Robust Gas Pipeline Network Expansion Planning to Support Power System Reliability

TL;DR

This paper develops a robust optimization model for expanding gas pipeline networks to meet the uncertain and growing demands of gas-fired power plants, ensuring reliability and minimal cost.

Contribution

It introduces a novel mixed-integer second order cone formulation that accounts for demand variability and uncertainty in pipeline expansion planning.

Findings

Effective handling of demand uncertainty through robust optimization.

Simplification of the semi-infinite problem using monotonicity properties.

Successful application to the Belgian network test case.

Abstract

We examine the problem of optimal transport capacity expansion planning for a gas pipeline network to service the growing demand of gas-fired power plants that are increasingly used to provide base load, flexibility, and reserve generation for bulk electric system. The aim is to determine the minimal cost set of additional pipes and gas compressors that can be added to the network to provide the additional capacity to service future loads. This combinatorial optimization problem is initially formulated as a mixed-integer nonlinear program, which we then extend to account for the variability that is inherent to the demands of gas-fired electricity production and uncertainty in expected future loads. We consider here steady-state flow modeling while ensuring that the solution is feasible for all possible values of interval uncertainty in loads, which results in a challenging semi-infinite problem. We apply previously derived monotonicity properties that enable simplification of the problem to require constraint satisfaction in the two extremal scenarios only, and then formulate the robust gas pipeline network expansion planning problem using a mixed-integer second order cone formulation. We consider case studies on the Belgian network test case to examine the performance of the proposed approach.