Objective of the plan4res project - see www.plan4res.eu The general objective of plan4res is to fill the gaps between the increasing complexity of the future energy system planning and operational problems and the currently available system analysis tools. Enhanced end-to-end planning and operational tools dealing with technological and market uncertainty, emerging technologies and increased sector coupling of multi-energy vectors such as heat, cold and transport will be assembled in a synergistic approach to support European system planners, operators, decision makers, regulators. Objective of the case studies The modular nature of the tools allows them to be tailored to the specific needs of different nature entities and can adapt to the wished (or data imposed) granularity. This should be highlighted by a set of exemplary case studies. Each of this case studies focuses on a different viewpoint on the energy system and the methods and tools necessary to solve their use cases, questions, and challenges. Three case studies with pan-European scope will be performed to show the adequacy and relevance of the developed tools and modelling framework and its interoperability. This comprises case study specific scenarios, highlighting their individual viewpoints on the energy system. This includes case study specific model-exogenous data, geographical scope, technology assumptions and tool functionality. In this deliverable the results of case study 1 “Multimodal European energy concept for achieving COP 21 goal” are report. Summary of achievements: Within the plan4res model framework we demonstrated interaction of the MIM, DMEM and GNO models according to the proposed workflow. With the MIM model we analyzed several scenarios to achieve COP21 targets and carbon neutrality in a multimodal approach (investments and operational dispatch of > 100 technology types) showing up possible pathways for energy transition and analyzing the impacts of sector coupling and decarbonizing of the individual sectors. We disaggregated results from the MIM to high spatial resolution. Applying the DMEM model, we checked the results from the aggregated level on a high spatial resolution for market and transmission grid operation for the focus year 2040. We identified bottlenecks in the grid and adjusted the operational schedules of electricity generation units and consumers. We also identified potential locations for power-to-gas maximizing grid flexibility. We proposed a method to integrate the gas grid to the electricity grid by a physical flow-based gas network optimization (GNO) model which can be aligned with the TGO model for testing of the operational schedules derived from the DMEM. With the pan-European gas demand and supply, we checked the operational schedules of electricity and heat generation from gas fuel. We demonstrated in a proof-of-concept approach how to check potential challenges from power-to-gas generated hydrogen infeed to the gas grid, and how to check the gas network’s capability as alternative energy transport network to the electric grid. As a by-product to the GNO model, we developed an approach to set up a compressor station data set using public data and network topology limitations. Additionally, we got from this case study a manifold of results, data, and also identified topics to be discussed further in deep analyses. These results are presented in the section 3. Key message of the results from the case study is that carbon neutrality for the pan-European energy system can be reached within feasible additional costs and in time. Although, manifestation of the potential pathways depends on the policy and technological constraints. Considering sector coupling impacts and facilitating additional flexibilities provided by non-electricity sectors is essential for future decarbonization towards carbon neutrality, as well as fostering pan-European cooperation between the coupled national energy systems is, e.g., to enable European-wide distribution of electricity generated from RES with sufficient cross-border interconnection capacities and ensuring security-of-supply this way.