Simulation and State Estimation of Transient Flow in Gas Pipeline Networks Using a Transfer Function Model

TLDR

Dynamic simulation models of gas pipeline networks are needed for online applications such as state estimation and leak detection, and they must be computationally efficient. The study develops a dynamic simulator for gas pipeline networks based on a transfer function model of a pipeline. The simulator employs a transfer function model and the American Gas Association compressibility model within a data‑reconciliation framework to estimate state from pressure and flow measurements. The proposed method achieves accurate state estimation and computational efficiency comparable to a fully nonlinear finite difference method, successfully estimating noisy states and unknown node demands in simulated networks.

Abstract

Dynamic simulation models of gas pipeline networks can be used for on-line applications such as state estimation, leak detection, etc. A prime requirement for such models is computational efficiency. In this paper, a transfer function model of a gas pipeline is used as a basis for developing a dynamic simulator for gas pipeline networks. The simulator is incorporated in a data reconciliation framework, which is ideally suited for on-line state estimation based on all available measurements of pressures and flow rates. The American Gas Association (AGA) model is used for making realistic computations of the gas compressibility. Accuracy and computational efficiency of the proposed method are evaluated by comparing our results with those obtained using a fully nonlinear second-order accurate finite difference method. The ability of the proposed approach for obtaining accurate state estimation from noisy measurements is demonstrated through simulations on an example network. We also demonstrate the use of the proposed approach for estimating an unknown demand at any node by exploiting the redundancy in measurements.