Gas quality tracking

 Gas quality tracking Interface

Natural gases of different origin may vary significantly in terms of their composition and hence their calorific value. The calorific value of bio natural gas, which is increasingly upgraded to meet natural gas quality specifications and fed into grids, is usually 5-10% lower than that of the natural gas supplied in a service area. The calorific value of hydrogen is even lower by a factor of 3 (per cubic meter). The equipment installed on the gas customer’s premises normally only measures the gas volume, so how then can the energy content of the gas be determined correctly?

The billing of gas and the actual energy supplied is governed by various codes and standards. In Germany it is DVGW Code of Practise G685 which states that where several gases are fed into a pipeline system, the difference between their superior calorific values must not exceed 2%. If this limit cannot be met, then previously the network operator had no option but to measure the superior calorific value at each exit point, or to condition the gas supplied; in the case of bio natural gas, this was usually done by adding liquefied petroleum gas (propane). Both options come with significant costs for the network operator.

SmartSim offers a simple and efficient way of determining the superior calorific values needed for gas billing at exit points using gas quality tracking.

How does gas quality tracking work?

SmartSim relies on a number of input variables. Apart from network topology details, the tool requires measured values for the superior calorific value at all entry points and for the gas volumes at all entry and exit points. For gas distribution grids, which often have no volumetric flow meters at the exit points, the gas quantity taken can be determined using standard load profiles.

On the basis of this input data, which is generally available as hourly values, the flow condition of the entire network is determined by way of simulation. Using a special algorithm, gas packages are tracked backwards through the pipeline system from an exit point to the entry points. This algorithm – also referred to as the "back-propagation algorithm" – allows the operator to show at each exit point the percentages of the gases fed into the system as well as the transit times. One of the advantages of this method is that all relevant gas parameters (superior calorific value, normal density, gas components, Wobbe index, CO2 emission factor etc.) can be determined for each exit point on the basis of just one simulation run.

In practice, calorific value tracking takes place on a monthly basis, with the superior calorific value used for billing being shown as a volume-weighted monthly average for each exit point.

The validation of SmartSim is based on a statistical method – the Monte-Carlo simulation. This method, which is performed in accordance with the ISO Guide to the Expression of Uncertainty in Measurement (GUM), is a metrologically accepted way of determining measurement uncertainty for complex systems. It involves a random variation of the input variables in accordance with their measurement uncertainty and calculation of the impact on the output variable, e.g. the superior calorific value. Using a large number of simulation runs it is then possible to determine the uncertainty of measurement. The validation also involves technical measurement of the system with a mobile process gas chromatograph (PGC). Approval of the method by the responsible Office of Weights and Measures for fiscal gas metering has already been obtained by a large number of network operators in Germany.

Designed for transmission and distribution networks

Thanks to its very precise and efficient calculation model SmartSim can be used both for high-pressure systems and distribution grids without any issues. The calculation model was programmed in a discrete module - the SmartSim Kernel - which can be operated with a graphical user interface. The short calculation times allow even highly complex grids to be calculated within an acceptable time frame.

An interface for data import and export can be configured for different data and file formats (incl. XML, MSCONS, CSV), making connections to upstream or downstream IT systems really straightforward. The user interface can be operated intuitively.

Grid operators save costs where biogas is fed into their system

Grids that have to accommodate different gas qualities can be operated very flexibly by using tools such as SmartSim to track the superior calorific value of the gas throughout the grid. Where biogas plants feed into a natural gas pipeline, the calorific value of the biogas no longer needs to be brought in line with that of natural gas by adding propane. Apart from creating considerable cost savings, this also avoids additional CO2 emissions because propane is known for its adverse effect on the carbon footprint, which is the very thing the use of biogas is supposed to improve.

Gas quality tracking  Flowchart
E.ON in Essen
E.ON Metering GmbH