A study of tropical cyclone impact on the power distribution grid in South Korea for estimating damage - Oh, Seongmun; Jufri, Fauzan Hanif; Choi, Min Hee; Jung, Jaesung (Renewable and Sustainable Energy Reviews, 2022)
Extreme weather events such as tropical cyclones (TC) are considered the most significant weather events causing severe damage to the power distribution grid. However, few or no studies have been performed at the perspectives of the power system although it is necessary, but a relevant study has recently received attention in South Korea. Accordingly, the motivation of this paper addresses the need to present a study of the impact of TCs, focusing on the analysis and the estimation of TC-induced damage. The study uses three sets of historical data: TC data, power distribution grid damage data, and local weather data from 2008 to 2018. Using these data, first, this paper provides an overview of the damage characteristics to understand power system damage. TC, local weather, and TC-induced damage data are analyzed to find their correlated characteristic. Then, TCs are classified by their track patterns associated with the damage characteristic. The importance of TC track is proved by the significance test and comparing the damages by TC tracks. Furthermore, the underlying key hazard variables (i.e., TC and local weather variables) associated with TC-induced damages are identified. Lastly, this paper proposes a multi-stage damage estimation methodology to evaluate the intensity of TC-induced damages using identified major TCs and local weather variables as well as TC tracking information. Therefore, this study will provide useful insights to assess TC-induced damages from the power system perspective in South Korea.
Keywords: Cyclone tracks; Grid resilience; Induced damage; Machine-learning; Power; Power distribution grids; Power system damage; South Korea; System damage; Tropical cyclone; Data analysis; Grid resilience; Machine learning; Power distribution grid; Power system damage; Tropical cyclone