Multi-Stage Linear Decision Rules for Stochastic Control of Natural Gas Networks with Linepack

TL;DR

This paper introduces multi-stage linear decision rules for controlling natural gas networks with linepack flexibility, aiming to balance renewable-induced uncertainties efficiently and improve operational stability.

Contribution

It develops a novel control policy leveraging linepack as a flexible resource, optimized via multi-stage linear decision rules for better uncertainty management in gas networks.

Findings

Linepack-based control reduces supply adjustment costs.

Policies minimize pressure variability under renewable uncertainties.

Topology optimization helps contain uncertainty propagation.

Abstract

The disturbances from variable and uncertain renewable generation propagate from power systems to natural gas networks, causing gas network operators to adjust gas supply nominations to ensure operational security. To alleviate expensive supply adjustments, we develop control policies to leverage instead the flexibility of linepack -- the gas stored in pipelines -- to balance stochastic gas extractions. These policies are based on multi-stage linear decision rules optimized on a finite discrete horizon to guide controllable network components, such as compressors and valves, towards feasible operations. Our approach offers several control applications. First, it treats the linepack as a main source of flexibility to balance disturbances from power systems without substantial impacts on nominal gas supply. Second, these policies can be optimized to minimize the variability (due to intermittency of renewables) and variance (due to their uncertainty) of network state variables, such as pressures. Finally, it enables topology optimization to decouple network parts and prevent uncertainty propagation through the network. This is demonstrated using illustrative numerical experiments.