A two‐stage simulation‐based framework for optimal resilient generation and transmission expansion planning

Abstract

This paper presents a two‐stage resilient framework for generation and transmission expansion planning that profits static and dynamic models. The first stage problem finds the generation and transmission expansion results without considering extreme events. Given the planned power system, in the second stage, a simulation‐based method is employed to accurately model the effects of the severe events and measure the expected demand not served. The proposed framework updates the formulation of the planning problem to efficiently search for a new expansion plan resulting in higher resilience levels. This paper uses the maximizing social welfare in the planning model to find the optimal result. Also, the effect of maximizing social welfare in updating the formulation of the planning problem is investigated. In this case, the planning problem is a bi‐level problem that using the primal‐dual formulation leads to a single‐level problem called a mathematical program with equilibrium constraints. After the linearization, the planning problem becomes a mixed‐integer linear programming problem. The planning model profits from reinforced transmission lines to improve power system resilience. The proposed framework is evaluated on 4‐bus, 6‐bus, and 118‐bus systems. According to the results, the proposed method with a low additional cost boosts power system resilience.