Spatial incentives for power-to-hydrogen through market splitting

Germany's energy transition is associated with increasing congestion in the electricity transmission grids due to increasing infeed from renewable energy sources, especially from wind turbine installation at the periphery in coastal areas. Here, regional differences in generation and demand lead to grid bottlenecks from the northern to the southern parts of the country, thus leading to grid expansion requirements towards the load centers. However, long lead times for grid expansion in combination with the rapid expansion of renewables amplify the grid congestion. The provision of flexibility is one way to overcome this issue. In zonal markets, loadside flexibility can mitigate this situation, but it can also exacerbate it. Hence, adequate spatial incentives are crucial. To date, research has discussed possible market splits as a mid-term solution to improve congestion management, recognizing that the first-best solution of nodal prices is controversial in Europe. Nevertheless, adjusted bidding zones, e.g., by market splitting, can offer a solution. In the context of energy transition and ambitious decarbonization goals, hydrogen becomes important both as a storage option for renewable energy surplus and a green fuel for multiple usages. The German government already foresees 10 GW of electrolyser capacity by 2030, yet their locations will strongly affect congestion in the electricity grid. Therefore, this study investigated the impact of a possible market split on both the operation of and the investment in electrolysers. We apply an optimization approach including endogenous investment decisions linked to a detailed scheduling model. The investments are iteratively adjusted based on a Benders decomposition approach to study the impacts of market splitting on both the amount and the location of investments in terms of the electrolysers' capacity and operation. In addition to conducting an analysis of spatial incentives, this study considered incentives through different CO2 prices.