Modelling and Simulation of Gas Distribution Networks using Proper Orthogonal Decomposition

Abstract

Gas distribution networks are systems with large pipelines, storage units, compressors, and many other devices such as regulators and valves. These networks cover broad geographical area and their analysis require large human resources, equipment and time which can lead to human/measurement device errors. To avoid these errors, one possibility is to analyse the network through modeling and simulation. This will require a mathematical model of the complete network and a computationally efficient simulation of the large scale complex network. In this thesis we explore fast simulation techniques for such complex models using model order reduction. The concept of model order reduction is to approximate large-scale dynamical systems effectively and efficiently into much smaller dimensions and produce nearly the same input/output characteristics. We observe the applicability of proper orthogonal decomposition (POD) based model order reduction on gas distribution network models as they are well used for nonlinear systems in the literature. A comparison between the original and the reduced models is made in terms of computational time and accuracy using different gas networks. Numerical analysis show that reduced order model is highly accurate, stable and takes lesser time to simulate as compared to the original model.