Role of Hydrogen in a Low-Carbon Electric Power System: A Case Study

The European Union set a 2050 decarbonization target in the Paris Agreement to reduce carbon emissions by 90–95% relative to 1990 emission levels. The path toward achieving those deep decarbonization targets can take various shapes but will surely include a portfolio of economy-wide low-carbon energy technologies/options. The growth of the intermittent renewable power sources in the grid mix has helped reduce the carbon footprint of the electric power sector. Under the need for decarbonizing the electric power sector, we simulated a low-carbon power system. We investigated the role of hydrogen for future electric power systems under current cost projections. The model optimizes the power generation mix economically for a given carbon constraint. The generation mix consists of intermittent renewable power sources (solar and wind) and dispatchable gas turbine and combined cycle units fuelled by natural gas with carbon capture and sequestration, as well as hydrogen. We created several scenarios with battery storage options, pumped hydro, hydrogen storage, and demand-side response (DSR). The results show that energy storage replaces power generation, and pumped hydro entirely replaces battery storage under given conditions. The availability of pumped hydro storage and demand-side response reduced the total cost as well as the combination of solar photovoltaic and pumped hydro storage. Demand-side response reduces relatively costly dispatchable power generation, reduces annual power generation, halves the shadow carbon price, and is a viable alternative to energy storage. The carbon constrain defines the generation mix and initializes the integration of hydrogen (H₂). Although the model rates power to gas with hydrogen as not economically viable in this power system under the given conditions and assumptions, hydrogen is important for hard-to-abate sectors and enables sector coupling in a real energy system. This study discusses the potential for hydrogen beyond this model approach and shows the differences between cost optimization models and real-world feasibility.