F.D. Sanvito
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Modeling Equitable Heating Transition Pathways for Dutch Urban Neighborhoods
Incorporating energy poverty aspects in the design of integrated energy systems
The Dutch heating transition aims to accelerate the shift away from heating with natural gas toward low-carbon alternatives. Although national climate policy provides longterm emission reduction targets, heating transition pathways are often assessed using
aggregated data, which do not show distributional impacts across households. This thesis addresses this gap by examining how neighborhood-scale heating systems can be designed to achieve decarbonization goals while incorporating dimensions of energy poverty. A community-level energy system optimization model was developed using Calliope, allowing for detailed representation of household heterogeneity, technology choices, cost-sharing structures, and equity-based objective functions.
The model incorporates three aspects of energy poverty: affordability, insulation quality, and the ability to participate. Seven scenarios are evaluated, combining individual or shared investment structures, cost or equity objective functions, and the presence or absence of a CO2 constraint. Household-level heat demand, income, and housing characteristics were used as inputs, alongside technology parameters and constraints. Outputs include total household costs, installed technology capacities, emissions and energy burden.
The scenario comparison shows several findings. First, shared heating systems consistently reduce total system costs relative to individual systems while achieving identical emission levels under a CO2 constraint. These benefits are strongest for apartment households, whose smaller demands enable more efficient use of shared technologies. Second, only the lowest-cost scenario without emission constraints meets the affordability criteria of the Dutch Wgiw. While electrified heating reduces annual energy bills due to higher efficiency, the associated investments are too high to be recovered over thirty years when strict emission limits are imposed. Third, stringent emission constraints increase total system costs, up to 2.5 times higher than the gas baseline. This shows that there is a strong trade-off between large emission reduction and costs. Moderate emission reductions can achieved at lower or moderately higher costs than the baseline. Sensitivity analyses highlight that energy price variations affect costs and emissions less than proportionally, indicating that the system configurations are relatively robust. The equity-based objective functions, designed to minimize income-weighted costs, have only marginal influence on outcomes. This is because optimal configurations under cost minimization already lie close to the equity-weighted optimum, and in shared systems a significant share of the costs are allocated using fixed fractions based on demand, leaving limited flexibility for redistribution. These findings explain why no single scenario fully satisfies affordability, equity, and emission reduction goals simultaneously.
Overall, the results show that achieving both low-carbon and socially equitable heatiing outcomes requires more than optimal system design. In particular, insulation upgrades, collective investment structures, targeted subsidies for low-income households, and careful alignmentwith local grid constraints are essential for reducing energy poverty while meeting emission targets. ...
aggregated data, which do not show distributional impacts across households. This thesis addresses this gap by examining how neighborhood-scale heating systems can be designed to achieve decarbonization goals while incorporating dimensions of energy poverty. A community-level energy system optimization model was developed using Calliope, allowing for detailed representation of household heterogeneity, technology choices, cost-sharing structures, and equity-based objective functions.
The model incorporates three aspects of energy poverty: affordability, insulation quality, and the ability to participate. Seven scenarios are evaluated, combining individual or shared investment structures, cost or equity objective functions, and the presence or absence of a CO2 constraint. Household-level heat demand, income, and housing characteristics were used as inputs, alongside technology parameters and constraints. Outputs include total household costs, installed technology capacities, emissions and energy burden.
The scenario comparison shows several findings. First, shared heating systems consistently reduce total system costs relative to individual systems while achieving identical emission levels under a CO2 constraint. These benefits are strongest for apartment households, whose smaller demands enable more efficient use of shared technologies. Second, only the lowest-cost scenario without emission constraints meets the affordability criteria of the Dutch Wgiw. While electrified heating reduces annual energy bills due to higher efficiency, the associated investments are too high to be recovered over thirty years when strict emission limits are imposed. Third, stringent emission constraints increase total system costs, up to 2.5 times higher than the gas baseline. This shows that there is a strong trade-off between large emission reduction and costs. Moderate emission reductions can achieved at lower or moderately higher costs than the baseline. Sensitivity analyses highlight that energy price variations affect costs and emissions less than proportionally, indicating that the system configurations are relatively robust. The equity-based objective functions, designed to minimize income-weighted costs, have only marginal influence on outcomes. This is because optimal configurations under cost minimization already lie close to the equity-weighted optimum, and in shared systems a significant share of the costs are allocated using fixed fractions based on demand, leaving limited flexibility for redistribution. These findings explain why no single scenario fully satisfies affordability, equity, and emission reduction goals simultaneously.
Overall, the results show that achieving both low-carbon and socially equitable heatiing outcomes requires more than optimal system design. In particular, insulation upgrades, collective investment structures, targeted subsidies for low-income households, and careful alignmentwith local grid constraints are essential for reducing energy poverty while meeting emission targets. ...
The Dutch heating transition aims to accelerate the shift away from heating with natural gas toward low-carbon alternatives. Although national climate policy provides longterm emission reduction targets, heating transition pathways are often assessed using
aggregated data, which do not show distributional impacts across households. This thesis addresses this gap by examining how neighborhood-scale heating systems can be designed to achieve decarbonization goals while incorporating dimensions of energy poverty. A community-level energy system optimization model was developed using Calliope, allowing for detailed representation of household heterogeneity, technology choices, cost-sharing structures, and equity-based objective functions.
The model incorporates three aspects of energy poverty: affordability, insulation quality, and the ability to participate. Seven scenarios are evaluated, combining individual or shared investment structures, cost or equity objective functions, and the presence or absence of a CO2 constraint. Household-level heat demand, income, and housing characteristics were used as inputs, alongside technology parameters and constraints. Outputs include total household costs, installed technology capacities, emissions and energy burden.
The scenario comparison shows several findings. First, shared heating systems consistently reduce total system costs relative to individual systems while achieving identical emission levels under a CO2 constraint. These benefits are strongest for apartment households, whose smaller demands enable more efficient use of shared technologies. Second, only the lowest-cost scenario without emission constraints meets the affordability criteria of the Dutch Wgiw. While electrified heating reduces annual energy bills due to higher efficiency, the associated investments are too high to be recovered over thirty years when strict emission limits are imposed. Third, stringent emission constraints increase total system costs, up to 2.5 times higher than the gas baseline. This shows that there is a strong trade-off between large emission reduction and costs. Moderate emission reductions can achieved at lower or moderately higher costs than the baseline. Sensitivity analyses highlight that energy price variations affect costs and emissions less than proportionally, indicating that the system configurations are relatively robust. The equity-based objective functions, designed to minimize income-weighted costs, have only marginal influence on outcomes. This is because optimal configurations under cost minimization already lie close to the equity-weighted optimum, and in shared systems a significant share of the costs are allocated using fixed fractions based on demand, leaving limited flexibility for redistribution. These findings explain why no single scenario fully satisfies affordability, equity, and emission reduction goals simultaneously.
Overall, the results show that achieving both low-carbon and socially equitable heatiing outcomes requires more than optimal system design. In particular, insulation upgrades, collective investment structures, targeted subsidies for low-income households, and careful alignmentwith local grid constraints are essential for reducing energy poverty while meeting emission targets.
aggregated data, which do not show distributional impacts across households. This thesis addresses this gap by examining how neighborhood-scale heating systems can be designed to achieve decarbonization goals while incorporating dimensions of energy poverty. A community-level energy system optimization model was developed using Calliope, allowing for detailed representation of household heterogeneity, technology choices, cost-sharing structures, and equity-based objective functions.
The model incorporates three aspects of energy poverty: affordability, insulation quality, and the ability to participate. Seven scenarios are evaluated, combining individual or shared investment structures, cost or equity objective functions, and the presence or absence of a CO2 constraint. Household-level heat demand, income, and housing characteristics were used as inputs, alongside technology parameters and constraints. Outputs include total household costs, installed technology capacities, emissions and energy burden.
The scenario comparison shows several findings. First, shared heating systems consistently reduce total system costs relative to individual systems while achieving identical emission levels under a CO2 constraint. These benefits are strongest for apartment households, whose smaller demands enable more efficient use of shared technologies. Second, only the lowest-cost scenario without emission constraints meets the affordability criteria of the Dutch Wgiw. While electrified heating reduces annual energy bills due to higher efficiency, the associated investments are too high to be recovered over thirty years when strict emission limits are imposed. Third, stringent emission constraints increase total system costs, up to 2.5 times higher than the gas baseline. This shows that there is a strong trade-off between large emission reduction and costs. Moderate emission reductions can achieved at lower or moderately higher costs than the baseline. Sensitivity analyses highlight that energy price variations affect costs and emissions less than proportionally, indicating that the system configurations are relatively robust. The equity-based objective functions, designed to minimize income-weighted costs, have only marginal influence on outcomes. This is because optimal configurations under cost minimization already lie close to the equity-weighted optimum, and in shared systems a significant share of the costs are allocated using fixed fractions based on demand, leaving limited flexibility for redistribution. These findings explain why no single scenario fully satisfies affordability, equity, and emission reduction goals simultaneously.
Overall, the results show that achieving both low-carbon and socially equitable heatiing outcomes requires more than optimal system design. In particular, insulation upgrades, collective investment structures, targeted subsidies for low-income households, and careful alignmentwith local grid constraints are essential for reducing energy poverty while meeting emission targets.
The transition to de-fossilized energy systems plays a central role in achieving climate neutrality in Europe, and the transport sector is pivotal in this transformation. Nowadays, passenger vehicles represent an important share of the final energy consumption and the greenhouse gas emissions. As internal combustion engine vehicles (ICEVs) are gradually phased out and replaced by battery electric vehicles (BEVs), and hydrogen fuel cell electric vehicles (FCEVs), understanding the evolving energy demand profile of passenger transport becomes more and more critical. This thesis addresses this challenge by quantifying the way in which the differences in powertrain technologies, in the vehicle types, and in weather conditions influence the energy consumption and the total energy demand across European regions.
The core of this research is the enhancement of the Vehicle Consumption Assessment Model (VCAM), a simulation platform capable of evaluating the energy consumption of different powertrains under various environmental and operational conditions. The model was extended to include a detailed representation of FCEVs and used under dynamic weather profiles and region-specific fleet compositions. These advancements allowed the simulation of real-world driving scenarios by using both historical and projected climate data, as well as the assessment of policy pathways and fleet evolution trends through 2050.
The methodological framework followed a multi-layered approach. First, a powertrain comparison for BEVS, FCEVs, and ICEVs has been made to evaluate them across different vehicle segments, considering performance under different driving cycles. Second, a temperature sensitivity analysis has been made for forty years of temperature data for Greece, Germany, and Finland, which were used to quantify the impact of cold and hot conditions on energy consumption and range for each powertrain technology. Lastly, a scenario-based analysis has been performed to scrutinize the effects of different IEA policy pathways (STEPS, SDS, NZE) and IPCC climate scenarios (RCP 2.6, 4.5, 8.5), as well as the influence of the growing SUV market share, on the passenger vehicle energy demand in 2050.
The results show that the energy demand is highly sensitive to the selection of powertrain technology, with BEVs offering the highest efficiency, as well as the highest sensitivity to ambient temperature. The FCEVs perform more consistently across extreme temperatures, but consume more energy than BEVs. ICEVs are the least efficient vehicles, but they present a moderate sensitivity to temperature because of their capability to use the engine's waste heat to cover the thermal loads. Vehicle size can significantly alter consumption, especially for electrified vehicles in extreme climates.
Regarding the regional effects, the projections for the passenger vehicle energy demand differ substantially. Germany's demand remains the highest due to population and mobility volume, while Finland shows the greatest sensitivity to climate conditions. Greece, where the most moderate climate conditions exist, presents the lowest variability. Across all technologies, BEVs offer the highest efficiency but also the greatest vulnerability to temperature extremes, with the energy consumption rising to more than 40% in cold conditions. FCEVs, which are less efficient overall, keep a more stable performance across temperature variations. The scenario analysis made shows that the ambitious decarbonization strategies (STEPS, SDS, NZE) could reduce total passenger vehicle energy demand by more than 60% relative to 2019 levels. However, this reduction is sensitive to fleet composition. To be more specific, for example, an annual SUV market growth of 2 percent could increase energy demand by up to 19% in Germany compared to a no-growth baseline. Similarly, consumption in the coldest years can exceed the warmest by 8 - 15 % for FCEVs and BEVs, depending on the region.
In conclusion, this thesis provides a detailed and geographically differentiated understanding of the passenger vehicle energy demand during the energy transition. It underlines the need to plan, while considering climate conditions, segments, and technologies to ensure that the electrification of the transport sector aligns with the broader goals. ...
The core of this research is the enhancement of the Vehicle Consumption Assessment Model (VCAM), a simulation platform capable of evaluating the energy consumption of different powertrains under various environmental and operational conditions. The model was extended to include a detailed representation of FCEVs and used under dynamic weather profiles and region-specific fleet compositions. These advancements allowed the simulation of real-world driving scenarios by using both historical and projected climate data, as well as the assessment of policy pathways and fleet evolution trends through 2050.
The methodological framework followed a multi-layered approach. First, a powertrain comparison for BEVS, FCEVs, and ICEVs has been made to evaluate them across different vehicle segments, considering performance under different driving cycles. Second, a temperature sensitivity analysis has been made for forty years of temperature data for Greece, Germany, and Finland, which were used to quantify the impact of cold and hot conditions on energy consumption and range for each powertrain technology. Lastly, a scenario-based analysis has been performed to scrutinize the effects of different IEA policy pathways (STEPS, SDS, NZE) and IPCC climate scenarios (RCP 2.6, 4.5, 8.5), as well as the influence of the growing SUV market share, on the passenger vehicle energy demand in 2050.
The results show that the energy demand is highly sensitive to the selection of powertrain technology, with BEVs offering the highest efficiency, as well as the highest sensitivity to ambient temperature. The FCEVs perform more consistently across extreme temperatures, but consume more energy than BEVs. ICEVs are the least efficient vehicles, but they present a moderate sensitivity to temperature because of their capability to use the engine's waste heat to cover the thermal loads. Vehicle size can significantly alter consumption, especially for electrified vehicles in extreme climates.
Regarding the regional effects, the projections for the passenger vehicle energy demand differ substantially. Germany's demand remains the highest due to population and mobility volume, while Finland shows the greatest sensitivity to climate conditions. Greece, where the most moderate climate conditions exist, presents the lowest variability. Across all technologies, BEVs offer the highest efficiency but also the greatest vulnerability to temperature extremes, with the energy consumption rising to more than 40% in cold conditions. FCEVs, which are less efficient overall, keep a more stable performance across temperature variations. The scenario analysis made shows that the ambitious decarbonization strategies (STEPS, SDS, NZE) could reduce total passenger vehicle energy demand by more than 60% relative to 2019 levels. However, this reduction is sensitive to fleet composition. To be more specific, for example, an annual SUV market growth of 2 percent could increase energy demand by up to 19% in Germany compared to a no-growth baseline. Similarly, consumption in the coldest years can exceed the warmest by 8 - 15 % for FCEVs and BEVs, depending on the region.
In conclusion, this thesis provides a detailed and geographically differentiated understanding of the passenger vehicle energy demand during the energy transition. It underlines the need to plan, while considering climate conditions, segments, and technologies to ensure that the electrification of the transport sector aligns with the broader goals. ...
The transition to de-fossilized energy systems plays a central role in achieving climate neutrality in Europe, and the transport sector is pivotal in this transformation. Nowadays, passenger vehicles represent an important share of the final energy consumption and the greenhouse gas emissions. As internal combustion engine vehicles (ICEVs) are gradually phased out and replaced by battery electric vehicles (BEVs), and hydrogen fuel cell electric vehicles (FCEVs), understanding the evolving energy demand profile of passenger transport becomes more and more critical. This thesis addresses this challenge by quantifying the way in which the differences in powertrain technologies, in the vehicle types, and in weather conditions influence the energy consumption and the total energy demand across European regions.
The core of this research is the enhancement of the Vehicle Consumption Assessment Model (VCAM), a simulation platform capable of evaluating the energy consumption of different powertrains under various environmental and operational conditions. The model was extended to include a detailed representation of FCEVs and used under dynamic weather profiles and region-specific fleet compositions. These advancements allowed the simulation of real-world driving scenarios by using both historical and projected climate data, as well as the assessment of policy pathways and fleet evolution trends through 2050.
The methodological framework followed a multi-layered approach. First, a powertrain comparison for BEVS, FCEVs, and ICEVs has been made to evaluate them across different vehicle segments, considering performance under different driving cycles. Second, a temperature sensitivity analysis has been made for forty years of temperature data for Greece, Germany, and Finland, which were used to quantify the impact of cold and hot conditions on energy consumption and range for each powertrain technology. Lastly, a scenario-based analysis has been performed to scrutinize the effects of different IEA policy pathways (STEPS, SDS, NZE) and IPCC climate scenarios (RCP 2.6, 4.5, 8.5), as well as the influence of the growing SUV market share, on the passenger vehicle energy demand in 2050.
The results show that the energy demand is highly sensitive to the selection of powertrain technology, with BEVs offering the highest efficiency, as well as the highest sensitivity to ambient temperature. The FCEVs perform more consistently across extreme temperatures, but consume more energy than BEVs. ICEVs are the least efficient vehicles, but they present a moderate sensitivity to temperature because of their capability to use the engine's waste heat to cover the thermal loads. Vehicle size can significantly alter consumption, especially for electrified vehicles in extreme climates.
Regarding the regional effects, the projections for the passenger vehicle energy demand differ substantially. Germany's demand remains the highest due to population and mobility volume, while Finland shows the greatest sensitivity to climate conditions. Greece, where the most moderate climate conditions exist, presents the lowest variability. Across all technologies, BEVs offer the highest efficiency but also the greatest vulnerability to temperature extremes, with the energy consumption rising to more than 40% in cold conditions. FCEVs, which are less efficient overall, keep a more stable performance across temperature variations. The scenario analysis made shows that the ambitious decarbonization strategies (STEPS, SDS, NZE) could reduce total passenger vehicle energy demand by more than 60% relative to 2019 levels. However, this reduction is sensitive to fleet composition. To be more specific, for example, an annual SUV market growth of 2 percent could increase energy demand by up to 19% in Germany compared to a no-growth baseline. Similarly, consumption in the coldest years can exceed the warmest by 8 - 15 % for FCEVs and BEVs, depending on the region.
In conclusion, this thesis provides a detailed and geographically differentiated understanding of the passenger vehicle energy demand during the energy transition. It underlines the need to plan, while considering climate conditions, segments, and technologies to ensure that the electrification of the transport sector aligns with the broader goals.
The core of this research is the enhancement of the Vehicle Consumption Assessment Model (VCAM), a simulation platform capable of evaluating the energy consumption of different powertrains under various environmental and operational conditions. The model was extended to include a detailed representation of FCEVs and used under dynamic weather profiles and region-specific fleet compositions. These advancements allowed the simulation of real-world driving scenarios by using both historical and projected climate data, as well as the assessment of policy pathways and fleet evolution trends through 2050.
The methodological framework followed a multi-layered approach. First, a powertrain comparison for BEVS, FCEVs, and ICEVs has been made to evaluate them across different vehicle segments, considering performance under different driving cycles. Second, a temperature sensitivity analysis has been made for forty years of temperature data for Greece, Germany, and Finland, which were used to quantify the impact of cold and hot conditions on energy consumption and range for each powertrain technology. Lastly, a scenario-based analysis has been performed to scrutinize the effects of different IEA policy pathways (STEPS, SDS, NZE) and IPCC climate scenarios (RCP 2.6, 4.5, 8.5), as well as the influence of the growing SUV market share, on the passenger vehicle energy demand in 2050.
The results show that the energy demand is highly sensitive to the selection of powertrain technology, with BEVs offering the highest efficiency, as well as the highest sensitivity to ambient temperature. The FCEVs perform more consistently across extreme temperatures, but consume more energy than BEVs. ICEVs are the least efficient vehicles, but they present a moderate sensitivity to temperature because of their capability to use the engine's waste heat to cover the thermal loads. Vehicle size can significantly alter consumption, especially for electrified vehicles in extreme climates.
Regarding the regional effects, the projections for the passenger vehicle energy demand differ substantially. Germany's demand remains the highest due to population and mobility volume, while Finland shows the greatest sensitivity to climate conditions. Greece, where the most moderate climate conditions exist, presents the lowest variability. Across all technologies, BEVs offer the highest efficiency but also the greatest vulnerability to temperature extremes, with the energy consumption rising to more than 40% in cold conditions. FCEVs, which are less efficient overall, keep a more stable performance across temperature variations. The scenario analysis made shows that the ambitious decarbonization strategies (STEPS, SDS, NZE) could reduce total passenger vehicle energy demand by more than 60% relative to 2019 levels. However, this reduction is sensitive to fleet composition. To be more specific, for example, an annual SUV market growth of 2 percent could increase energy demand by up to 19% in Germany compared to a no-growth baseline. Similarly, consumption in the coldest years can exceed the warmest by 8 - 15 % for FCEVs and BEVs, depending on the region.
In conclusion, this thesis provides a detailed and geographically differentiated understanding of the passenger vehicle energy demand during the energy transition. It underlines the need to plan, while considering climate conditions, segments, and technologies to ensure that the electrification of the transport sector aligns with the broader goals.
Master thesis
(2024)
-
L. Alconchel Ibarrola, Stefan Pfenninger, F. Lombardi, F.D. Sanvito, Merla Kubli
This report focuses on raw material requirements for self-sufficient, carbon-neutral European energy systems. It addresses the need to ensure that the transition to a low-carbon economy in Europe is realistic, feasible, and sustainable. Previous studies have often overlooked the integration of material requirements in optimized designs considering a sector-coupled energy system, or have only considered a single configuration without exploring trade-offs in other equally feasible pathways.
To overcome these limitations, this report evaluates the material requirements of hundreds of radically different energy configurations that would allow Europe to become energy self-sufficient and carbon- neutral by 2050. The solutions were generated with the Euro-Calliope framework using an extension of the modeling-to-generate-alternatives approach, creating spatially explicit practically optimal results (SPORES). This approach broadens the solution space and explores energy configurations that are within 10% of the cost-optimal solution.
The results reveal that future energy configurations will be inherently material-intensive, primarily due to the large-scale deployment of power technologies and electric vehicles. In contrast, technologies such as infrastructure expansion and heating systems pose minimal challenges regarding resource consumption. The findings confirm that equally feasible energy system designs can have significantly different CRM demands, with some configurations more likely to face supply-chain bottlenecks for materials like lithium, cobalt, and nickel. Trade-offs emerge between specific CRMs and energy system options. For example, high electrification of the transport sector requires nearly double the amount of CRMs compared to configurations with greater biofuel utilization. However, reducing the number of EVs significantly limits flexibility in energy configurations, pushing Europe toward an energy system design that maximizes biofuel.
Nevertheless, this research identifies key strategies that may help mitigate CRM demand in electric vehicles. In the next 15 to 20 years, recycling could become a significant alternative to mining for meeting a substantial share of raw material needs. This report estimates that end-of-life battery recycling rates could decrease the need for newly mined materials like lithium, cobalt, and nickel by more than half. However, in the short-term, the availability of these minerals will be insufficient for recycling to become a practical solution. Furthermore, technical and economic barriers currently limit the potential of recycling and the complete shift to battery technologies that do not rely on critical raw materials. This provides actionable guidance for integrating circular economy efforts into energy policy.
Future research would benefit from adopting a more dynamic approach to better capture future material requirements. This can be done by incorporating potential improvements in material intensities, a wider range of sub-technologies, and their evolving market shares. Furthermore, exploring alternative energy configurations and examining how changes in constraints, such as self-sufficiency or moving further away from the cost-optimal solution, affect system design and material demand would be beneficial. Finally, material constraints could be included directly in energy models by limiting CRM demand, which would allow the assessment of feasible energy configurations. ...
To overcome these limitations, this report evaluates the material requirements of hundreds of radically different energy configurations that would allow Europe to become energy self-sufficient and carbon- neutral by 2050. The solutions were generated with the Euro-Calliope framework using an extension of the modeling-to-generate-alternatives approach, creating spatially explicit practically optimal results (SPORES). This approach broadens the solution space and explores energy configurations that are within 10% of the cost-optimal solution.
The results reveal that future energy configurations will be inherently material-intensive, primarily due to the large-scale deployment of power technologies and electric vehicles. In contrast, technologies such as infrastructure expansion and heating systems pose minimal challenges regarding resource consumption. The findings confirm that equally feasible energy system designs can have significantly different CRM demands, with some configurations more likely to face supply-chain bottlenecks for materials like lithium, cobalt, and nickel. Trade-offs emerge between specific CRMs and energy system options. For example, high electrification of the transport sector requires nearly double the amount of CRMs compared to configurations with greater biofuel utilization. However, reducing the number of EVs significantly limits flexibility in energy configurations, pushing Europe toward an energy system design that maximizes biofuel.
Nevertheless, this research identifies key strategies that may help mitigate CRM demand in electric vehicles. In the next 15 to 20 years, recycling could become a significant alternative to mining for meeting a substantial share of raw material needs. This report estimates that end-of-life battery recycling rates could decrease the need for newly mined materials like lithium, cobalt, and nickel by more than half. However, in the short-term, the availability of these minerals will be insufficient for recycling to become a practical solution. Furthermore, technical and economic barriers currently limit the potential of recycling and the complete shift to battery technologies that do not rely on critical raw materials. This provides actionable guidance for integrating circular economy efforts into energy policy.
Future research would benefit from adopting a more dynamic approach to better capture future material requirements. This can be done by incorporating potential improvements in material intensities, a wider range of sub-technologies, and their evolving market shares. Furthermore, exploring alternative energy configurations and examining how changes in constraints, such as self-sufficiency or moving further away from the cost-optimal solution, affect system design and material demand would be beneficial. Finally, material constraints could be included directly in energy models by limiting CRM demand, which would allow the assessment of feasible energy configurations. ...
This report focuses on raw material requirements for self-sufficient, carbon-neutral European energy systems. It addresses the need to ensure that the transition to a low-carbon economy in Europe is realistic, feasible, and sustainable. Previous studies have often overlooked the integration of material requirements in optimized designs considering a sector-coupled energy system, or have only considered a single configuration without exploring trade-offs in other equally feasible pathways.
To overcome these limitations, this report evaluates the material requirements of hundreds of radically different energy configurations that would allow Europe to become energy self-sufficient and carbon- neutral by 2050. The solutions were generated with the Euro-Calliope framework using an extension of the modeling-to-generate-alternatives approach, creating spatially explicit practically optimal results (SPORES). This approach broadens the solution space and explores energy configurations that are within 10% of the cost-optimal solution.
The results reveal that future energy configurations will be inherently material-intensive, primarily due to the large-scale deployment of power technologies and electric vehicles. In contrast, technologies such as infrastructure expansion and heating systems pose minimal challenges regarding resource consumption. The findings confirm that equally feasible energy system designs can have significantly different CRM demands, with some configurations more likely to face supply-chain bottlenecks for materials like lithium, cobalt, and nickel. Trade-offs emerge between specific CRMs and energy system options. For example, high electrification of the transport sector requires nearly double the amount of CRMs compared to configurations with greater biofuel utilization. However, reducing the number of EVs significantly limits flexibility in energy configurations, pushing Europe toward an energy system design that maximizes biofuel.
Nevertheless, this research identifies key strategies that may help mitigate CRM demand in electric vehicles. In the next 15 to 20 years, recycling could become a significant alternative to mining for meeting a substantial share of raw material needs. This report estimates that end-of-life battery recycling rates could decrease the need for newly mined materials like lithium, cobalt, and nickel by more than half. However, in the short-term, the availability of these minerals will be insufficient for recycling to become a practical solution. Furthermore, technical and economic barriers currently limit the potential of recycling and the complete shift to battery technologies that do not rely on critical raw materials. This provides actionable guidance for integrating circular economy efforts into energy policy.
Future research would benefit from adopting a more dynamic approach to better capture future material requirements. This can be done by incorporating potential improvements in material intensities, a wider range of sub-technologies, and their evolving market shares. Furthermore, exploring alternative energy configurations and examining how changes in constraints, such as self-sufficiency or moving further away from the cost-optimal solution, affect system design and material demand would be beneficial. Finally, material constraints could be included directly in energy models by limiting CRM demand, which would allow the assessment of feasible energy configurations.
To overcome these limitations, this report evaluates the material requirements of hundreds of radically different energy configurations that would allow Europe to become energy self-sufficient and carbon- neutral by 2050. The solutions were generated with the Euro-Calliope framework using an extension of the modeling-to-generate-alternatives approach, creating spatially explicit practically optimal results (SPORES). This approach broadens the solution space and explores energy configurations that are within 10% of the cost-optimal solution.
The results reveal that future energy configurations will be inherently material-intensive, primarily due to the large-scale deployment of power technologies and electric vehicles. In contrast, technologies such as infrastructure expansion and heating systems pose minimal challenges regarding resource consumption. The findings confirm that equally feasible energy system designs can have significantly different CRM demands, with some configurations more likely to face supply-chain bottlenecks for materials like lithium, cobalt, and nickel. Trade-offs emerge between specific CRMs and energy system options. For example, high electrification of the transport sector requires nearly double the amount of CRMs compared to configurations with greater biofuel utilization. However, reducing the number of EVs significantly limits flexibility in energy configurations, pushing Europe toward an energy system design that maximizes biofuel.
Nevertheless, this research identifies key strategies that may help mitigate CRM demand in electric vehicles. In the next 15 to 20 years, recycling could become a significant alternative to mining for meeting a substantial share of raw material needs. This report estimates that end-of-life battery recycling rates could decrease the need for newly mined materials like lithium, cobalt, and nickel by more than half. However, in the short-term, the availability of these minerals will be insufficient for recycling to become a practical solution. Furthermore, technical and economic barriers currently limit the potential of recycling and the complete shift to battery technologies that do not rely on critical raw materials. This provides actionable guidance for integrating circular economy efforts into energy policy.
Future research would benefit from adopting a more dynamic approach to better capture future material requirements. This can be done by incorporating potential improvements in material intensities, a wider range of sub-technologies, and their evolving market shares. Furthermore, exploring alternative energy configurations and examining how changes in constraints, such as self-sufficiency or moving further away from the cost-optimal solution, affect system design and material demand would be beneficial. Finally, material constraints could be included directly in energy models by limiting CRM demand, which would allow the assessment of feasible energy configurations.
Currently, there are optimization models that are able of modeling building renovation, but their scope is limited only to the heating system. There are also models that consider interactions between different energy subsystems, but they lack the ability to simulate building renovation. Having those two things combined would be beneficial as the impact of renovation on the power system might be significant.
The goal of this thesis is to assess the impact of building renovation on the energy system. It was done with the use of Euro-calliope model, which is capable of minimizing the cost of the whole energy system. In the current state, Euro-calliope model does not offer the chance to renovate the building stock. Therefore, the aim of this work is to introduce the building renovation option subject to the software objective function and reshape, when necessary, the heating sector.
The main outcome is that the heating sector significantly affects the distribution of power generation sources as most of heat is supplied via heat pumps. The penetration of renovation increases the fraction of energy generated by photovoltaics in the energy mix. However, when it comes to absolute values, in all scenarios wind farms are dominating.
The cost-optimal renovation always results in a higher renovation level than the currently present renovation levels. However, those levels are usually lower than the currently imposed local renovation standards. Moreover, the renovation has a positive impact on decreasing the variability of the system costs for scenarios with low renewable supply.
...
The goal of this thesis is to assess the impact of building renovation on the energy system. It was done with the use of Euro-calliope model, which is capable of minimizing the cost of the whole energy system. In the current state, Euro-calliope model does not offer the chance to renovate the building stock. Therefore, the aim of this work is to introduce the building renovation option subject to the software objective function and reshape, when necessary, the heating sector.
The main outcome is that the heating sector significantly affects the distribution of power generation sources as most of heat is supplied via heat pumps. The penetration of renovation increases the fraction of energy generated by photovoltaics in the energy mix. However, when it comes to absolute values, in all scenarios wind farms are dominating.
The cost-optimal renovation always results in a higher renovation level than the currently present renovation levels. However, those levels are usually lower than the currently imposed local renovation standards. Moreover, the renovation has a positive impact on decreasing the variability of the system costs for scenarios with low renewable supply.
...
Currently, there are optimization models that are able of modeling building renovation, but their scope is limited only to the heating system. There are also models that consider interactions between different energy subsystems, but they lack the ability to simulate building renovation. Having those two things combined would be beneficial as the impact of renovation on the power system might be significant.
The goal of this thesis is to assess the impact of building renovation on the energy system. It was done with the use of Euro-calliope model, which is capable of minimizing the cost of the whole energy system. In the current state, Euro-calliope model does not offer the chance to renovate the building stock. Therefore, the aim of this work is to introduce the building renovation option subject to the software objective function and reshape, when necessary, the heating sector.
The main outcome is that the heating sector significantly affects the distribution of power generation sources as most of heat is supplied via heat pumps. The penetration of renovation increases the fraction of energy generated by photovoltaics in the energy mix. However, when it comes to absolute values, in all scenarios wind farms are dominating.
The cost-optimal renovation always results in a higher renovation level than the currently present renovation levels. However, those levels are usually lower than the currently imposed local renovation standards. Moreover, the renovation has a positive impact on decreasing the variability of the system costs for scenarios with low renewable supply.
The goal of this thesis is to assess the impact of building renovation on the energy system. It was done with the use of Euro-calliope model, which is capable of minimizing the cost of the whole energy system. In the current state, Euro-calliope model does not offer the chance to renovate the building stock. Therefore, the aim of this work is to introduce the building renovation option subject to the software objective function and reshape, when necessary, the heating sector.
The main outcome is that the heating sector significantly affects the distribution of power generation sources as most of heat is supplied via heat pumps. The penetration of renovation increases the fraction of energy generated by photovoltaics in the energy mix. However, when it comes to absolute values, in all scenarios wind farms are dominating.
The cost-optimal renovation always results in a higher renovation level than the currently present renovation levels. However, those levels are usually lower than the currently imposed local renovation standards. Moreover, the renovation has a positive impact on decreasing the variability of the system costs for scenarios with low renewable supply.
The aim of this thesis project is to investigate how different PV-deployment strategies can help reinforce energy security and reduce GHG emissions in Ukraine. The author addresses several sub-questions related to energy security, the current status of Ukraine's electricity and heat sector, and the potentials and yields of renewable energy sources in Ukraine. To answer this question, the author uses literature review and simulations using optimization software. Three different deployment strategies are considered: utility-scale PV systems, distributed PV systems, and a combination of both. The simulations are based on hourly data for solar irradiance, temperature, wind speed, and load demand for 2018 in Ukraine. The results are evaluated based on several key performance indicators (KPIs) linked to energy security such as import dependency, diversity, as well as GHG emissions reduction potential.
The author finds that a combination of utility-scale and distributed PV systems can provide the most effective solution for reinforcing energy security while also reducing GHG emissions in Ukraine. The simulations also show that improvements in grid infrastructure is crucial for achieving these results.
Overall, the author concludes that deploying both utility-scale and distributed PV systems can provide a cost-effective way to reinforce energy security while also reducing GHG emissions in Ukraine.
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The author finds that a combination of utility-scale and distributed PV systems can provide the most effective solution for reinforcing energy security while also reducing GHG emissions in Ukraine. The simulations also show that improvements in grid infrastructure is crucial for achieving these results.
Overall, the author concludes that deploying both utility-scale and distributed PV systems can provide a cost-effective way to reinforce energy security while also reducing GHG emissions in Ukraine.
...
The aim of this thesis project is to investigate how different PV-deployment strategies can help reinforce energy security and reduce GHG emissions in Ukraine. The author addresses several sub-questions related to energy security, the current status of Ukraine's electricity and heat sector, and the potentials and yields of renewable energy sources in Ukraine. To answer this question, the author uses literature review and simulations using optimization software. Three different deployment strategies are considered: utility-scale PV systems, distributed PV systems, and a combination of both. The simulations are based on hourly data for solar irradiance, temperature, wind speed, and load demand for 2018 in Ukraine. The results are evaluated based on several key performance indicators (KPIs) linked to energy security such as import dependency, diversity, as well as GHG emissions reduction potential.
The author finds that a combination of utility-scale and distributed PV systems can provide the most effective solution for reinforcing energy security while also reducing GHG emissions in Ukraine. The simulations also show that improvements in grid infrastructure is crucial for achieving these results.
Overall, the author concludes that deploying both utility-scale and distributed PV systems can provide a cost-effective way to reinforce energy security while also reducing GHG emissions in Ukraine.
The author finds that a combination of utility-scale and distributed PV systems can provide the most effective solution for reinforcing energy security while also reducing GHG emissions in Ukraine. The simulations also show that improvements in grid infrastructure is crucial for achieving these results.
Overall, the author concludes that deploying both utility-scale and distributed PV systems can provide a cost-effective way to reinforce energy security while also reducing GHG emissions in Ukraine.