No abstract

Different scenarios at different scales must be studied to help define long term policies to decarbonate our societies. In this work, we analyse the Belgian energy system in 2035 for different carbon emission targets, and accounting for electricity, heat, and mobility. To achieve this objective, we applied the EnergyScope Typical Days open source model, which optimises both the investment and the operation strategy of a complete energy system for a target year. The model includes 96 technologies and 24 resources that have to supply, hourly, the heat, electricity, mobility, and non-energy demands. In line with other research, we identify and quantify, with a merit order, different technological steps of the energy transition. The lack of endogenous resources in Belgium is highlighted and estimated at 275.6 TWh/y. It becomes obvious that additional potentials shall be obtained by importing renewable fuels and/or electricity, deploying geothermal energy, etc. Aside from a reduction of the energy demand, a mix of solutions is shown to be, by far, the most cost effective to reach low carbon emissions.

Wind and solar energies present a time and space disparity that generally leads to a mismatch between the demand and the supply. To harvest their maximum potentials, one of the main challenges is the storage and transport of these energies. This challenge can be tackled by electrofuels, such as hydrogen, methane, and methanol. They offer three main advantages: compatibility with existing distribution networks or technologies of conversion, economical storage solution for high capacity, and ability to couple sectors (i.e., electricity to transport, to heat, or to industry). However, the level of contribution of electric-energy carriers is unknown. To assess their role in the future, we used whole-energy system modelling (EnergyScope Typical Days) to study the case of Belgium in 2050. This model is multi-energy and multi-sector. It optimises the design of the overall system to minimise its costs and emissions. Such a model relies on many parameters (e.g., price of natural gas, efficiency of heat pump) to represent as closely as possible the future energy system. However, these parameters can be highly uncertain, especially for long-term planning. Consequently, this work uses the polynomial chaos expansion method to integrate a global sensitivity analysis in order to highlight the influence of the parameters on the total cost of the system. The outcome of this analysis points out that, compared to the deterministic cost-optimum situation, the system cost, accounting for uncertainties, becomes higher (+17%) and twice more uncertain at carbon neutrality and that electrofuels are a major contribution to the uncertainty (up to 53% in the variation of the costs) due to their importance in the energy system and their high uncertainties, their higher price, and uncertainty.