Comparing open source power system models - A case study focusing on fundamental modeling parameters for the German energy transition

Ouwerkerk, Jonas van; Hainsch, Karlo; Candas, Soner; Muschner, Christoph; Buchholz, Stefanie; Günther, Stephan; Huyskens, Hendrik; Berendes, Sarah; Bußar, Christian; Tardasti, Fateme; Köckritz, Luja von; Bramstoft, Rasmus

doi:10.1016/j.rser.2022.112331

Cited by 22 publications

(10 citation statements)

References 18 publications

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“…The modeling framework has been developed extensively by an open-source community since its first release in 2001 [33]. The mathematical formulation and results have recently been compared against four other well-known open-source energy system models [34,35], with conclusions emphasizing the model's validity.…”

Section: Energy System Optimization Model: Balmorelmentioning

confidence: 99%

A unified European hydrogen infrastructure planning to support the rapid scale-up of hydrogen production

Kountouris

Bramstoft

Madsen

et al. 2023

Preprint

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Hydrogen will become a key player in the transition toward a net-zero energy system. However, a clear pathway toward a unified European hydrogen infrastructure is still under discussion. We explore plausible pathways using a fully sector-coupled energy system model and assess the emergence of hydrogen infrastructure build-outs connecting third-nation hydrogen import and domestic production centers with Western and Central European demands via four distinct hydrogen corridors. We identify a potential lock-in effect of blue hydrogen in the medium term, highlighting the risk of long-term dependence on methane. In contrast, we show that a self-sufficient Europe relying on domestic green hydrogen by 2050 increases yearly expense by around 3 % and requires 500 GW of electrolysis. This study emphasizes the importance of a rapid scale-up of electrolysis capacity, build-out of hydrogen network and storage facilities, deployment of renewable electricity generation, and coherent coordination across European nations.

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Section: Energy System Optimization Model: Balmorelmentioning

confidence: 99%

A unified European hydrogen infrastructure planning to support the rapid scale-up of hydrogen production

Kountouris

Bramstoft

Madsen

et al. 2023

Preprint

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“…The category b) direct comparison is characterized by the simple comparison of indicators or outputs of the modeling process. Some examples for the sub-category ii) "costs" are the total system costs [22,24], the variable operational costs [25],…”

Section: Acronymsmentioning

confidence: 99%

“…Some examples for the sub-category vi) "installed capacities of storages and transmission units" are storage capacity [31], storage expansion capacity and transmission grid expansion capacity [26]. Some examples for the sub-category vii) "curtailments and excess energy" are annual VRE curtailment [32], curtailment [24] and critical excess electricity production [33]. Some examples for the sub-category viii) "hourly generation and storage profiles" are the hourly mean of discharge and charge flows [30], hourly energy balances of the week with the highest residual load [30], hourly electricity generation and demand response load reduction [32].…”

Section: Comparison Of Frameworkmentioning

confidence: 99%

“…They also calculate the deviance on the power generation between the case with and without storage to evaluate the role of energy storage in the integration of renewable energy. Ouwerkerk et al [24] compare five open source power system frameworks (Balmorel [66], GENESYS-2 [67], GENeSYS-MOD [58], oemof [43,44], and urbs [65]) with a quantitative approach based on direct comparison of the following indicators: system costs, generation and demand, installed capacities of generation sources, storage and transmission units, curtailments and excess energy and CO2 emissions.…”

Section: Comparison Of Frameworkmentioning

confidence: 99%

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Comparison methods of energy system frameworks, models and scenario results

Prina

Nastasi

Groppi

et al. 2022

Renewable and Sustainable Energy Reviews

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“…Energy system modeling tools with similar purposes often yield different results [20]. In order to identify these deviations and determine the causes, comparing different models is important.…”

Section: Introductionmentioning

confidence: 99%

Open Source District Heating Modeling Tools—A Comparative Study

2022

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Heating networks are highly relevant for the achievement of climate protection goals of urban energy systems. This is due to their high renewable energy potential combined with high plant efficiency and utilization rates. For the optimal integration and sector coupling of heating networks in holistic urban energy systems, open source energy system modeling tools are highly recommended. In this contribution, two open source approaches (the “Spreadsheet Energy System Model Generator”-integrated DHNx-Python module (DHNx/SESMG) and Thermos) are theoretically compared, and practically applied to a real-world energy system. Deviations within the results can be explained by incorrectly pre-defined parameters within Thermos and cannot be adjusted by the modeler. The simultaneity is underestimated in the case study by Thermos by more than 20%. This results in undersized heating plant capacities and a 50% higher number of buildings connected to the network. However, Thermos offers a higher end-user usability and over 100 times faster solving. DHNx/SESMG, in contrast, offers the possibility to adjust more model parameters individually and consider multiple energy sectors. This enables a holistic modeling of urban energy systems and the model-based optimization of multi-sectoral synergies.

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Comparing open source power system models - A case study focusing on fundamental modeling parameters for the German energy transition

Cited by 22 publications

References 18 publications

A unified European hydrogen infrastructure planning to support the rapid scale-up of hydrogen production

A unified European hydrogen infrastructure planning to support the rapid scale-up of hydrogen production

Comparison methods of energy system frameworks, models and scenario results

Open Source District Heating Modeling Tools—A Comparative Study

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