1,721,047 research outputs found
Northern Lights: Four Energy Futures of the North
No full textFunder: Arctic Center of Energy (ACE);Full text license: CC BY-NC-SAEnergy Futures of Northern Swede
National Energy System Modelling for Supporting Energy and Climate Policy Decision-making: The Case of Sweden
No full textEnergy 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
National Energy System Modelling for Supporting Energy and Climate Policy Decision-making: The Case of Sweden
No full textEnergy 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
Assessing Sustainability of Regional Climate and Energy Targets at Local Level for Supporting Municipalities in Navigating the Green Transition
No full textThe European Union has implemented targets to address climate change, air pollution and increase the share of renewable energy. Local governments play a significant role in executing actions to contribute to these targets while meeting local sustainability targets. This research aims to guide the local governance by assessing the impact of implementing key energy targets from the European Union at the local level from a sustainability perspective using indicators based on sustainable development goals. An energy system optimization model is used to assess the case study of Gällivare, a municipality in Northern Sweden. The results show that localized climate and air quality targets effectively support the integration of renewable energy, improvements in energy efficiency, and reductions in final energy consumption. Air quality targets correspond carbon reduction targets and subsequently leading to the net zero emission. However, while air pollution targets help achieve 100% carbon dioxide reduction by 2050, achieving 100% reduction in air pollution requires specific air pollution targets.Godkänd;2025;Nivå 0;2025-06-19 (u2);Full text license: CC BY</p
Energisystem och klimatförändringar: Vad kan vi påverka och vad ska vi styra? Hur systemanalys kan stödja politiska beslut kring energiomställningen [Elektronisk resurs]
No full textBilaga 12: Klimatmålsanalys med TIMES-Sweden [Elektronisk resurs] : Övergripande klimatmål 2045 i kombination med sektormål 2030
No full textEnergisystem och klimatförändringar: Vad kan vi påverka och vad ska vi styra? Hur systemanalys kan stödja politiska beslut kring energiomställningen
No full textAnförande på Riksdagens forskningsdag den 8 juni 2023 med temat: Att möta komplexa utmaningar med hjälp av forskningFORMAS: Modellstöd i klimatpolitiskt beslutfattande: att hantera osäkerhet och komplexitet (019-01550)MESAM: Den svenska stadens omställning till ett hållbart energisystem – Kan modeller stötta beslutsprocessen? (46240-1)
Bilaga 12: Klimatmålsanalys med TIMES-Sweden : Övergripande klimatmål 2045 i kombination med sektormål 2030
No full textLinks between cross-border electricity trade and long-term development of the Nordic energy system
No full textModelling ambitious climate targets and long-term strategies for Sweden – Describing the main the challenges [Elektronisk resurs] : Presentation at The 5th Asian Energy Modelling Workshop Achieving a Sustainable 2050: Insights from Energy System Modelling
No full textThe aim is to share insights from modeling net zero CO2-emission pathways for Sweden from an energy system analysis approach, both with respect to results (how to get to net zero) and to modeling needs (what to include and how to link models). Sweden is a European country rich in biomass and energy intensive industries, thus rich in energy resources but also with challenging freight transports and industries to decarbonize. The model results shows that an increased use of biomass residues and waste heat significantly increase the possibility to meet the targets. TIMES-Sweden, an energy system optimization model of the comprehensive Swedish energy system, was used to explore different low carbon and net zero emission pathways until 2030 and 2045. In order to do so, the model has (and currently is) being updated to include fossil free alternatives to all energy conversion and production processes within the model. When doing so we take a process-oriented approach, thus describe important energy intensive industries (e.g. pulp & paper, iron & steel and cement) in detail. The model is driven by the demand of energy intensive products and services (e.g. heating of single-houses, production of ton steel and person-km in cars). The demand projections were determined by soft-linking TIMES-Sweden with a national CGE model, in which we relied on multiple direction-specific connection points.</p
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