On the autocorrelation of measurement results for gas volume and calorific value in fiscal metering in gas grids

¹ VSL, Data Science & Modelling Department, Thijsseweg 11, 2629 JA Delft, The Netherlands
² TU/e, Eindhoven University of Technology, Department of Mathematics and Computer Science, Eindhoven, The Netherlands

^* Corresponding author: fgugole@vsl.nl

Published online: 7 April 2025

Abstract

The fiscal metering of natural gas is often performed using a flow meter and a gas chromatograph. The flow meter measures the volume flow rate of the gas and the gas chromatograph measures the composition, from which the calorific value is calculated. The energy is then calculated as the product of the volume and the calorific value. The uncertainty of the energy delivered (or received) is an important parameter for operating the gas grid. Currently, the energy values used to compute the total energy are considered mutually independent. However, the underlying processes affecting the gas flow through a pipe are continuous. We analysed the correlation between successive measurements due to temporal variations in the physical process by applying autoregressive moving average (ARMA) models to a set of measurement data taken at a metering station in the Dutch gas grid. The analysis showed that the volume time series can be modelled as an autoregressive model of order 1, while the time series of the calorific value can be described by an autoregressive model of order 2. These correlations lead to an increase of the instrumental measurement uncertainty associated to the total energy of about 50%.