Resilience Assessment of Distributed Distribution Networks Taking into Account Sudden Natural Conditions

• Published in: 2024 IEEE 25th China Conference on System Simulation Technology and its Application (CCSSTA) pp. 789 - 795
• Main Authors: Song, Huayu, Kong, Xiangyu, Liu, Jiancun, Song, Xudong, Yang, Wenlong, Liu, Hongbin
• Format: Conference Proceeding
• Language: English
• Published: IEEE 21.07.2024
• Subjects: Analytical models; distributed power generation; Distribution networks; Meteorology; Power system reliability; Reliability; Reliability theory; Resilience; resilience assessment; Socioeconomics; sudden natural conditions; Timing; Uncertainty
• DOI: 10.1109/CCSSTA62096.2024.10691834

Understanding and improving the reliability of distribution grids under extreme weather conditions in the context of global climate change is important for ensuring stable socio-economic operation and improving the quality of life of the public. The current global assessment of distribution grid reliability under extreme weather conditions faces challenges such as insufficient data, modeling limitations, insufficient consideration of multidimensional impacts, technical resource constraints, and global change uncertainty. Through this paper, we hope to provide new perspectives and ideas for power system researchers and practitioners to jointly explore effective strategies for distribution network reliability and resilience under extreme weather. This study enhances the resilience assessment of distribution networks. It takes into account the generation and consumption dynamics of the network, the unpredictability of power supply and demand, as well as the impact of network topology and equipment on its reliability, and utilizes the Markov process to perform comprehensive reliability analysis of the network. In terms of assessment techniques, the Monte Carlo simulation method simulates the stochastic nature of severe weather, including its severity, timing, and duration, while quantifying its impact on the network through fault modeling. In terms of assessment metrics, the network is divided into two phases in order to establish a precise and clear system of network resilience assessment metrics. Through literature review, modeling analysis, and actual case studies, the current status of distributed generation application in extreme weather is explored, its impact on distribution network reliability is assessed, and future research directions and practical suggestions are proposed.