A Resilience Assessment Framework for Distribution Systems Under Typhoon Disasters

With the increase of extreme natural disasters and the frequent occurrence of man-made attacks, resilience studies of power grids have attracted much attention, among which resilience assessment reflects the resistance and resilience of power systems to cope with extreme disasters. To improve the re...

Descripción completa

Guardado en:
Detalles Bibliográficos
Autores principales: Yuantao Wang, Tianen Huang, Xiang Li, Jian Tang, Zhenjie Wu, Yajun Mo, Lin Xue, Yixi Zhou, Tao Niu, Sicong Sun
Formato: article
Lenguaje:EN
Publicado: IEEE 2021
Materias:
Acceso en línea:https://doaj.org/article/aea06a1ef0e7460f9c3532fc5ca89616
Etiquetas: Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
Descripción
Sumario:With the increase of extreme natural disasters and the frequent occurrence of man-made attacks, resilience studies of power grids have attracted much attention, among which resilience assessment reflects the resistance and resilience of power systems to cope with extreme disasters. To improve the resilience of distribution grids under extreme weather conditions, this paper proposes a resilience assessment framework for distribution grids under typhoon disasters. First, a probabilistic generation model of typhoon is established. Second, a spatiotemporal vulnerability model of the distribution grid lines to quantify the spatiotemporal impacts of typhoon. Third, a breadth-first search algorithm is used to island the distribution grid, and the amount of load shedding of the islanded microgrid is calculated. Meanwhile, the resilience of the distribution grid was quantitatively assessed according to the proposed new resilience index. Finally, the feasibility of the proposed resilience assessment method is verified in the IEEE 33-bus test system, and the results show that the proposed method can accurately account for the impact of typhoon on the distribution grid and provides a quantitative reference basis for later power system planning and scheduling.