The study relies on the Artelys Crystal Super Grid modelling platform, which has enabled us to represent the power system and its interaction with gas and heat vectors with an unprecedented level of detail thanks to its advanced features such as multi-energy modelling, investment planning, and ability to use high-performance computing infrastructure.
In fact, the study relies on the optimisation of the electricity mix (generation, storage, network) and of its ability to produce and inject synthetic natural gas (via electrolysis and subsequent methanation) and heat (via heat pumps and electric heaters) in gas and district heating networks. The investments and their management to ensure the power demand-supply equilibrium is met at all times are jointly optimised with an hourly time resolution over the whole year, using a spatial resolution where France is split in 21 regions.
The study shows that at the 2050 horizon in the context of a fully decarbonised power sector, the decarbonisation of the gas and heat sectors mainly depends on the CO2 price. For CO2 prices above 100 €/tonne, heat and hydrogen production become economically viable, and for CO2 prices above 300 €/tonne the production of synthetic natural gas from renewable electricity to replace fossil gas is found to be profitable.
— Artelys is working with the Paris City Council on the development of data-centric solutions. These projects aim at making the most of the data available to the Parisian community in order to improve the quality of public policies.
— We are pleased to announce that Artelys Knitro 12.4, the new version of the leading nonlinear optimization solver, is now available! Check out how its improvements on performance and interface versatility can help you leverage mathematical optimization when tackling your problems.
— Within the INSULAE project, Artelys develops a tool for the strategic planning of the energy transition of European Union islands.
— Watch the video presenting the Artelys Crystal Energy Planner software, entirely dedicated to the operational scheduling of energy systems.
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