Data-Driven Resilience Enhancement for Power Distribution Systems Against Multishocks of Earthquakes

Earthquakes, which consist of one intensive main shock and a series of aftershocks, can significantly damage power distribution systems (PDSs). In this article, a data-driven PDS resilience enhancement strategy is proposed against multishocks of earthquakes. In particular, the investment and prepositioning of mobile emergency generators (MEGs) is determined against multishocks of earthquakes. The reallocation of MEG and the repair scheduling are obtained considering aftershocks and postrestoration failures. A resistibility index (RI) is developed based on hierarchical hidden Markov model (HHMM) for stochastic resilience evaluation. The historical earthquake data are incorporated into the HHMM as observed information of multishocks of earthquakes. Based on the RI, the problems of prepositioning and reallocation of MEGs are formulated as mixed-integer programming problems. The problem of repair scheduling is formulated as an adaptive multiperiod two-stage stochastic programming problem, for which a revision period is introduced to allow the decisions to adapt to the uncertainties after the revision. To reduce the computational complexity, an iterative algorithm is presented based on linear programming relaxation. The strategy is verified via case studies on the IEEE 123-Node Test Feeder and historical earthquake data. It shows by considering RI, the resilience of restoration can be optimized against future shocks of earthquakes. Also, the overall consideration of MEG investment, prepositioning, reallocation, and repair scheduling against multishocks of earthquakes can achieve an improved restoration performance.