On the Numerical Treatment of Interlaced Target Values -- Modeling, Optimization and Simulation of Regulating Valves in Gas Networks

TL;DR

This paper introduces two new mathematical models for regulating valves in gas networks, enabling dynamic control based on multiple target values, and compares simulation results with a commercial tool to enhance gas network management.

Contribution

The paper presents novel models for control valves in gas networks that incorporate multiple dynamic target values and prioritize them differently, advancing simulation and optimization capabilities.

Findings

Models successfully incorporate up to six target values.

Simulation results align with the commercial tool SIMONE.

Dynamic prioritization of target values is feasible at run-time.

Abstract

Due to the current and foreseeable shifts in energy production, the trading and transport operations of gas will become more dynamic, volatile, and hence also less predictable. Therefore, computer-aided support in terms of rapid simulation and control optimization will further broaden its importance for gas network dispatching. In this paper, we aim to contribute and openly publish two new mathematical models for regulators, also referred to as control valves, which together with compressors make up the most complex and involved types of active elements in gas network infrastructures. They provide full direct control over gas networks but are in turn controlled via target values, also known as set-point values, themselves. Our models incorporate up to six dynamical target values to define desired transient states for the elements' local vicinity within the network. That is, each pair of every two target values defines a bounding box for the inlet pressure, outlet pressure as well as the passing mass flow of gas. In the proposed models, those target values are prioritized differently and are constantly in competition with each other, which can only be resolved dynamically at run-time of either a simulation or optimization process. Besides careful derivation, we compare simulation and optimization results with predictions of the commercial simulation tool SIMONE.