National Energy System Modelling for Supporting Energy and Climate Policy Decision-making : The Case of Sweden

Energy system models can contribute in evaluating impacts of energy and climate policies. The process of working with energy system models assists the understanding of the quantita¬tive relationships between different parts of the energy system and between different time periods, under various assumptions. With the aim of improving the ability of national energy system models to provide robust and transparent input to the decision-making process, a three-step energy modelling process is introduced based on the literature on system analysis and energy modelling. This process is then used to address five different research questions, which are based on (but not identical to) six embedded papers. In the first step (step 1) the ‘real’ system is simplified and conceptualised into a model, where the main components and parameters of a problem are represented. In order to attain robust results, it is important to focus not only on what needs to be included in the model, but also on what can be left out. In order not to add noise to the analysis, there is a trade-off between what is desired and what can be included in terms of data. In the second step (step 2), all assumptions are sorted within a mathematical model and the algorithms solved. The structure of the model is found crucial for the possibility to trace the results back to the assumptions (transparency). In the last step (step 3), the model results are interpreted together with aspects not captured in the model (e.g. non-economic preferences, institutional barriers), and discussed in relation to the direct assumptions provided to the model (step 1) and to the implicit assumptions due to the choice of model (step 2). All three steps are essential in order to achieve robust and transparent policy analyses, and all three steps contribute to the learning about the ‘real’ system.The embedded papers (Paper I-VI) deal with issues of particular relevance for long-term analysis of the Swedish energy system. The results of Paper I illustrate the importance of capturing the seasonal and daily variations when representing cross-border trade of electricity in national models; a too simplified representation will make the model overestimate the need for installed power capacity in Sweden. Paper II presents a methodology for estimating the ‘useful demand’ for heating and cooling based on national statistics, which is useful as most energy system models are driven by ‘useful demand’, while national statistics are based on the measurable ‘final energy consumption’. Paper III compares the technical potential of com-bined heat and power (CHP) from different approaches and calculates the economic potential of CHP using a European energy system model (EU-TIMES). The comparison the technical potential of the different approaches reveals differences in definitions of the potential as well as in the system boundary. The resulting economic potential of CHP in year 2030 is shown to be significantly higher compared to today’s level, even though conservative assumptions regarding district heating were used. Paper IV assesses the impacts of district heating on the future Swedish energy system, first by a quantitative analysis using TIMES-Sweden and then by discussing aspects that cannot be captured by the model. Paper V compares different climate target scenarios and examines the impacts on the resulting total system cost with and without the addition of ancillary benefits of reductions in domestic air-pollution. The results reflect the fact that carbon dioxide emission reductions abroad imply a lost opportunity of achieving substantial domestic welfare gains from the reductions of regional and local environmental pollutants. Paper VI presents and discusses an iteration procedure for soft-linking a national energy system model (TIMES-Sweden) with a national CGE model (EMEC). Some aspects of the way in which we perform the soft-linking are not standard in the literature (e.g., the use of direction-specific connection points). By applying the iteration process, the resulting carbon emissions were found to be lower than when the models are used separately.Upprättat; 2015; 20150706 (kroann