Research Details

Abstract

After a blackout event, power system restoration is an essential activity for grid resilience; operators restart generators, re-establish transmission paths, and restore loads. With a goal of restoring electric service in the shortest time, the core decisions in restoration planning are to partition the grid into subnetworks, each of which has an initial power source for black-start (called sectionalization problem), and then restart all generators in each network (called generator startup sequencing (GSS) problem) as soon as possible. Due to their complexity, the sectionalization and GSS problems are usually solved separately, often resulting in a suboptimal solution. Our paper develops models and computational methods to solve the two problems simultaneously. We first study the computational complexity of the GSS problem and develop an efficient integer linear programming formulation. We then integrate the GSS problem with the sectionalization problem and develop an integer linear programming formulation for the parallel power system restoration (PPSR) problem to find exact optimal solutions. To solve larger systems, we then develop bounding approaches that find good upper and lower bounds efficiently. Finally, to address computational challenges for very large power grids, we develop a randomized approach to find a high-quality feasible solution quickly. Our computational experiments demonstrate that the proposed approaches are able to find good solutions for PPSR in up to 2,000-bus systems.

Type

Article

Author(s)

Sunil Chopra, Sangho Shim, Feng Qiu

Date Published

2023

Citations

Chopra, Sunil, Sangho Shim, and Feng Qiu. 2023. Parallel power system restoration. Informs Journal of Computing.(1): 233-247.