Potential-risk and no-regret options for urban energy system design — A sensitivity analysis

  • This study identifies supply options for sustainable urban energy systems, which are robust to external system changes. A multi-criteria optimization model is used to minimize greenhouse gas (GHG) emissions and financial costs of a reference system. Sensitivity analyses examine the impact of changing boundary conditions related to GHG emissions, energy prices, energy demands, and population density. Options that align with both financial and emission reduction and are robust to system changes are called “no-regret” options. Options sensitive to system changes are labeled as “potential-risk” options. There is a conflict between minimizing GHG emissions and financial costs. In the reference case, the emission-optimized scenario enables a reduction of GHG emissions (-93%), but involves higher costs (+160%) compared to the financially-optimized scenario. No-regret options include photovoltaic systems, decentralized heat pumps, thermal storages, electricity exchange between sub-systems and with higher-level systems, and reducing energy demands through building insulation, behavioral changes, or the decrease of living space per inhabitant. Potential-risk options include solar thermal systems, natural gas technologies, high-capacity battery storages, and hydrogen for building energy supply. When energy prices rise, financially-optimized systems approach the least-emission system design. The maximum profitability of natural gas technologies was already reached before the 2022 European energy crisis.

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Metadaten
Author:Christian KlemmORCiD, Peter VennemannORCiD, Frauke WieseORCiD
URN:urn:nbn:de:hbz:836-opus-175686
DOI:https://doi.org/10.25974/fhms-17568
DOI of first publication:https://doi/org/10.1016/j.scs.2024.105189
ISSN:2210-6707
Parent Title (English):Sustainable Cities and Society
Document Type:Article
Language:English
Date of Publication (online):2024/01/24
Year of first Publication:2024
Publishing Institution:FH Münster - University of Applied Sciences
Release Date:2024/01/24
Tag:energy system modeling; no-regret; sensitivity analysis; sustainable energy; urban energy system
Volume:102
First Page:105189
Institutes:Energie · Gebäude · Umwelt (EGU)
IEP Institut für Energie und Prozesstechnik
open_access (DINI-Set):open_access
Publication list:Vennemann, Peter
Klemm, Christian
Licence (German):License Logo Creative Commons - Namensnennung (CC BY 4.0)