The Energy Transition requires meticulous planning, taking into consideration economic, technical, social, and resource constraints. In Europe ambitious targets have been set for system electrification, however, integrating the potential of marine renewables have not been thoroughly investigated. This study extends the framework of PyPSA-Eur into PyPSA-Eur-MREL that for the first time incorporates all marine renewables, using high resolution datasets, that uncover the potential of marine renewables. Marine renewables are modelled in terms of power estimations, deployment strategies and revised packing density, and expected benefits for 2030, and 2050 across all European Countries are quantified. Higher spatio-temporal data have an immediate impact in estimates, and reduction of energy storage by 73%. Wind energy has a reduced installation capacity by 50%, but the higher fidelity of resource matches production to demand and reduces curtailments up to 60%. System costs with high resolution data are 40% reduced to 160 billion € for a 2030 100% renewable reliant system. The benefits of having more marine renewables are not limited to cost and more efficient demand matching, reduced energy storage, but it also with the area required to decarbonise the system. The results are encouraging and outline the importance and further need for marine renewable energies.

Wave energy as a renewable resource has been shown to have immense potential. Up to date research has predominately focused on sector focused approaches, with devices being explored in small applications, or solely on their own merit. However, when discussing the integration to energy systems with high share of renewable energies, large levels of electrical interconnectivity and grid balancing infrastructure, the role of wave energy is often “lost”. This work further refines the approach of integrating wave energy in the European and UK energy system, highlighting potential future pathways to improve wave energy considerations.

This study assesses the input source of climate data for evaluation of wave energy production and economics. The comparison of ERA5 and a high-fidelity wave dataset across all Europe, the ECHOWAVE database, show a clear benefit for wave energy. When ERA5 is utilised to assess the potential of wave energy, the usefulness and integration of wave energy is not reflected in the system. This works shows that a proper representation of wave energy in terms of climate, power production methodologies and economic considerations.

This study examines the potential contribution of marine renewable generators in Greece, in order to achieve a 100% renewable energy system by 2050. Using PyPSA-Eur, a cost-optimization model of the European energy system, possible energy transition pathways are explored, across five-year intervals from 2030 to 2050. For each five-year target, a new cost assumption dataset is used, one that follows estimated cost reduction learning rates. This version of the model is called PyPSA-Eur-MREL, and is modified to include marine power generators, i.e. floating wind, wave, tidal and floating solar, but also high fidelity climate data, in the scale of 5.5 km ² for wind and 4 km ² for wave resources. Three different approaches were employed in this investigation: greenfield, generator constrained, and a high-load scenario inspired by Greece's National Energy and Climate Plan (NECP). The analysis focused on generator capacity and performance, the levels of utilization and availability of each energy carrier and the land-use impact of onshore and offshore generators. While the first two scenarios exhibit similar overall system capacities, they differ in land-use requirements, with the constrained case installing more bottom-fixed wind turbines (1.2 GW), thereby reducing land occupation. The high-load scenario introduces floating wind turbines (4.5 GW), however, the scale of onshore installations remains substantial, covering nearly one-third of Greece's total land area.