Resilience-oriented proactive operation strategy of coupled transportation power systems under exogenous and endogenous uncertainties

Abstract

This paper proposes a proactive resilience enhancement strategy for power systems under hurricanes, focusing on the coordinated scheduling of coupled transportation power systems (CTPS) with rail-based energy storage transportation (REST). To capture the strong uncertainties of hurricanes on CTPS, a hybrid endogenous and exogenous uncertainty set is developed. In the proposed uncertainty set, the pre-layout and trail accessibility of REST is endogenous, i.e., decision-dependent, and the operating state of transmission lines is exogenous, i.e., decision-independent. An innovative two-stage decision-dependent robust optimization (T-D${}^2$RO) problem is formulated to enhance the economic feasibility of the CTPS and meet load survivability requirements during hurricane. In particular, we introduce the structure of a mixed-integer programming problem with a maximum-minimum objective, ensuring post-event service protection by jointly optimizing the REST routing, load shedding, and generation curtailment in the worst-case scenario. The T-D${}^2$RO problem is addressed using a customized parameterized column-and-constraint generation (C&CG) algorithm, leveraging the structural characteristics of this complex problem. Numerical results for the exemplary CTPSs demonstrate that proactive deployment and adaptive routing of REST provide economically viable solutions for achieving grid resilience objectives. Moreover, the customized parameterized C&CG algorithm exhibits superior performance that reduces the computation time compared to nested C&CG, thus enabling efficient emergency response via coordinated network operations.