Modelling, simulation and analysis of green gas injection into the gas distribution network

Abstract

The increase of the average world temperature, as a result of greenhouse gasses, is one of the greatest challenges the world is currently facing and will be facing in the future. One of the many efforts to reduce the increase of carbon dioxide, is to decarbonize the gas network by replacing natural gas with renewable gasses like green gas. Since the current gas network is not always suited for the injection of big green gas volumes, especially during summer periods, the process of decarbonizing the natural gas network requires adjustments of the current functioning of the gas network. Several technical adjustments for obtaining an increased green gas injection capacity exists, although, up to now, the potential green gas injection capacity obtained per solution was not known. Within this study, a dynamic gas network simulation model was developed wherein different gas network function strategies can be explored to obtain the potential green gas injection capacities. With the developed dynamic gas network simulation model one is capable to implement and simulate different gas distribution network configurations, specify green gas suppliers on the location of choice, simulate different gas demand scenarios and consumer profiles, adjust the city gate station pressure used for simulations of static- and dynamic pressure management, and to model the injection of excess green gas into a storage- and from the storage into the network. Within this study, the gas distribution network of Northeast Friesland, The Netherlands was analyzed on its green gas injection capacity after applying static pressure management, dynamic pressure management, and a pressure management strategy combined with storage. The gas network of Northeast Friesland was explicitly chosen since currently, green gas injection problems are experienced within this network. Following the results obtained from the simulations, a city gate station inlet pressure - demand table was defined. Within this table, the total gas demand measured within the network was plotted against the minimum city gate station inlet pressures, while still in compliance with the lower pressure boundary condition. Using this table, the optimal period to statically decrease- and increase the city gate station inlet pressures from 8.3 to 6.5 bar and from 6.5 bar to 8.3 bar, appeared to be respectively 1 May and 1 October. By changing the pressure to 6.5 bar, a safety margin of 1.5 bar was taken into account. For both static- and dynamic pressure management, green gas injection capacities ranging from 400 to 1600 m³/h, divided over three green gas suppliers, were analysed. The results were depicted against the total injectable hours, providing insight in the maximum green gas injection capacity while remaining eligible for the Stimulation of Sustainable Energy Production (SDE+) subsidy. Since with dynamic pressure management the city gate station can inject at lower inlet pressures, dynamic pressure management results in a greater green gas injection capacity. To point out, static pressure management provide 450 m³/h green gas injection capacity, whereas dynamic pressure management provides 650 m³/h green gas injection capacity without experiencing any injection problems.