arXiv subjects

Jonas Finke

Publications and source records attributed to Jonas Finke.

3 recordsLinked to original sources

arXiv2026

Materealistic? How European energy system models exceed raw material reserves

Decarbonising energy systems reduces emissions and fossil fuel dependency, but expanding renewables increases demands for critical raw materials. Most energy system models, however, neglect material demands, putting the material feasibility of energy scenarios at question. We combine a systematic review of 59 highly decarbonised European energy system modelling studies with a quantitative ex-post assessment of material demands for 5 key technologies and 19 materials. We find that material demands exceed Europe's population-based shares of current global reserves for seven materials (Ga, In, Ir, Te; less pronounced for Ag, Se, V), in particular if multiple sectors of the energy system are considered. Competing non-energy demand further amplifies the scarcity, while technological innovation can either alleviate or intensify it. We conclude that energy efficiency, recycling, expanding reserves and technological innovation may only partly address the identified shortages and call for energy sufficiency measures to achieve sustainability in the energy-material nexus.

econ.GN↗

arXiv2026

Value-focused modelling to generate alternatives -- Coupling multi-criteria decision analysis and optimisation models to support strategic decisions

Decision support methods from operations research are widely used to support complex planning decisions. Within the energy sector, energy system models (ESMs) applying modelling to generate alternatives (MGA) generate large sets of near-optimal, different system configurations. However, they typically generate and analyse alternatives in the model variable space without ensuring stakeholder relevance. Multi-criteria decision analysis (MCDA), in contrast, provides a structured means to account for conflicting objectives and heterogeneous stakeholder interests but often relies on a limited set of pre-defined alternatives that may not appropriately represent the feasible solution space. To address these limitations, this work proposes value-focused modelling to generate alternatives (VF-MGA), a novel methodology that bidirectionally couples MGA and MCDA. Stakeholder objectives elicited within the MCDA inform the MGA-algorithm, enabling a stakeholder-orientated diversification of the alternatives, which are subsequently evaluated within the MCDA based on elicited stakeholder preferences, thereby providing a comprehensive decision basis. Applied to a case study on the decarbonised energy supply of a large university campus, involving eleven stakeholders representing diverse institutional groups, VF-MGA (i) systematically integrates stakeholder objectives into the generation of 691 alternatives reflecting stakeholder-relevant interests, (ii) enables the identification of stakeholder-relevant alternatives from this large set through MCDA-based evaluation, and (iii) provides more differentiated stakeholder preference information by evaluating a large and diverse set of alternatives, thereby revealing acceptable ranges for system options. With this, VF-MGA provides a generalisable methodology for complex planning decision integrating quantitative modelling with participatory decision analysis.

econ.GN↗

arXiv2025

Most certainly certain? The Impact of Contract for Difference Design on Renewables' Strike Prices and Electricity Market Risks

Weather, technological and regulatory uncertainties expose actors in highly renewable electricity markets to substantial price and volume risks. Two-way Contracts for Difference (CfDs) can mitigate these risks. They stipulate payments between the government and generators of renewable electricity based on the difference of a strike and a reference price, whose definition and unit of payment differ between CfD designs. We study the effect of three different CfD designs on wind power profit and consumer price volatility under the consideration of uncertain market outcomes in a highly renewable, sector-coupled electricity market. First, we analytically derive optimal strike prices under uncertainty. Second, we numerically determine optimal strike prices based on market expectations retrieved from optimising a set of 36 market scenarios in an energy system model. Third, we study the distribution of ex post market revenues, CfD payments and consumer prices across all 36 scenarios. Compared to purely market-based consumer prices and investor profits, we find all CfDs to significantly reduce volatility. For consumer prices, results show no substantial differences between CfD designs. For investor profits, we identify the highest volatility reduction under a capacity-based CfD with a reference price similar to power plants' individual market revenues. Since such a CfD design is known to diminish the effect of price signals on investment decisions, our results reveal a trade-off between incentivising system-friendliness and reducing investor risk.

econ.GN↗