Fast and reliable transient simulation and continuous optimization of large-scale gas networks

Pia Domschke,Jens Lang,Oliver Kolb

doi:10.1007/s00186-021-00765-7

Abstract

We are concerned with the simulation and optimization of large-scale gas pipeline systems in an error-controlled environment. The gas flow dynamics is locally approximated by sufficiently accurate physical models taken from a hierarchy of decreasing complexity and varying over time. Feasible work regions of compressor stations consisting of several turbo compressors are included by semiconvex approximations of aggregated characteristic fields. A discrete adjoint approach within a first-discretize-then-optimize strategy is proposed and a sequential quadratic programming with an active set strategy is applied to solve the nonlinear constrained optimization problems resulting from a validation of nominations. The method proposed here accelerates the computation of near-term forecasts of sudden changes in the gas management and allows for an economic control of intra-day gas flow schedules in large networks. Case studies for real gas pipeline systems show the remarkable performance of the new method.

Highlights

The ongoing replacement of traditional energy production by coal fired and nuclear plants with gas consuming facilities has rapidly increased the role of natural gas transport through large networks
Natural gas is considered as a bridging combustible resource on the way towards a future energy mix mainly based on low-carbon and regenerative energy (IEA 2019)
To enable an efficient usage within a nonlinear optimization, we extend the approximate convex decomposition developed in Hiller and Walther (2017), Lien and Amato (2006)

Summary

Introduction

The ongoing replacement of traditional energy production by coal fired and nuclear plants with gas consuming facilities has rapidly increased the role of natural gas transport through large networks. Model-space-time-adaptive simulations provide accuracy bounds for target functionals and can be viewed as an efficient way to automatically and safely reduce the order of the gas network model They can be computed in the range of seconds for several hundreds of edges including pipes, valves, and compressor stations. An outer linear approximation of the feasible states of a compressor station is proposed in Walther and Hiller (2017) This results in a characteristic diagram given by a polyhedral model in the (Q,Had)-space, where Q = qρ0/ρ is the volumetric flow rate in m3/s and Had is the adiabatic head of the compressor defined by the gas compression from pin to pout:. We will give a brief overview on the main ingredients

Adaptive network simulation

Gradient-based optimization methods

Network with three compressor stations

Conclusion and outlook