Merla Kubli
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Boundary Conditions for Nuclear Viability in the Netherlands
Bridging System Optimality and Investor Bankability
The Netherlands aims for a climate-neutral energy system by 2050, targeting the deployment of up to 7 GW of new nuclear capacity to provide firm, low-carbon power alongside variable renewables. Integrating these baseload assets into a grid dominated by variable renewables creates profound physical and financial risks. Consequently, this thesis asks: what techno-economic boundary conditions are required for the economic viability of new nuclear capacity in the 2050 Dutch power system?
The research adopts a hybrid exploratory modelling methodology. First, a spatially explicit capacity expansion framework evaluates the cost-optimal configuration of the Dutch energy system and identifies local physical bottlenecks. Second, an hourly economic dispatch model evaluates the projected capacity mix incorporating the targeted 7 GW of nuclear power to determine specific wholesale revenues captured by the assets. Finally, a stochastic discounted cash flow model evaluates bankability for private investors and calculates required financial interventions.
From a central planner perspective, results demonstrate that the optimal level of unconstrained inland nuclear deployment is 10.4 GW, reducing annualised system costs by €816.7 million compared to a non-nuclear baseline. Enforcing the current political intention to locate this capacity at coastal nodes actively destroys this macroeconomic benefit, increasing total annual system costs by €250 million relative to a non-nuclear system, and resulting in a €328.7 million annual redispatch cost driven by existing grid congestion. Transitioning to the investor perspective reveals that price cannibalisation renders pure market financing unviable: whether operating as rigid baseload or flexible load-following, the assets face a net present value (NPV) deficit of approximately €14.7 billion and an expected internal rate of return (IRR) of 4.4%.
These findings demonstrate that forcing gigawatt-scale nuclear deployment into the future Dutch grid poses severe financial risks without specific interventions. To achieve economic viability, policymakers must satisfy three strict boundary conditions. First, an infrastructural boundary requires enabling alternative strategic locations to avoid congestion or executing extensive grid expansion to accommodate coastal generation. Second, a financial boundary requires state-backed financing mechanisms, specifically a regulated asset base (RAB) model paired with a two-way contract for difference (CfD), to compress the cost of capital during construction, protect against price cannibalisation, and structurally bridge the identified funding gap. Third, a project delivery boundary implies developers must adhere to rigorous construction management practices, such as strict standardisation and multi-unit deployment, to prevent severe cost overruns that historically affect Western megaprojects.
The core scientific contribution of this research lies in demonstrating the need for spatial explicitness in national energy modelling, alongside introducing a comprehensive methodological approach that integrates system-level assessments with investor-level metrics to prove the need for coordinated policy interventions aligning physical grid limits with market bankability. Future research should expand upon these findings by testing spatial configurations using detailed AC power flow models, evaluating alternative revenue streams like co-located hydrogen production, and elevating the assessment to a holistic social cost-benefit analysis that explicitly accounts for societal externalities. ...
The research adopts a hybrid exploratory modelling methodology. First, a spatially explicit capacity expansion framework evaluates the cost-optimal configuration of the Dutch energy system and identifies local physical bottlenecks. Second, an hourly economic dispatch model evaluates the projected capacity mix incorporating the targeted 7 GW of nuclear power to determine specific wholesale revenues captured by the assets. Finally, a stochastic discounted cash flow model evaluates bankability for private investors and calculates required financial interventions.
From a central planner perspective, results demonstrate that the optimal level of unconstrained inland nuclear deployment is 10.4 GW, reducing annualised system costs by €816.7 million compared to a non-nuclear baseline. Enforcing the current political intention to locate this capacity at coastal nodes actively destroys this macroeconomic benefit, increasing total annual system costs by €250 million relative to a non-nuclear system, and resulting in a €328.7 million annual redispatch cost driven by existing grid congestion. Transitioning to the investor perspective reveals that price cannibalisation renders pure market financing unviable: whether operating as rigid baseload or flexible load-following, the assets face a net present value (NPV) deficit of approximately €14.7 billion and an expected internal rate of return (IRR) of 4.4%.
These findings demonstrate that forcing gigawatt-scale nuclear deployment into the future Dutch grid poses severe financial risks without specific interventions. To achieve economic viability, policymakers must satisfy three strict boundary conditions. First, an infrastructural boundary requires enabling alternative strategic locations to avoid congestion or executing extensive grid expansion to accommodate coastal generation. Second, a financial boundary requires state-backed financing mechanisms, specifically a regulated asset base (RAB) model paired with a two-way contract for difference (CfD), to compress the cost of capital during construction, protect against price cannibalisation, and structurally bridge the identified funding gap. Third, a project delivery boundary implies developers must adhere to rigorous construction management practices, such as strict standardisation and multi-unit deployment, to prevent severe cost overruns that historically affect Western megaprojects.
The core scientific contribution of this research lies in demonstrating the need for spatial explicitness in national energy modelling, alongside introducing a comprehensive methodological approach that integrates system-level assessments with investor-level metrics to prove the need for coordinated policy interventions aligning physical grid limits with market bankability. Future research should expand upon these findings by testing spatial configurations using detailed AC power flow models, evaluating alternative revenue streams like co-located hydrogen production, and elevating the assessment to a holistic social cost-benefit analysis that explicitly accounts for societal externalities. ...
The Netherlands aims for a climate-neutral energy system by 2050, targeting the deployment of up to 7 GW of new nuclear capacity to provide firm, low-carbon power alongside variable renewables. Integrating these baseload assets into a grid dominated by variable renewables creates profound physical and financial risks. Consequently, this thesis asks: what techno-economic boundary conditions are required for the economic viability of new nuclear capacity in the 2050 Dutch power system?
The research adopts a hybrid exploratory modelling methodology. First, a spatially explicit capacity expansion framework evaluates the cost-optimal configuration of the Dutch energy system and identifies local physical bottlenecks. Second, an hourly economic dispatch model evaluates the projected capacity mix incorporating the targeted 7 GW of nuclear power to determine specific wholesale revenues captured by the assets. Finally, a stochastic discounted cash flow model evaluates bankability for private investors and calculates required financial interventions.
From a central planner perspective, results demonstrate that the optimal level of unconstrained inland nuclear deployment is 10.4 GW, reducing annualised system costs by €816.7 million compared to a non-nuclear baseline. Enforcing the current political intention to locate this capacity at coastal nodes actively destroys this macroeconomic benefit, increasing total annual system costs by €250 million relative to a non-nuclear system, and resulting in a €328.7 million annual redispatch cost driven by existing grid congestion. Transitioning to the investor perspective reveals that price cannibalisation renders pure market financing unviable: whether operating as rigid baseload or flexible load-following, the assets face a net present value (NPV) deficit of approximately €14.7 billion and an expected internal rate of return (IRR) of 4.4%.
These findings demonstrate that forcing gigawatt-scale nuclear deployment into the future Dutch grid poses severe financial risks without specific interventions. To achieve economic viability, policymakers must satisfy three strict boundary conditions. First, an infrastructural boundary requires enabling alternative strategic locations to avoid congestion or executing extensive grid expansion to accommodate coastal generation. Second, a financial boundary requires state-backed financing mechanisms, specifically a regulated asset base (RAB) model paired with a two-way contract for difference (CfD), to compress the cost of capital during construction, protect against price cannibalisation, and structurally bridge the identified funding gap. Third, a project delivery boundary implies developers must adhere to rigorous construction management practices, such as strict standardisation and multi-unit deployment, to prevent severe cost overruns that historically affect Western megaprojects.
The core scientific contribution of this research lies in demonstrating the need for spatial explicitness in national energy modelling, alongside introducing a comprehensive methodological approach that integrates system-level assessments with investor-level metrics to prove the need for coordinated policy interventions aligning physical grid limits with market bankability. Future research should expand upon these findings by testing spatial configurations using detailed AC power flow models, evaluating alternative revenue streams like co-located hydrogen production, and elevating the assessment to a holistic social cost-benefit analysis that explicitly accounts for societal externalities.
The research adopts a hybrid exploratory modelling methodology. First, a spatially explicit capacity expansion framework evaluates the cost-optimal configuration of the Dutch energy system and identifies local physical bottlenecks. Second, an hourly economic dispatch model evaluates the projected capacity mix incorporating the targeted 7 GW of nuclear power to determine specific wholesale revenues captured by the assets. Finally, a stochastic discounted cash flow model evaluates bankability for private investors and calculates required financial interventions.
From a central planner perspective, results demonstrate that the optimal level of unconstrained inland nuclear deployment is 10.4 GW, reducing annualised system costs by €816.7 million compared to a non-nuclear baseline. Enforcing the current political intention to locate this capacity at coastal nodes actively destroys this macroeconomic benefit, increasing total annual system costs by €250 million relative to a non-nuclear system, and resulting in a €328.7 million annual redispatch cost driven by existing grid congestion. Transitioning to the investor perspective reveals that price cannibalisation renders pure market financing unviable: whether operating as rigid baseload or flexible load-following, the assets face a net present value (NPV) deficit of approximately €14.7 billion and an expected internal rate of return (IRR) of 4.4%.
These findings demonstrate that forcing gigawatt-scale nuclear deployment into the future Dutch grid poses severe financial risks without specific interventions. To achieve economic viability, policymakers must satisfy three strict boundary conditions. First, an infrastructural boundary requires enabling alternative strategic locations to avoid congestion or executing extensive grid expansion to accommodate coastal generation. Second, a financial boundary requires state-backed financing mechanisms, specifically a regulated asset base (RAB) model paired with a two-way contract for difference (CfD), to compress the cost of capital during construction, protect against price cannibalisation, and structurally bridge the identified funding gap. Third, a project delivery boundary implies developers must adhere to rigorous construction management practices, such as strict standardisation and multi-unit deployment, to prevent severe cost overruns that historically affect Western megaprojects.
The core scientific contribution of this research lies in demonstrating the need for spatial explicitness in national energy modelling, alongside introducing a comprehensive methodological approach that integrates system-level assessments with investor-level metrics to prove the need for coordinated policy interventions aligning physical grid limits with market bankability. Future research should expand upon these findings by testing spatial configurations using detailed AC power flow models, evaluating alternative revenue streams like co-located hydrogen production, and elevating the assessment to a holistic social cost-benefit analysis that explicitly accounts for societal externalities.
Reducing CO2-emissions of Port of Rotterdam hinterland transport by truck
Analyzing the dynamics of adoption of technologies that reduce the carbon intensity of energy used by trucks
This study investigates the decarbonization of truck-based container transport in the Port of Rotterdam's hinterland, focusing on the adoption of three key low-carbon technologies: Battery Electric Trucks (BETs), Fuel-Cell Electric Trucks (FCETs), and e-diesel. As the largest logistics hub in Europe, the Port of Rotterdam faces increasing pressure to reduce CO₂ emissions, especially from road transport. Using a system dynamics model developed in Vensim and informed by expert interviews, the research explores technology adoption dynamics, including infrastructure availability, technology maturity, awareness, energy source supply, and lifecycle costs. The study identifies interdependent feedback loops among these factors and evaluates policy interventions that can accelerate adoption. Two key policies—stimulation of lower-emission truck adoption and collaborative BET implementation—are found to be particularly effective in initiating exponential adoption growth. Scenario analyses also highlight the importance of early and coordinated policy action. BETs emerge as the most viable near-term solution due to their faster cost reductions and existing infrastructure advantages, while FCETs remain a longer-term option for specific use cases. The findings offer actionable insights for the Port of Rotterdam Authority and policymakers, emphasizing early intervention, national coordination, and a strategic focus on BETs to achieve carbon neutrality in hinterland transport by 2050.
...
This study investigates the decarbonization of truck-based container transport in the Port of Rotterdam's hinterland, focusing on the adoption of three key low-carbon technologies: Battery Electric Trucks (BETs), Fuel-Cell Electric Trucks (FCETs), and e-diesel. As the largest logistics hub in Europe, the Port of Rotterdam faces increasing pressure to reduce CO₂ emissions, especially from road transport. Using a system dynamics model developed in Vensim and informed by expert interviews, the research explores technology adoption dynamics, including infrastructure availability, technology maturity, awareness, energy source supply, and lifecycle costs. The study identifies interdependent feedback loops among these factors and evaluates policy interventions that can accelerate adoption. Two key policies—stimulation of lower-emission truck adoption and collaborative BET implementation—are found to be particularly effective in initiating exponential adoption growth. Scenario analyses also highlight the importance of early and coordinated policy action. BETs emerge as the most viable near-term solution due to their faster cost reductions and existing infrastructure advantages, while FCETs remain a longer-term option for specific use cases. The findings offer actionable insights for the Port of Rotterdam Authority and policymakers, emphasizing early intervention, national coordination, and a strategic focus on BETs to achieve carbon neutrality in hinterland transport by 2050.
IoT-driven Digital Product Passport for EV batteries
An evaluation framework for potentials and challenges
The European Union’s transition towards a circular and sustainable economy has driven the introduction of the Digital Product Passport (DPP) as a regulatory tool to improve product transparency, lifecycle accountability, and environmental stewardship. For electric vehicle (EV) batteries, mandated under Regulation (EU) 2023/1542, the DPP consolidates critical lifecycle data—including state of charge, temperature, charge cycles, and safety incidents—into a standardized, accessible format. This enables compliance monitoring, facilitates reuse and recycling, and significantly contributes to EU sustainability goals. However, translating these regulatory requirements into functional, IoT-enabled systems is challenging due to the dynamic nature of battery data and the complexity in system design and the stakeholder perspective in the battery value chain.
This study delivers a decision-support framework to address these challenges. The framework’s two core tools—an evaluation matrix for systematic comparison of IoT architecture capabilities against DPP requirements, and a trade-off table revealing key design interdependencies—equip stakeholders with practical instruments for early-stage system planning. Validation through eleven expert interviews from academia and industry confirmed the framework’s regulatory alignment, technical soundness, and adaptability across organizational contexts. Experts highlighted the value of the trade-off table in surfacing tensions such as edge–cloud processing balance, latency constraints, and cost–complexity trade-offs, and stressed the importance of lifecycle data updates, sensing accuracy, and stakeholder-specific access control. Their feedback directly informed refinements, resulting in a more intuitive, context-aware, and versatile toolset. The refined framework can be used by OEMs, solution providers, and policymakers to design, assess, and optimize IoT-enabled DPP systems that balance compliance, performance, and operational feasibility. ...
This study delivers a decision-support framework to address these challenges. The framework’s two core tools—an evaluation matrix for systematic comparison of IoT architecture capabilities against DPP requirements, and a trade-off table revealing key design interdependencies—equip stakeholders with practical instruments for early-stage system planning. Validation through eleven expert interviews from academia and industry confirmed the framework’s regulatory alignment, technical soundness, and adaptability across organizational contexts. Experts highlighted the value of the trade-off table in surfacing tensions such as edge–cloud processing balance, latency constraints, and cost–complexity trade-offs, and stressed the importance of lifecycle data updates, sensing accuracy, and stakeholder-specific access control. Their feedback directly informed refinements, resulting in a more intuitive, context-aware, and versatile toolset. The refined framework can be used by OEMs, solution providers, and policymakers to design, assess, and optimize IoT-enabled DPP systems that balance compliance, performance, and operational feasibility. ...
The European Union’s transition towards a circular and sustainable economy has driven the introduction of the Digital Product Passport (DPP) as a regulatory tool to improve product transparency, lifecycle accountability, and environmental stewardship. For electric vehicle (EV) batteries, mandated under Regulation (EU) 2023/1542, the DPP consolidates critical lifecycle data—including state of charge, temperature, charge cycles, and safety incidents—into a standardized, accessible format. This enables compliance monitoring, facilitates reuse and recycling, and significantly contributes to EU sustainability goals. However, translating these regulatory requirements into functional, IoT-enabled systems is challenging due to the dynamic nature of battery data and the complexity in system design and the stakeholder perspective in the battery value chain.
This study delivers a decision-support framework to address these challenges. The framework’s two core tools—an evaluation matrix for systematic comparison of IoT architecture capabilities against DPP requirements, and a trade-off table revealing key design interdependencies—equip stakeholders with practical instruments for early-stage system planning. Validation through eleven expert interviews from academia and industry confirmed the framework’s regulatory alignment, technical soundness, and adaptability across organizational contexts. Experts highlighted the value of the trade-off table in surfacing tensions such as edge–cloud processing balance, latency constraints, and cost–complexity trade-offs, and stressed the importance of lifecycle data updates, sensing accuracy, and stakeholder-specific access control. Their feedback directly informed refinements, resulting in a more intuitive, context-aware, and versatile toolset. The refined framework can be used by OEMs, solution providers, and policymakers to design, assess, and optimize IoT-enabled DPP systems that balance compliance, performance, and operational feasibility.
This study delivers a decision-support framework to address these challenges. The framework’s two core tools—an evaluation matrix for systematic comparison of IoT architecture capabilities against DPP requirements, and a trade-off table revealing key design interdependencies—equip stakeholders with practical instruments for early-stage system planning. Validation through eleven expert interviews from academia and industry confirmed the framework’s regulatory alignment, technical soundness, and adaptability across organizational contexts. Experts highlighted the value of the trade-off table in surfacing tensions such as edge–cloud processing balance, latency constraints, and cost–complexity trade-offs, and stressed the importance of lifecycle data updates, sensing accuracy, and stakeholder-specific access control. Their feedback directly informed refinements, resulting in a more intuitive, context-aware, and versatile toolset. The refined framework can be used by OEMs, solution providers, and policymakers to design, assess, and optimize IoT-enabled DPP systems that balance compliance, performance, and operational feasibility.
Indonesia’s energy transition is hindered by persistent structural challenges rooted in the contractual design of Power Purchase Agreements (PPAs). These long-term contracts, often including take-or-pay clauses and capacity payments, financially bind the state-owned utility PLN to coal-fired generation. Despite official decarbonization targets, coal continues to dominate the power mix, exceeding 60%, resulting in electricity oversupply and fiscal strain. Current regulations and incentive structures remain insufficient to accelerate the coal phase-out.
This thesis investigates the systemic impact of coal PPAs on Indonesia’s decarbonization pathway, particularly in the context of early termination policies and financial instruments such as the Just Energy Transition Partnership (JETP). A System Dynamics (SD) model is developed to simulate the interplay of contractual lock-in, procurement logic, and financial levers over time. The model structure is informed by stakeholder interviews and validated through historical calibration, sensitivity testing, and scenario analysis.
Results indicate that coal dependency is structurally reinforced unless both upstream and downstream barriers are addressed. In the Base Case, installed coal capacity rises from 5.6 GW in 2015 to over 227 GW by 2060. Policy interventions such as a modest carbon price (2.02 USD/tCO₂) or targeted JETP funding alone achieve only limited reductions—capacity remains at 180 GW under Scenario E04. A complete coal phase-out by 2040 is only achieved when a strict procurement moratorium is combined with sufficient transition funding, leading to the retirement of over 70 GW of coal capacity and a 100% reduction in coal-based electricity generation compared to the base scenario.
The novelty of this study lies in its integration of contractual, institutional, and financial dynamics into a unified feedback-based simulation framework. It is the first study to quantify how coal PPAs interact with policy and finance to sustain or disrupt coal lock-in. The model explicitly captures mechanisms often overlooked in static assessments, offering policymakers a dynamic tool to explore intervention strategies and system leverage points.
While the model simplifies the technology mix to a coal–solar binary and assumes idealized funding flows, it offers valuable insights into PPAs as systemic anchors. Key limitations include the exclusion of strategic stakeholder behavior, spatial heterogeneity in grid capacity and demand, and detailed grid operational constraints. Addressing these limitations in future research could improve the realism and applicability of the model. In particular, expanding the model to incorporate energy choice heterogeneity, agent-based negotiation dynamics, and integration with power system adequacy or dispatch models would allow for a more comprehensive understanding of political feasibility, grid reliability, and transition costs.
This research contributes a transferable simulation tool and strategic policy insights for countries confronting similar PPA-induced lock-ins. It highlights the need for coordinated structural reform, regulatory realignment, and targeted finance to enable a just and timely coal transition. ...
This thesis investigates the systemic impact of coal PPAs on Indonesia’s decarbonization pathway, particularly in the context of early termination policies and financial instruments such as the Just Energy Transition Partnership (JETP). A System Dynamics (SD) model is developed to simulate the interplay of contractual lock-in, procurement logic, and financial levers over time. The model structure is informed by stakeholder interviews and validated through historical calibration, sensitivity testing, and scenario analysis.
Results indicate that coal dependency is structurally reinforced unless both upstream and downstream barriers are addressed. In the Base Case, installed coal capacity rises from 5.6 GW in 2015 to over 227 GW by 2060. Policy interventions such as a modest carbon price (2.02 USD/tCO₂) or targeted JETP funding alone achieve only limited reductions—capacity remains at 180 GW under Scenario E04. A complete coal phase-out by 2040 is only achieved when a strict procurement moratorium is combined with sufficient transition funding, leading to the retirement of over 70 GW of coal capacity and a 100% reduction in coal-based electricity generation compared to the base scenario.
The novelty of this study lies in its integration of contractual, institutional, and financial dynamics into a unified feedback-based simulation framework. It is the first study to quantify how coal PPAs interact with policy and finance to sustain or disrupt coal lock-in. The model explicitly captures mechanisms often overlooked in static assessments, offering policymakers a dynamic tool to explore intervention strategies and system leverage points.
While the model simplifies the technology mix to a coal–solar binary and assumes idealized funding flows, it offers valuable insights into PPAs as systemic anchors. Key limitations include the exclusion of strategic stakeholder behavior, spatial heterogeneity in grid capacity and demand, and detailed grid operational constraints. Addressing these limitations in future research could improve the realism and applicability of the model. In particular, expanding the model to incorporate energy choice heterogeneity, agent-based negotiation dynamics, and integration with power system adequacy or dispatch models would allow for a more comprehensive understanding of political feasibility, grid reliability, and transition costs.
This research contributes a transferable simulation tool and strategic policy insights for countries confronting similar PPA-induced lock-ins. It highlights the need for coordinated structural reform, regulatory realignment, and targeted finance to enable a just and timely coal transition. ...
Indonesia’s energy transition is hindered by persistent structural challenges rooted in the contractual design of Power Purchase Agreements (PPAs). These long-term contracts, often including take-or-pay clauses and capacity payments, financially bind the state-owned utility PLN to coal-fired generation. Despite official decarbonization targets, coal continues to dominate the power mix, exceeding 60%, resulting in electricity oversupply and fiscal strain. Current regulations and incentive structures remain insufficient to accelerate the coal phase-out.
This thesis investigates the systemic impact of coal PPAs on Indonesia’s decarbonization pathway, particularly in the context of early termination policies and financial instruments such as the Just Energy Transition Partnership (JETP). A System Dynamics (SD) model is developed to simulate the interplay of contractual lock-in, procurement logic, and financial levers over time. The model structure is informed by stakeholder interviews and validated through historical calibration, sensitivity testing, and scenario analysis.
Results indicate that coal dependency is structurally reinforced unless both upstream and downstream barriers are addressed. In the Base Case, installed coal capacity rises from 5.6 GW in 2015 to over 227 GW by 2060. Policy interventions such as a modest carbon price (2.02 USD/tCO₂) or targeted JETP funding alone achieve only limited reductions—capacity remains at 180 GW under Scenario E04. A complete coal phase-out by 2040 is only achieved when a strict procurement moratorium is combined with sufficient transition funding, leading to the retirement of over 70 GW of coal capacity and a 100% reduction in coal-based electricity generation compared to the base scenario.
The novelty of this study lies in its integration of contractual, institutional, and financial dynamics into a unified feedback-based simulation framework. It is the first study to quantify how coal PPAs interact with policy and finance to sustain or disrupt coal lock-in. The model explicitly captures mechanisms often overlooked in static assessments, offering policymakers a dynamic tool to explore intervention strategies and system leverage points.
While the model simplifies the technology mix to a coal–solar binary and assumes idealized funding flows, it offers valuable insights into PPAs as systemic anchors. Key limitations include the exclusion of strategic stakeholder behavior, spatial heterogeneity in grid capacity and demand, and detailed grid operational constraints. Addressing these limitations in future research could improve the realism and applicability of the model. In particular, expanding the model to incorporate energy choice heterogeneity, agent-based negotiation dynamics, and integration with power system adequacy or dispatch models would allow for a more comprehensive understanding of political feasibility, grid reliability, and transition costs.
This research contributes a transferable simulation tool and strategic policy insights for countries confronting similar PPA-induced lock-ins. It highlights the need for coordinated structural reform, regulatory realignment, and targeted finance to enable a just and timely coal transition.
This thesis investigates the systemic impact of coal PPAs on Indonesia’s decarbonization pathway, particularly in the context of early termination policies and financial instruments such as the Just Energy Transition Partnership (JETP). A System Dynamics (SD) model is developed to simulate the interplay of contractual lock-in, procurement logic, and financial levers over time. The model structure is informed by stakeholder interviews and validated through historical calibration, sensitivity testing, and scenario analysis.
Results indicate that coal dependency is structurally reinforced unless both upstream and downstream barriers are addressed. In the Base Case, installed coal capacity rises from 5.6 GW in 2015 to over 227 GW by 2060. Policy interventions such as a modest carbon price (2.02 USD/tCO₂) or targeted JETP funding alone achieve only limited reductions—capacity remains at 180 GW under Scenario E04. A complete coal phase-out by 2040 is only achieved when a strict procurement moratorium is combined with sufficient transition funding, leading to the retirement of over 70 GW of coal capacity and a 100% reduction in coal-based electricity generation compared to the base scenario.
The novelty of this study lies in its integration of contractual, institutional, and financial dynamics into a unified feedback-based simulation framework. It is the first study to quantify how coal PPAs interact with policy and finance to sustain or disrupt coal lock-in. The model explicitly captures mechanisms often overlooked in static assessments, offering policymakers a dynamic tool to explore intervention strategies and system leverage points.
While the model simplifies the technology mix to a coal–solar binary and assumes idealized funding flows, it offers valuable insights into PPAs as systemic anchors. Key limitations include the exclusion of strategic stakeholder behavior, spatial heterogeneity in grid capacity and demand, and detailed grid operational constraints. Addressing these limitations in future research could improve the realism and applicability of the model. In particular, expanding the model to incorporate energy choice heterogeneity, agent-based negotiation dynamics, and integration with power system adequacy or dispatch models would allow for a more comprehensive understanding of political feasibility, grid reliability, and transition costs.
This research contributes a transferable simulation tool and strategic policy insights for countries confronting similar PPA-induced lock-ins. It highlights the need for coordinated structural reform, regulatory realignment, and targeted finance to enable a just and timely coal transition.
The production of carbon dioxide (CO2) is the largest contributor to global warming. The primary source of these emissions is petroleum-derived fuel used in transportation, specifically in internal combustion engine vehicles. In response, the European Union (EU) has implemented a low-emission mobility strategy, aiming to shift towards low-carbon transportation. This strategy includes ambitious targets for electric vehicle (EV) adoption with at least 30 million zero-emission vehicles expected to be on European roads by 2030. This push towards EVs is driving up demand for lithium-ion batteries (LIBs).
While efforts to improve efficiency in EV battery production and use are intended to reduce environmental impacts, they might potentially lead to unintended consequences known as rebound effects. Rebound effects occur when efficiency improvements result in increased consumption or production elsewhere in the system, negating the expected benefits. These effects can arise from both behavioural and systemic responses to efficiency gains. Current discussions and policy frameworks often overlook the potential rebound effects in CE activities, particularly concerning EV batteries. This oversight poses a significant risk to the effectiveness of initiatives aimed at reducing CO2 emissions and advancing CE practices. Therefore, it is crucial to investigate these rebound effects within the CE context for EV batteries to develop effective mitigation strategies.
There is a noticeable gap in the existing literature regarding the interconnected dynamics of CE practices and rebound effects in the context of EV batteries. While some studies have explored rebound effects in other sectors, limited research examines how CE practices for EV batteries contribute to rebound effects across different lifecycle stages. To ensure the sustainability of CE initiatives, it is essential to adopt a systemic view that considers these effects. By doing so, businesses can develop strategies that not only focus on recycling and efficiency but also address broader systemic impacts, ensuring that increased demand does not negate the benefits of circular practices.
The research employs qualitative SD to examine potential rebound effects in the CE system for EV batteries. This approach allows for a comprehensive understanding of the system's dynamics by identifying causal relationships between physical and behavioural components. The study uses CLDs to represent the interconnections and feedback processes within the circular economy of EV batteries, helping to identify reinforcing and balancing feedback loops that drive system behaviour. The initial phase involves identifying key variables that influence the system's behaviour. These variables include economic incentives, technological advancements, regulatory frameworks, consumer behaviour, and environmental impacts. The relationships between these variables are mapped to create CLDs, which are then iteratively refined based on expert feedback to ensure accuracy and relevance.
Expert interviews are conducted to validate and refine the constructed CLDs. Professionals with in-depth knowledge of the circular economy and EV batteries provide insights that help verify the model's assumptions, structure, and behaviour. This validation process includes discussions on potential oversights or nuances that the initial model may not fully capture. The methodology also involves developing Circular Business Models (CBMs) as strategies to mitigate rebound effects. A review of existing business model innovations in the CE context is conducted to identify patterns relevant to EV batteries. These business model patterns are categorized to align with the rebound mechanism categories, facilitating a cohesive analysis.
The study identifies key mechanisms within the EV battery lifecycle that can lead to rebound effects, particularly during the usage phase. Three significant mechanisms—Income, Substitution, and Demand Adjustment by Efficiency—were found to be most prominent in this phase. To mitigate these effects, the research proposes various strategies. Dynamic Pricing emerges as the most effective strategy, capable of addressing all three mechanisms by adjusting prices in response to real-time market conditions, thereby preventing excessive consumption and production. Alternative strategies such as Pay per Use and Subscription models also show promise in mitigating rebound effects by promoting efficient use and reducing the need for outright ownership.
The research highlights the importance of understanding these mechanisms and selecting suitable strategies to mitigate rebound effects. Firms must focus on the identified mechanisms and integrate appropriate strategies into their business models to ensure sustainable practices. Furthermore, the study underscores the necessity of engaging a diverse range of stakeholders, including consumers, policymakers, and industry practitioners, to develop comprehensive and inclusive CE strategies. Future research should continue to refine these strategies and explore the dynamic interactions within the EV battery lifecycle to enhance the effectiveness of CE initiatives. ...
While efforts to improve efficiency in EV battery production and use are intended to reduce environmental impacts, they might potentially lead to unintended consequences known as rebound effects. Rebound effects occur when efficiency improvements result in increased consumption or production elsewhere in the system, negating the expected benefits. These effects can arise from both behavioural and systemic responses to efficiency gains. Current discussions and policy frameworks often overlook the potential rebound effects in CE activities, particularly concerning EV batteries. This oversight poses a significant risk to the effectiveness of initiatives aimed at reducing CO2 emissions and advancing CE practices. Therefore, it is crucial to investigate these rebound effects within the CE context for EV batteries to develop effective mitigation strategies.
There is a noticeable gap in the existing literature regarding the interconnected dynamics of CE practices and rebound effects in the context of EV batteries. While some studies have explored rebound effects in other sectors, limited research examines how CE practices for EV batteries contribute to rebound effects across different lifecycle stages. To ensure the sustainability of CE initiatives, it is essential to adopt a systemic view that considers these effects. By doing so, businesses can develop strategies that not only focus on recycling and efficiency but also address broader systemic impacts, ensuring that increased demand does not negate the benefits of circular practices.
The research employs qualitative SD to examine potential rebound effects in the CE system for EV batteries. This approach allows for a comprehensive understanding of the system's dynamics by identifying causal relationships between physical and behavioural components. The study uses CLDs to represent the interconnections and feedback processes within the circular economy of EV batteries, helping to identify reinforcing and balancing feedback loops that drive system behaviour. The initial phase involves identifying key variables that influence the system's behaviour. These variables include economic incentives, technological advancements, regulatory frameworks, consumer behaviour, and environmental impacts. The relationships between these variables are mapped to create CLDs, which are then iteratively refined based on expert feedback to ensure accuracy and relevance.
Expert interviews are conducted to validate and refine the constructed CLDs. Professionals with in-depth knowledge of the circular economy and EV batteries provide insights that help verify the model's assumptions, structure, and behaviour. This validation process includes discussions on potential oversights or nuances that the initial model may not fully capture. The methodology also involves developing Circular Business Models (CBMs) as strategies to mitigate rebound effects. A review of existing business model innovations in the CE context is conducted to identify patterns relevant to EV batteries. These business model patterns are categorized to align with the rebound mechanism categories, facilitating a cohesive analysis.
The study identifies key mechanisms within the EV battery lifecycle that can lead to rebound effects, particularly during the usage phase. Three significant mechanisms—Income, Substitution, and Demand Adjustment by Efficiency—were found to be most prominent in this phase. To mitigate these effects, the research proposes various strategies. Dynamic Pricing emerges as the most effective strategy, capable of addressing all three mechanisms by adjusting prices in response to real-time market conditions, thereby preventing excessive consumption and production. Alternative strategies such as Pay per Use and Subscription models also show promise in mitigating rebound effects by promoting efficient use and reducing the need for outright ownership.
The research highlights the importance of understanding these mechanisms and selecting suitable strategies to mitigate rebound effects. Firms must focus on the identified mechanisms and integrate appropriate strategies into their business models to ensure sustainable practices. Furthermore, the study underscores the necessity of engaging a diverse range of stakeholders, including consumers, policymakers, and industry practitioners, to develop comprehensive and inclusive CE strategies. Future research should continue to refine these strategies and explore the dynamic interactions within the EV battery lifecycle to enhance the effectiveness of CE initiatives. ...
The production of carbon dioxide (CO2) is the largest contributor to global warming. The primary source of these emissions is petroleum-derived fuel used in transportation, specifically in internal combustion engine vehicles. In response, the European Union (EU) has implemented a low-emission mobility strategy, aiming to shift towards low-carbon transportation. This strategy includes ambitious targets for electric vehicle (EV) adoption with at least 30 million zero-emission vehicles expected to be on European roads by 2030. This push towards EVs is driving up demand for lithium-ion batteries (LIBs).
While efforts to improve efficiency in EV battery production and use are intended to reduce environmental impacts, they might potentially lead to unintended consequences known as rebound effects. Rebound effects occur when efficiency improvements result in increased consumption or production elsewhere in the system, negating the expected benefits. These effects can arise from both behavioural and systemic responses to efficiency gains. Current discussions and policy frameworks often overlook the potential rebound effects in CE activities, particularly concerning EV batteries. This oversight poses a significant risk to the effectiveness of initiatives aimed at reducing CO2 emissions and advancing CE practices. Therefore, it is crucial to investigate these rebound effects within the CE context for EV batteries to develop effective mitigation strategies.
There is a noticeable gap in the existing literature regarding the interconnected dynamics of CE practices and rebound effects in the context of EV batteries. While some studies have explored rebound effects in other sectors, limited research examines how CE practices for EV batteries contribute to rebound effects across different lifecycle stages. To ensure the sustainability of CE initiatives, it is essential to adopt a systemic view that considers these effects. By doing so, businesses can develop strategies that not only focus on recycling and efficiency but also address broader systemic impacts, ensuring that increased demand does not negate the benefits of circular practices.
The research employs qualitative SD to examine potential rebound effects in the CE system for EV batteries. This approach allows for a comprehensive understanding of the system's dynamics by identifying causal relationships between physical and behavioural components. The study uses CLDs to represent the interconnections and feedback processes within the circular economy of EV batteries, helping to identify reinforcing and balancing feedback loops that drive system behaviour. The initial phase involves identifying key variables that influence the system's behaviour. These variables include economic incentives, technological advancements, regulatory frameworks, consumer behaviour, and environmental impacts. The relationships between these variables are mapped to create CLDs, which are then iteratively refined based on expert feedback to ensure accuracy and relevance.
Expert interviews are conducted to validate and refine the constructed CLDs. Professionals with in-depth knowledge of the circular economy and EV batteries provide insights that help verify the model's assumptions, structure, and behaviour. This validation process includes discussions on potential oversights or nuances that the initial model may not fully capture. The methodology also involves developing Circular Business Models (CBMs) as strategies to mitigate rebound effects. A review of existing business model innovations in the CE context is conducted to identify patterns relevant to EV batteries. These business model patterns are categorized to align with the rebound mechanism categories, facilitating a cohesive analysis.
The study identifies key mechanisms within the EV battery lifecycle that can lead to rebound effects, particularly during the usage phase. Three significant mechanisms—Income, Substitution, and Demand Adjustment by Efficiency—were found to be most prominent in this phase. To mitigate these effects, the research proposes various strategies. Dynamic Pricing emerges as the most effective strategy, capable of addressing all three mechanisms by adjusting prices in response to real-time market conditions, thereby preventing excessive consumption and production. Alternative strategies such as Pay per Use and Subscription models also show promise in mitigating rebound effects by promoting efficient use and reducing the need for outright ownership.
The research highlights the importance of understanding these mechanisms and selecting suitable strategies to mitigate rebound effects. Firms must focus on the identified mechanisms and integrate appropriate strategies into their business models to ensure sustainable practices. Furthermore, the study underscores the necessity of engaging a diverse range of stakeholders, including consumers, policymakers, and industry practitioners, to develop comprehensive and inclusive CE strategies. Future research should continue to refine these strategies and explore the dynamic interactions within the EV battery lifecycle to enhance the effectiveness of CE initiatives.
While efforts to improve efficiency in EV battery production and use are intended to reduce environmental impacts, they might potentially lead to unintended consequences known as rebound effects. Rebound effects occur when efficiency improvements result in increased consumption or production elsewhere in the system, negating the expected benefits. These effects can arise from both behavioural and systemic responses to efficiency gains. Current discussions and policy frameworks often overlook the potential rebound effects in CE activities, particularly concerning EV batteries. This oversight poses a significant risk to the effectiveness of initiatives aimed at reducing CO2 emissions and advancing CE practices. Therefore, it is crucial to investigate these rebound effects within the CE context for EV batteries to develop effective mitigation strategies.
There is a noticeable gap in the existing literature regarding the interconnected dynamics of CE practices and rebound effects in the context of EV batteries. While some studies have explored rebound effects in other sectors, limited research examines how CE practices for EV batteries contribute to rebound effects across different lifecycle stages. To ensure the sustainability of CE initiatives, it is essential to adopt a systemic view that considers these effects. By doing so, businesses can develop strategies that not only focus on recycling and efficiency but also address broader systemic impacts, ensuring that increased demand does not negate the benefits of circular practices.
The research employs qualitative SD to examine potential rebound effects in the CE system for EV batteries. This approach allows for a comprehensive understanding of the system's dynamics by identifying causal relationships between physical and behavioural components. The study uses CLDs to represent the interconnections and feedback processes within the circular economy of EV batteries, helping to identify reinforcing and balancing feedback loops that drive system behaviour. The initial phase involves identifying key variables that influence the system's behaviour. These variables include economic incentives, technological advancements, regulatory frameworks, consumer behaviour, and environmental impacts. The relationships between these variables are mapped to create CLDs, which are then iteratively refined based on expert feedback to ensure accuracy and relevance.
Expert interviews are conducted to validate and refine the constructed CLDs. Professionals with in-depth knowledge of the circular economy and EV batteries provide insights that help verify the model's assumptions, structure, and behaviour. This validation process includes discussions on potential oversights or nuances that the initial model may not fully capture. The methodology also involves developing Circular Business Models (CBMs) as strategies to mitigate rebound effects. A review of existing business model innovations in the CE context is conducted to identify patterns relevant to EV batteries. These business model patterns are categorized to align with the rebound mechanism categories, facilitating a cohesive analysis.
The study identifies key mechanisms within the EV battery lifecycle that can lead to rebound effects, particularly during the usage phase. Three significant mechanisms—Income, Substitution, and Demand Adjustment by Efficiency—were found to be most prominent in this phase. To mitigate these effects, the research proposes various strategies. Dynamic Pricing emerges as the most effective strategy, capable of addressing all three mechanisms by adjusting prices in response to real-time market conditions, thereby preventing excessive consumption and production. Alternative strategies such as Pay per Use and Subscription models also show promise in mitigating rebound effects by promoting efficient use and reducing the need for outright ownership.
The research highlights the importance of understanding these mechanisms and selecting suitable strategies to mitigate rebound effects. Firms must focus on the identified mechanisms and integrate appropriate strategies into their business models to ensure sustainable practices. Furthermore, the study underscores the necessity of engaging a diverse range of stakeholders, including consumers, policymakers, and industry practitioners, to develop comprehensive and inclusive CE strategies. Future research should continue to refine these strategies and explore the dynamic interactions within the EV battery lifecycle to enhance the effectiveness of CE initiatives.
Master thesis
(2024)
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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.