Natural Gas Short-Term Operation Problem with Dynamics: A Rank Minimization Approach

TL;DR

This paper introduces a rank minimization approach to accurately model natural gas network dynamics in short-term operation problems, outperforming traditional simplified equations in solution quality and computational efficiency.

Contribution

It proposes a convex relaxation scheme using rank minimization for non-linear gas flow equations, improving solution accuracy and efficiency in dynamic natural gas network optimization.

Findings

The proposed model captures gas demand fluctuations through pipeline pressure adjustments.

The method improves solution optimality compared to traditional Weymouth equation-based models.

Scalability is verified in a case study demonstrating computational efficiency.

Abstract

Natural gas-fired generation units can hedge against the volatility in the uncertain renewable generation, which may occur during very short periods. It is crucial to utilize models capable of correctly capturing the natural gas network dynamics induced by the volatile demand of gas-fired units. The Weymouth equation is commonly implemented in literature to avoid dealing with the mathematical complications of solving the original governing differential equations of the natural gas dynamics. However, it is shown in this paper that this approach is not reliable in the short-term operation problem. Here, the merit of the non-convex transient model is compared with the simplified Weymouth equation, and the drawbacks of employing the Weymouth equation are illustrated. The results demonstrate how changes in the natural gas demand are met by adjustment in the pressure within pipelines rather than the output of natural gas suppliers. This work presents a convex relaxation scheme for the original non-linear and non-convex natural gas flow equations with dynamics, utilizing a rank minimization approach to ensure the tightness. The proposed method renders a computationally efficient framework that can accurately solve the non-convex non-linear gas operation problem and accurately capture its dynamics. Also, the results suggest that the proposed model improves the solution optimality and solution time compared to the original non-linear non-convex model. Finally, the scalability of the proposed approach is verified in the case study.