Sweden has set ambitious climate targets, aiming for net-zero emissions by 2045 and negative emissions thereafter. As one of the world’s early adopters of carbon pricing and renewable energy, Sweden faces unique challenges in decarbonizing hard-to-abate sectors while maintaining its competitive industrial base and energy security.
Key challenges include phasing out remaining fossil fuel use in industry and transport, integrating variable renewables at scale, and balancing electrification with sustainable bioenergy use—all while preserving Sweden’s position as a clean energy leader.
Energy Modelling Lab has developed TIMES-SE, a comprehensive energy systems model for Sweden. This modeling framework captures the interactions between electricity, heating, industry, transport, and other key sectors. By analyzing different technology pathways and policy scenarios, TIMES-SE helps identify cost-effective strategies for deep decarbonization. The model enables exploration of optimal investment timing, technology choices, and sector coupling opportunities to support Sweden’s climate ambitions.
MODELLING We have built a tailored energy systems model, the TIMES-SE, using the TIMES energy systems modelling framework developed under IEA.
The model includes a full investment catalog for the entire energy sector and shows the economically optimal pathways through the jungle of technological solutions.
SCENARIO ANALYSIS Through a series of scenarios, we can investigate the consequences of different climate scenarios and consider prioritized mitigation actions.
DOCUMENTATION The model documentation can be found here soon.
The overall goal of the PtX Infrastructure project is to evaluate Danish investment options for hydrogen and CO2 infrastructure. The results should support Danish green fuel production in the context of an integrated, sector-coupled European energy system.
The project is a research project carried out by eight partners. EML contributes to the project with our advanced energy systems modelling expertise. We will use the energy systems model TIMES-NEU to generate scenarios for detailed analyses.
The expected results are forecasts and estimates of the following:
Hydrogen demand evolution in each region, including hydrogen as a feedstock for e-fuels production (e-methanol, ammonia).
Size of Danish H2 export market and potential countries to export to.
Electricity demand in Denmark, Sweden, Norway, Germany, and Poland at sector level.
CO2 trajectory for Power and Heat sector.
CO2 use and storage.
Identified research gaps
Currently, the number of analyses of feasible CO2 infrastructures and H2 and CO2 storage is limited. Furthermore, the partners in the project are addressing another three research gaps that have been identified:
Silo thinking when optimising energy infrastructures.
National foci when developing PtX plans.
Poor representation of uncertainty and robustness in investment planning.
To bridge the gaps, the project partners will apply and further develop three state-of-the-art energy system models to encompass a holistic energy system perspective. The three models in question are Balmorel, PyPSA-Eur-Sec, and TIMES.
The partners design common scenarios and explore the results to understand differences, enhancing the robustness of the results. An essential part of the project is carrying out a detailed uncertainty analysis.
Advantages of the TIMES-NEU model
When using the TIMES-NEU model, the Danish energy system is analysed within the framework of the European energy system.
The TIMES-NEU model represents the entire energy system of Norway (NO), Denmark (DK), Sweden (SE), Germany (DE), and Poland (PL), covering all sectors to assess future hydrogen and electrofuel demand. Furthermore, it has data on the Netherlands, Belgium, and the UK.
It includes key hydrogen and CO₂ infrastructure and detailed sectoral modelling for aviation and shipping, incorporating technology developments for electro fuel adoption. Additionally, the model provides an in-depth analysis of iron, steel, and other industries, evaluating the competition between hydrogen and electrification pathways.
With 56 time slices per year, the model captures seasonal and intra-annual variations, while global market trade with 40 energy carriers ensures a comprehensive representation of international energy flows.
EML developed the TIMES-NEU model in 2022 using the TIMES energy systems modelling framework. TIMES is internationally recognized and developed under the Energy Technology Systems Analysis Program (ETSAP).
MissionGreenFuels partnership
The PtX Infrastructure project is implemented under the aegis of the MissionGreenFuels partnership, which is one of the four Innomissions launched by the Danish Innovation Fund. Innomission is funded by a 700 million DKK grant from the Danish government and funds from the NextGenerationEU program. The second phase of the project started in 2025.
The American company Brightcore Energy has assigned EML to build a tailored energy systems model, the TIMES-Arlington model. The company can use the model to make recommendations for investments in new technologies regarding renewing and optimizing energy supply.
The model represents a school’s heating and cooling systems and an adjacent neighborhood in Arlington, Massachusetts. At the outset, the systems are supplied by only natural gas (main source) and some electricity. The buildings have individual AC units.
EML has considered local resources such as river and sewage water. In numerous scenarios, we have tested production, storage, and grid capacities, and space heat, space cooling, and hot water production in different combinations of technologies.
Our initial analysis has shown that a mix of geothermal and air-source pumps is the most feasible and lowest-cost solution for a future system.
Total discounted costs of systems
The analysis included the costs of grid expansion and the building of new pipes. Furthermore, we tested the optimal percentage of residential houses to be connected to the different kinds of pumps. We could demonstrate significant differences in total discounted costs of systems between tested mixes.
In addition to total system costs for different technology mixes, our analysis included CapEx breakdowns and estimates of primary energy supply and final energy consumption.
The TIMES-Arlington model is set to optimize the system for the milestone years 2024, 2030, 2040, and 2050.
Load profiles and accurate system sizing
To ensure accurate system sizing according to the load demands and to reflect peaks, we selected eight representative weeks based on load profiles. Each selected week captures the load behavior of a specific season. The resulting time series distinguishes between weekdays and non-weekdays and represents 24 hours per day. This method also minimizes computational time.
MODELLING
The TIMES-Arlington model is developed using the TIMES energy systems modelling framework. It represents a school’s heating and cooling systems and an adjacent neighbourhood in Arlington, US.
SCENARIOS
We have tested production, storage, and grid capacities, and space heat, space cooling, and hot water production in scenarios with different combinations of technologies.
REPORT
In addition to total discounted system costs of different technology mixes, our analysis included CapEx breakdowns and estimates of primary energy supply and final energy consumption.
Trollhättan Energi is developing district heating in Trollhättan and has assigned EML to develop a customized energy systems model, the TIMES-TE model. The model is used as a tool to analyze existing district heating operations, explore options for new technologies, and identify cost-optimal solutions.
Consequently, EML has generated about 30 scenarios, allowing for an in-depth analysis and testing of multiple options. The model data spans the period 2027- 2040.
Among the results of the scenario analysis were recommendations for phasing out some existing plants over time, investing in heat pump technology, and not reinvesting in certain plants.
Furthermore, we estimated the payback time for recommended investments in heat pump technology.
Identifying waste heat potential
Trollhättan Energi provides heating to 18,000 homes and 300 companies in the Swedish city of Trollhättan. The Company has set a strategic aim that its energy production should be fossil-free by 2030.
The TIMES-TE model has a representation of available energy resources, including not yet exploited sources such as wastewater. Waste heat potential in Trollhättan was identified using registers of all municipal activities and mapping through GIS modelling.
The TIMES-TE model can be regularly updated and used as a tool for continuous strategic energy planning, dovetailing system developments, and financial planning.
MODELLING
EML used the TIMES energy systems modelling framework to develop a customized model of the district heating network in Trollhättan, the TIMES-TE model.
SCENARIOS
An analysis of about 30 scenarios testing different assumptions, technology options, and targets was accomplished.
REPORTING
We produced a comprehensive report of the results that supported the decision-making of the management of Trollhättan Energi.
Vinnytsia municipality has engaged in a project to develop a comprehensive district heating investment roadmap, innovating energy planning in Ukraine. As part of the project, the Energy Modelling Lab is building the TIMES-Vinnytsia energy systems model.
The model enables energy planners to identify the most cost-effective and sustainable solutions to modernize the district heating system. It covers the period 2025-2050. Subsequently, Vinnytsia’s energy planners can adopt a long-term strategic approach, allowing for informed decisions on priority investment projects.
Building the TIMES-Vinnytsia model entails mapping available local energy resources such as river water, wind, waste energy, geothermal, and solar. Furthermore, we will assess the feasibility of using these sources in the local district heating system. Likewise, we will analyze current assets to determine which ones should be replaced or retrofitted and identify opportunities for system expansion.
20-30 scenarios for modernizing the district heating system
We expect to develop and analyze 20-30 scenarios for modernizing the district heating system. The scenarios will show the impact of factors such as energy taxation policies, choice of energy resources, alignment with EU legislation (e.g., EU Taxonomy), the resilience of the energy system (technology combinations, storage solutions), the marginal cost of production, potential grid expansion, and energy efficiency investments in buildings.
The analysis of the scenarios will result in a roadmap for 2025-2050 outlining recommended investments, timing, and costs.
The TIMES-Vinnytsia will have a representation of the heat supply balance including storages and demands and showing centralized and individual options.
Vinnytsia first in Ukraine to announce the Green Deal
Vinnytsia has 370.000 inhabitants. It is located on the banks of the Southern Bug and is a prominent industrial city. Vinnytsia City Territorial Community was the first in Ukraine to announce the Green Deal following the example of the European Green Deal.
The district heating systems in Ukraine supply about 40 pct. of the residents during the heating season. The National Renewable Energy Action Plan (NREAP) has set ambitious targets to increase the share of renewable energy in heating and cooling from 20.8% to 32.5% by 2030.
MODELLING
Building the TIMES-Vinnytsia model. We use the TIMES energy systems modelling framework. It was developed as a methodology for energy scenarios to conduct in-depth energy and environmental analyses by ETSAP, a technology collaboration program under the IEA.
SCENARIO ANALYSIS
Generating and analyzing 20-30 scenarios of modernizing the Vinnytsia district heating system considering the impact on demand and production by factors such as energy taxation policies, choice of energy resources, alignment with EU taxonomy, and energy system resilience.
ROADMAP
Developing a Roadmap 2025-2050 detailing recommended priority investment projects, timeline, and costs. The Roadmap will support the energy planners of Vinnytsia Municipality in making informed choices and enable long-term strategic planning.
We have made a quantitative impact assessment related to load distribution for Varmelast. The impact assessment is part of the project Load Distribution based on Contract Prices. The aim of the project is improving the competitiveness of district heating.
Varmelast handles load dispatching of heat production in the greater Copenhagen area. Varmelast is organized as a cooperation between the three largest municipally owned heating companies in the Copenhagen metropolitan area: CTR, VEKS, and HOFOR.
Varmelast has published the EML report on Varmelast.dk.
One fundamental way of improving the competitiveness of district heating is to reform the load distribution system to ensure the lowest possible heating prices. Our analysis focused on the pricing of load distribution, comparing the advantages of different pricing systems.
Comparing load distribution systems
We based the assessment on the model TIMES-Varmelast. TIMES-Varmelast is an optimization model we built and tailored based on the internationally recognized TIMES modelling framework.
In the model, a load distribution system based on the contract prices is tested and compared with the existing system load distribution system based on minimizing the total costs of running the plants (e.g., fuel costs and revenue from the sale of electricity which are not part of the heating contract).
The analysis examines the total variable heat payment in 2030 under the two load distribution systems. The purpose was to contribute to understanding how changes in load distribution, and design of future contracts can affect the future heat price and production. Likewise, we also wished to gain insights into how electricity price assumptions and fuel price assumptions can affect future heat prices and production.
The TIMES-Varmelast model
The TIMES-Varmelast model is solved on an hourly level (8760 hours). We equipped it with a detailed representation of the greater Copenhagen district heating area. The model features 98 regions representing relevant district heating supply, transmission, and demand areas.
TIMES-Varmelast was developed from scratch within a few weeks by EML. The successful result has demonstrated the strength and flexibility of the TIMES modelling framework. Furthermore, we confirmed our ability to apply the TIMES framework quickly to any complex energy system case.
Key takeaways
Adopting the format of price-based contracts for load distribution results in substantial reductions in the costs and lower prices of district heating compared to cost-based load distribution.
Operating the format of price-based contracts for load distribution results in using the cheapest production plant at any given time.
Using the format of price-based contracts for load distribution results in considerable change in the district heating production. The impact includes decreased production from thermal plants while production from heat pumps and electric boilers increases.
The format of price-based contracts for load distribution is more robust to changes in electricity prices.
Modelling
We used the TIMES modelling framework to build the TIMES-Varmelast model for load distribution with different pricing systems, hourly time resolution, and detailed representation of the Greater Copenhagen district heating area.
Scenarios
We developed scenarios comparing price-based contracts for load distribution to the existing load distribution system (based on total costs) and ran sensitivity analyses.
We have developed an innovative model enabling the planning of an optimal energy island. The model makes it possible to generate scenarios and explore how to plan for the maximum economic returns for investors and developers. By analyzing various scenarios we can assess how differing conditions might affect the island’s operations, capacity, investment, and profitability.
Correspondingly, the model can generate scenarios showing the optimal scale of production of various e-fuels such as hydrogen, ammonia, methanol, and kerosene. Likewise, we can probe the most cost-efficient solutions for the management of electricity transmission.
The model is the result of a master’s thesis that we have supervised. It’s developed using the TIMES modelling framework and diverges from the prevalent demand-driven approach by adopting a price-driven strategy.
North Sea Energy Island
As a case study, the master’s thesis explores the strategic development and optimization of a North Sea Energy Island. The Danish government is planning for several energy islands in the North Sea. The Energy Island project directly addresses the European Union’s imperative to boost energy security and diminish its dependence on fossil fuel imports amidst evolving geopolitical and energy market dynamics.
The model employs an hourly resolution. It thus provides a detailed understanding of the island’s configuration and operations, enhancing the reliability of the results.
The developed model tool has proven reliable although some simplifications concerning the electricity market and transport operations were necessary. It can be integrated with other demand-driven studies to determine optimal operational strategies and future projections.
Results
The findings indicate that Germany and Denmark are the most viable markets for exporting the island’s electricity. However, producing hydrogen for export to the Netherlands and Belgium appears to be the most lucrative option, given the high industrial demand and pricing in these regions.
The study also notes that producing other e-fuels on the island would be economically feasible only under specific conditions with sufficiently high prices. These results suggest that the island’s most effective role may be as a hydrogen hub.
Furthermore, using an hourly resolution has proven instrumental in understanding storage operations on the island and achieving more dependable outcomes.
Modelling
We have developed a model of a North Sea energy island using the TIMES modelling framework.
Scenarios
We have generated various scenarios and assessed how differing conditions might affect the island’s operations, capacity, investment, and profitability.
Publication
The research is part of a master’s thesis at Danish Technical University.
We are hosting and supervising PhD student Daniele Mosso for one year. Daniele Mosso is doing his PhD at Politecnico di Torino. He is focusing on developing tools to modelling the water-energy-food nexus. The objective is to answer the following question: To what extent can energy be produced without significantly harming natural resources and related sectors?
Daniele Mosso spent the initial period of his PhD examining the major factors affecting the sustainability of energy systems. He concluded that land use, or the consumption of natural resources, is a major issue.
Limitations of existing models
Meanwhile, the existing Energy System Optimization Models (ESOMs) have limitations concerning sustainability and environmental aspects. The limitations can be overcome in several ways. Based on his initial research, Daniele Mosso opted to develop a tool to represent the sectors of agriculture, forestry, and land use (AFOLU) in an ESOM. The tool should make it possible to account for land and water consumption and related emissions.
Subsequently, the research of Daniele Mosso is in line with a new research project Energy Modelling Lab launched recently. The aim is to develop a prototype module representing the AFOLU sector for the TIMES modelling framework. The TIMES model is an energy system optimization model.
Exploring a soft-linking methodology
Furthermore, Daniele Mosso plans to devote the last part of his PhD to exploring a soft-linking methodology. One possibility is direct coupling with an integrated assessment model (IAM) representing natural resources.
At Politecnico di Torino, Daniele Mosso is a member of the MAHTEP Group (Modeling of Advanced Heat Transfer and Energy Problems). It’s a research team established at the end of 2019.
Modelling
We will develop a prototype module representing the AFOLU sector for the TIMES modelling framework.
Scenarios
We will test scenarios of the impacts of energy consumption of the AFOLU sector.
Publication
The research is part of a PhD to be finalized in 2026.
We are contributing to a project designating low-carbon solutions for Azerbaijan. The project result should be a Roadmap recommending relevant policies and technologies. The full title is “Low-Carbon Solutions in the Electric Power Sector of Azerbaijan Technical Assistance Project”.
Azerbaijan relies heavily on oil and gas, which has brought significant economic growth over the years. Oil, gas, and related petroleum products accounted for 91 percent of Azerbaijan’s total exports in 2022 and almost 48 percent of its GDP. Likewise, in 2021, natural gas dominated the electricity generation mix (94 percent). It was followed by hydropower (4.6 percent), waste and biomass incineration (0.7 percent), and solar and wind (0.5 percent).
Meanwhile, there is a vast potential for solar and wind power that investors have already begun to develop.
TIMES-Azerbaijan
Energy Modelling Lab carries out part of the energy systems modelling work for the project. Subsequently, we are updating and tailoring the TIMES-Azerbaijan model we have developed for the EU Commission in 2021. We are using the model to create three scenarios:
A Business As Usual (BAU) scenario reflects current and planned policies concerning low carbon penetration.
One scenario assumes high economic growth and targets carbon neutrality by 2050.
One scenario assumes low economic growth and targets carbon neutrality by 2050.
Stakeholder engagement
We have also been assigned to design and take charge of stakeholder engagement, consultation, and communications. The aim is to foster an understanding of the modelling approaches. The key stakeholders should reach and maintain agreement on scenario assumptions, and we should obtain the necessary feedback. The overall objective is to ensure the full capacity of ownership of the key stakeholders. Additionally, the Roadmap should be credible, robust, and functional.
Energy Modelling Lab has been subcontracted for the project by Tetra Tech. The project is implemented within the Memorandum of Understanding between the Ministry of Energy of Azerbaijan and the European Bank for Reconstruction and Development EBRD on technical support related to the development of the electric power sector of the Republic of Azerbaijan.
Modelling
We are updating and tailoring the TIMES-Azerbaijan model using the TIMES energy systems modelling framework.
Scenarios
We are creating a business as usual (BAU) scenario and two scenarios targeting net zero for the energy sector by 2050.
Stakeholder engagement
We are taking charge of designing the consultation and communications to ensure the full ownership of key stakeholders.
We have contributed to developing scenarios for CONCITO, a major Danish green think tank. CONCITO has analyzed the scenarios in the report The Importance of Agriculture for Future Land Use (Jordbrugets Betydning for Fremtidens Arealanvendelse), published in May 2024.
The scenarios represent different visions of land use in Denmark. The scenarios consider major concerns regarding sustainability, climate neutrality, and natural resources.
Consequently, the scenarios explore the potential of a substantial increase in plant-based food production and a corresponding livestock decrease. The impact of such measures on the economy and the well-being of the Danish population has also been explored.
The set target for the scenarios is to keep contributing to global food production on the present scale. The set target amounts to producing about 22 trillion kilojoules, feeding about 22 million people by 2050.
Bio-Resources of Denmark
We used the model for Denmark’s bioresources, DK-BioRes. Energy Modelling Lab developed this model for the Danish Energy Agency in 2021. We have updated and tailored the model to meet the needs of CONCITO. The model contains data on Denmark’s bioresources, i.e., agricultural land, forests, natural areas, and aquaculture.
The model and the data sources used are available on GitHub.
Based on the input on crop distribution, livestock, land distribution, and desired applied technologies that the model receives, it can analyze how biomass flows through a network of processes. The results include the final production, land use, and greenhouse gas emissions.
Potential pathways
The model can generate scenarios showing the pathway to a specific target. For the CONCITO scenarios, the set target is that the Danish agricultural sector keeps contributing to global food production on the present scale relative to the global population growth.
The scenarios generated show which kind and quantities of crops and livestock production could meet the target. They also show the land use needed. The non-edible bi-products such as straw are also included in the calculations of final material production.
In general, the focus of CONCITO in transforming the food system is to ensure sufficient healthy food in the least space possible with the least greenhouse gas emissions and negative impact on nature, the environment, and animal welfare.
During 2024, CONCITO is running the project Rethink Denmark with a special focus on land use.
Open-access model
The DK-BioRes model was developed under the program of the Bioenergy Taskforce. The model is calibrated to use 2019 as the base year. The data used are from Statistics Denmark. For the CONCITO scenarios, data on calories for edible products have been added to the model.
The DK-BioRes is built in Excel and is an open-access and open-source model. The model and the data sources used are available on GitHub.
Energy Model Lab has also developed a new and updated version of the DK-BioRes model, tailored to meet requirements from the Climate Council. We handed the model over to the Climate Council in March 2024.
Overview of the DK-BioRes model:
Documentation report
The documentation report on the scenarios, “The Danish Bio Ressource”, is available in Danish only.
