Arif Fikri Malek

Power distribution systems face increasing threats from high-impact, low-probability (HILP) events caused by extreme weather conditions such as floods, typhoons, droughts, and heatwaves. These events often lead to power outages worldwide, highlighting the need for effective strategies to mitigate their impact. This work proposes an emergency response strategy that integrates network reconfiguration (NR) with the deployment of mobile emergency generators (MEGs) to enhance system resilience. The objective is to maximize power supply availability following HILP events. To achieve this, mixed-integer quadratic constraint programming (MIQCP) is used to optimize MEG deployment and network restoration. Additionally, improved quantitative resilience metrics are introduced to assess system degradation, pre-recovery, and recovery phases, enabling continuous resilience measurement and informed decision-making. Furthermore, an optimal capacity deployment strategy (OCDS) is proposed to ensure that MEGs are deployed with suitable capacities based on the specific needs of outage-affected areas. The effectiveness of the proposed strategy is demonstrated through tests on the IEEE 118 bus system. The results show a significant improvement of up to 100% in system resilience, reducing power outages and accelerating restoration. The findings confirm that integrating NR with optimized MEG deployment enhances service restoration, providing an effective approach for utilities to manage power disruptions.

Smart grid systems play a significant role in improving the resilience of distribution systems (DSs). In this paper, two strategies are proposed for implementation of a smart grid application: (a) a network reconfiguration and (b) a network reconfiguration with mobile emergency generator (MEGs) deployment. An improved set of resilience metrics to quantify and enhance the resiliency of distribution systems (DSs) is developed for the proposed optimization. The metrics aim to determine a suitable strategy and the optimal number and capacity of MEGs to restore the disconnected loads through the development of several microgrids. These metrics are then aggregated with the proposed strategy to develop an automated solution provider. The objective is to maximize system resilience considering the priority loads. The proposed resilience metrics are tested on the IEEE 33-Bus radial DSs. The case studies conducted proved the performance of the proposed power outage management strategy and resilience metrics in maximizing system resiliency for smart grids.