Building a low-carbon, climate resilient future: secure, clean and efficient energy
- Type of publication:Deliverable
- Date of publication:March 2021
- Author/s: Vassilis Stavrakas,Andrzej Ceglarz, Nikos Kleanthis, George Giannakidis, Amanda Schibline, Diana Süsser, Johan Lilliestam, Alexandra Psyrri, Alexandros Flamos
- Related Project:SENTINEL - Sustainable Energy Transitions Laboratory
While energy system models are important tools supporting decision- and policymakers, they are often monolithic, and, therefore, not particularly versatile and not able to address all types of problems related to the energy transition. Although models have become more complex, it does not necessarily mean that they are better suited to answer the questions asked, and address the challenges faced by decision- and policymakers. To overcome the challenges and limitations of current modelling approaches within the SENTINEL project, we will apply and validate different updated models of the SENTINEL modelling suite in three case studies of different spatial scale.
In this deliverable, we aim to (i). identify and specify policy-relevant scenarios, along with the respective energy targets, and qualitative narratives to base modelling simulations on, and (ii). identify contextual critical issues and challenges in energy system planning, and specific research questions, to which the SENTINEL models will attempt to provide answers, accounting for particularities of diverse spatial scales. The main research questions of our work are: “What scenarios should we apply in each of the SENTINEL case studies?” and “What are the main challenges and research questions by decision- and policymakers that the SENTINEL models should be able to answer?”
The specifications for scenarios, narratives, and the extended list of research questions of this deliverable will inform further work within the SENTINEL project. More specifically, SENTINEL modellers will set up their models by using the scenarios and assumptions for the three case studies and will conduct model-based analysis attempting to provide answers to the comprehensive list of research questions identified in this report.