Categoria: Seminari e Convegni
Stato: Archiviata

EMP-E 2020: Modelling Climate Neutrality for the European Green Deal Call for paper

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The conference is organised in cooperation with the H2020 Energy Modelling Group, such as the PLANET project coordinated by Energy Department@Polito, made up of eight Horizon 2020 projects, in cooperation with the European Commission. Its purpose is to bring together scientists and policy makers working on current energy modelling and energy policy issues, looking at opportunities for and impacts of decarbonising the energy system. The EMP-E seeks to find a common understanding between scientific modellers and policy makers, with the support of European Commission representatives. To reach beyond local, national and regional policy makers, and engage with the widest possible range of stakeholders involved in the EU energy system, modelling and policy insights developed during the conference will be opened up to a peer review process and compiled into an informative report. This year’s conference offers us a unique chance to include even more stakeholders, from even further afield.
The themes covered by this year’s EMP-E include:
• Climate neutral pathways, scenarios and storylines: Lessons learned for the European Green Deal
• Socio and economic impacts of decarbonisation: How to design a transition that is socially fair and economically viable?
• Sector integration: Decarbonisation through multi-energy carrier integration
• Smart cities, smart grids and digitalisation: Modelling insights and lessons learned
• Circularity: use of raw material
• Consumer and Citizen Engagement
• Transformation of the Energy system: centralisation versus further decentralisation
• Climate neutrality: energy modelling, weather, and climate
• Uncertainty and modelling: lessons learned and uncertainty in modelling
• Energy modelling tools contributions to national energy/climate plans
• Infrastructure for integrating open-source models across spatial and sectoral scales to facilitate openness and transparency