的关键情况，还可以使用提议的“精英集更新”方法来确定具有成本效益的改造组合，以应对级联故障的风险。通过两个复杂的供电网络的数值示例对所提出的减少灾害风险的决策方法进行了演示和测试。还使用提议的“精英集更新”方法确定了针对级联故障风险的具有成本效益的改造组合。通过两个复杂的供电网络的数值示例对所提出的减少灾害风险的决策方法进行了演示和测试。还使用提议的“精英集更新”方法确定了针对级联故障风险的具有成本效益的改造组合。通过两个复杂的供电网络的数值示例对所提出的减少灾害风险的决策方法进行了演示和测试。