Controlling transient gas flow in real-world pipeline intersection areas

TL;DR

This paper presents a mixed integer programming approach to automate and optimize the control of compressor stations in gas pipeline intersections, aiming to adapt configurations over time while minimizing operational changes.

Contribution

It introduces a novel model and algorithms for real-time control of complex compressor station configurations in pipeline networks.

Findings

Effective optimization of station configurations on real-world data

Reduced operational changes while meeting performance demands

Demonstrated scalability and efficiency of the approach

Abstract

Compressor stations are the heart of every high-pressure gas transport network. Located at intersection areas of the network they are contained in huge complex plants, where they are in combination with valves and regulators responsible for routing and pushing the gas through the network. Due to their complexity and lack of data compressor stations are usually dealt with in the scientific literature in a highly simplified and idealized manner. As part of an ongoing project with one of Germany's largest Transmission System Operators to develop a decision support system for their dispatching center, we investigated how to automatize control of compressor stations. Each station has to be in a particular configuration, leading in combination with the other nearby elements to a discrete set of up to 2000 possible feasible operation modes in the intersection area. Since the desired performance of the station changes over time, the configuration of the station has to adapt. Our goal is to minimize the necessary changes in the overall operation modes and related elements over time, while fulfilling a preset performance envelope or demand scenario. This article describes the chosen model and the implemented mixed integer programming based algorithms to tackle this challenge. By presenting extensive computational results on real world data we demonstrate the performance of our approach.