Resilience-Motivated Distribution System Restoration Considering Electricity-Water-Gas Interdependency

TL;DR

This paper presents a novel optimization-based method for restoring electricity, water, and gas services after outages, accounting for their interdependencies to improve resilience of critical infrastructure systems.

Contribution

It introduces a mixed-integer second-order cone programming approach that models interdependent networks and their operational constraints for efficient service restoration.

Findings

The method effectively allocates resources considering interdependencies.

Convex relaxation provides exact solutions.

Numerical simulations validate the approach on benchmark models.

Abstract

A major outage in the electricity distribution system may affect the operation of water and natural gas supply systems, leading to an interruption of multiple services to critical customers. Therefore, enhancing resilience of critical infrastructures requires joint efforts of multiple sectors. In this paper, a distribution system service restoration method considering the electricity-water-gas interdependency is proposed. The objective is to provide electricity, water, and natural gas supplies to critical customers in the desired ratio according to their needs after an extreme event. The operational constraints of electricity, water, and natural gas networks are considered. The characteristics of electricity-driven coupling components, including water pumps and gas compressors, are also modeled. Relaxation techniques are applied to nonconvex constraints posed by physical laws of those networks. Consequently, the restoration problem is formulated as a mixed-integer second-order cone program, which can readily be solved by the off-the-shelf solvers. The proposed method is validated by numerical simulations on electricity-water-gas integrated systems, developed based on benchmark models of the subsystems. The results indicate that considering the interdependency refines the allocation of limited generation resources and demonstrate the exactness of the proposed convex relaxation.