arXiv subjects

Falko Ueckerdt

Publications and source records attributed to Falko Ueckerdt.

7 recordsLinked to original sources

arXiv2026

Planning resilient hydrogen supply chains under disruption risk

Despite growing concerns over energy security, infrastructure planning and modelling for emerging green fuel supply chains often neglect risks from supply disruptions. Using a stochastic optimisation model of EU hydrogen imports, we show that 'naive' infrastructure planning results in welfare losses of 12 % (24 billion EUR) compared to risk-aware planning that anticipates supply disruptions. Despite requiring higher upfront investments, anticipatory planning achieves welfare levels close to those of an idealised system without disruptions, but entails a markedly different infrastructure configuration. Two complementary resilience strategies emerge: diversification across import corridors and strategic over-investment. This leads to increased intra-European transport capacity, a broader set of import pipelines, and investments in costly shipping terminals for hydrogen carriers. Our results show that incorporating supply risk considerations into infrastructure planning helps prevent the structural vulnerabilities seen in fossil fuel systems when designing future hydrogen supply chains.

econ.GN↗

arXiv2025

REMIND-PyPSA-Eur: Integrating power system flexibility into sector-coupled energy transition pathways

The rapid expansion of low-cost renewable electricity combined with end-use electrification in transport, industry, and buildings offers a promising path to deep decarbonisation. However, aligning variable supply with demand requires strategies for daily and seasonal balancing. Existing models either lack the wide scope required for long-term transition pathways or the spatio-temporal detail to capture power system variability and flexibility. Here, we combine the complementary strengths of REMIND, a long-term integrated assessment model, and PyPSA-Eur, an hourly energy system model, through a bi-directional, price-based and iterative soft coupling. REMIND provides pathway variables such as sectoral electricity demand, installed capacities, and costs to PyPSA-Eur, which returns optimised operational variables such as capacity factors, storage requirements, and relative prices. After sufficient convergence, this integrated approach jointly optimises long-term investment and short-term operation. We demonstrate the coupling for two Germany-focused scenarios, with and without demand-side flexibility, reaching climate neutrality by 2045. Our results confirm that a sector-coupled energy system with nearly 100\% renewable electricity is technically possible and economically viable. Power system flexibility influences long-term pathways through price differentiation: supply-side market values vary by generation technology, while demand-side prices vary by end-use sector. Flexible electrolysers and smart-charging electric vehicles benefit from below-average prices, whereas less flexible heat pumps face almost twice the average price due to winter peak loads. Without demand-side flexibility, electricity prices increase across all end-users, though battery deployment partially compensates. Our approach therefore fully integrates power system dynamics into multi-decadal energy transition pathways.

econ.GN↗

arXiv2025

Balancing Cost Savings and Import Dependence in Germany's Industry Transformation

Greenhouse gas emissions from the steel, fertiliser and plastic industries can be mitigated by producing their precursors with green hydrogen. In Germany, green production may be economically unviable due to high energy costs. This study quantifies the 'renewables pull' of cheaper production abroad and high-lights trade-offs between cost savings and import dependence. Using a detailed European energy system model coupled to global supply curves for hydrogen and industry precursors (hot briquetted iron, ammonia and methanol), we assess five scenarios with increasing degrees of freedom with respect to imports. We find that precursor import is preferred over hydrogen import because there are significant savings in hydrogen infrastructure. Cost savings in the German industry sector from shifting precursor production to European partners compared to domestic production are at 4.1 bnEUR/a or 11.2 %. This strategy captures 47.7 % of the cost savings achievable by precursor import from non-European countries, which lowers industry costs by 8.6 bnEUR/a (23.3 %). Moving energy-intensive precursor production abroad allows Germany to save costs while still retaining a substantial share of subsequent value-creating industry. However, cost savings must be weighed against the risks of import dependence, which can be mitigated by sourcing exclusively from regional partners.

physics.soc-ph↗

arXiv2024

The green hydrogen ambition and implementation gap

Green hydrogen is critical for decarbonising hard-to-electrify sectors, but faces high costs and investment risks. Here we define and quantify the green hydrogen ambition and implementation gap, showing that meeting hydrogen expectations will remain challenging despite surging announcements of projects and subsidies. Tracking 137 projects over three years, we identify a wide 2022 implementation gap with only 2% of global capacity announcements finished on schedule. In contrast, the 2030 ambition gap towards 1.5{\deg}C scenarios is gradually closing as the announced project pipeline has nearly tripled to 441 GW within three years. However, we estimate that, without carbon pricing, realising all these projects would require global subsidies of \$1.6 trillion (\$1.2 - 2.6 trillion range), far exceeding announced subsidies. Given past and future implementation gaps, policymakers must prepare for prolonged green hydrogen scarcity. Policy support needs to secure hydrogen investments, but should focus on applications where hydrogen is indispensable.

econ.GN↗

arXiv2024

The impact of temporal hydrogen regulation on hydrogen exporters and their domestic energy transition

As global demand for green hydrogen rises, potential hydrogen exporters move into the spotlight. However, the large-scale installation of on-grid hydrogen electrolysis for export can have profound impacts on domestic energy prices and energy-related emissions. Our investigation explores the interplay of hydrogen exports, domestic energy transition and temporal hydrogen regulation, employing a sector-coupled energy model in Morocco. We find substantial co-benets of domestic climate change mitigation and hydrogen exports, whereby exports can reduce domestic electricity prices while mitigation reduces hydrogen export prices. However, increasing hydrogen exports quickly in a system that is still dominated by fossil fuels can substantially raise domestic electricity prices, if green hydrogen production is not regulated. Surprisingly, temporal matching of hydrogen production lowers domestic electricity cost by up to 31% while the effect on exporters is minimal. This policy instrument can steer the welfare (re-)distribution between hydrogen exporting firms, hydrogen importers, and domestic electricity consumers and hereby increases acceptance among actors.

physics.soc-ph↗

arXiv2023

Multi-level emission impacts of electrification and coal pathways in China's netzero transition

Decarbonizing China's energy system requires both greening the power supply and electrifying end-use sectors. However, concerns exist that electrification may increase emissions while coal power dominates. Using a global climate model, we explore electrification scenarios with varying coal phase-out timelines and assess their climate impact on China's sectors. A ten-year delay in coal phase-out could increase global peak temperature by about 0.02{\deg}C. However, on a sectoral level, there is no evidence of significant additional emissions from electrification, even with a slower coal phase-out. This challenges the sequential ``order of abatement'' view, showing electrification can start before the power sector is fully decarbonized. As long as power emission intensity drops below 150 gCO2/kWh by 2040, electrification can substantially reduce the carbon footprint of buildings, steel, and transport services, and along with energy efficiency measures, it can avoid approximately 0.035{\deg}C of additional global warming by 2060.

econ.GN↗

arXiv2022

Bidirectional coupling of a long-term integrated assessment model REMIND v3.0.0 with an hourly power sector model DIETER v1.0.2

Integrated assessment models (IAMs) are a central tool for the quantitative analysis of climate change mitigation strategies. However, due to their global, cross-sectoral and centennial scope, IAMs cannot explicitly represent the spatio-temporal detail required to properly analyze the key role of variable renewable electricity (VRE) for decarbonizing the power sector and end-use electrification. In contrast, power sector models (PSMs) incorporate high spatio-temporal resolutions, but tend to have narrower scopes and shorter time horizons. To overcome these limitations, we present a novel methodology: an iterative and fully automated soft-coupling framework that combines the strengths of a IAM and a PSM. This framework uses the market values of power generation as well as the capture prices of demand in the PSM as price signals that change the capacity and power mix of the IAM. Hence, both models make endogenous investment decisions, leading to a joint solution. We apply the method to Germany in a proof-of-concept study using the IAM REMIND and the PSM DIETER, and confirm the theoretical prediction of almost-full convergence both in terms of decision variables and (shadow) prices. At the end of the iterative process, the absolute model difference between the generation shares of any generator type for any year is <5% for a simple configuration (no storage, no flexible demand), and 6-7% for a more realistic and detailed configuration (with storage and flexible demand). For the simple configuration, we mathematically show that this coupling scheme corresponds uniquely to an iterative mapping of the Lagrangians of two power sector optimization problems of different time resolutions, which can lead to a comprehensive model convergence of both decision variables and (shadow) prices. Since our approach is based on fundamental economic principles, it is applicable also to other IAM-PSM pairs.

econ.GN↗