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Hauptverfasser: Wiest, Gabriel, Nolzen, Niklas, Baader, Florian, Bardow, André, Moret, Stefano
Format: Preprint
Veröffentlicht: 2025
Schlagworte:
Online-Zugang:https://arxiv.org/abs/2505.13277
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author Wiest, Gabriel
Nolzen, Niklas
Baader, Florian
Bardow, André
Moret, Stefano
author_facet Wiest, Gabriel
Nolzen, Niklas
Baader, Florian
Bardow, André
Moret, Stefano
contents Large uncertainties in the energy transition urge decision-makers to develop low-regret strategies, i.e., strategies that perform well regardless of how the future unfolds. To address this challenge, we introduce a decision-support framework that identifies low-regret strategies in energy system planning under uncertainty. Our framework (i) automatically identifies strategies, (ii) evaluates their performance in terms of regret, (iii) assesses the key drivers of regret, and (iv) supports the decision process with intuitive decision trees, regret curves and decision maps. We apply the framework to evaluate the optimal use of biomass in the transition to net-zero energy systems, considering all major biomass utilization options: biofuels, biomethane, chemicals, hydrogen, biochar, electricity, and heat. Producing fuels and chemicals from biomass performs best across various decision-making criteria. In contrast, the current use of biomass, mainly for low-temperature heat supply, results in high regret, making it a must-avoid in the energy transition.
format Preprint
id arxiv_https___arxiv_org_abs_2505_13277
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Low-regret Strategies for Energy Systems Planning in a Highly Uncertain Future
Wiest, Gabriel
Nolzen, Niklas
Baader, Florian
Bardow, André
Moret, Stefano
Systems and Control
Large uncertainties in the energy transition urge decision-makers to develop low-regret strategies, i.e., strategies that perform well regardless of how the future unfolds. To address this challenge, we introduce a decision-support framework that identifies low-regret strategies in energy system planning under uncertainty. Our framework (i) automatically identifies strategies, (ii) evaluates their performance in terms of regret, (iii) assesses the key drivers of regret, and (iv) supports the decision process with intuitive decision trees, regret curves and decision maps. We apply the framework to evaluate the optimal use of biomass in the transition to net-zero energy systems, considering all major biomass utilization options: biofuels, biomethane, chemicals, hydrogen, biochar, electricity, and heat. Producing fuels and chemicals from biomass performs best across various decision-making criteria. In contrast, the current use of biomass, mainly for low-temperature heat supply, results in high regret, making it a must-avoid in the energy transition.
title Low-regret Strategies for Energy Systems Planning in a Highly Uncertain Future
topic Systems and Control
url https://arxiv.org/abs/2505.13277