REVOL-E-TION: A flexible and scalable investment optimization toolbox for local energy systems incorporating electric vehicle fleets

Electric vehicles (EVs) interact with their energy supply systems fundamentally differently than conventional internal combustion engine vehicles (ICEVs). Therefore, only joint consideration can leverage all integration synergies and show the most valuable transition pathway, accelerating EV proliferation, especially for commercial applications recharging in depots. However, openly available toolboxes lack easy-to-use functions for vehicle and mobile storage fleet modeling as well as multi-scenario investment decision making. With REVOL-E-TION, we present an open source local energy system investment optimization toolbox based on the open source oemof framework in Python, filling these gaps. This publication presents both the application spectrum and setup of REVOL-E-TION, and demonstrates its use in a hypothetical municipal fleet depot electrification.

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Publication Details

Journal
SoftwareX
Published
2025-05-27
DOI
https://doi.org/10.1016/j.softx.2025.102178
Citations
1
Primary Topic
Electric Vehicles and Infrastructure
Type
article
Field-Weighted Citation Impact
0.73
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article

REVOL-E-TION: A flexible and scalable investment optimization toolbox for local energy systems incorporating electric vehicle fleets

Philipp Rosner, Markus Lienkamp, Brian Dietermann, Marcel Brödel et al.
1 citations
SoftwareX
Electric Vehicles and Infrastructure
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article

REVOL-E-TION: A flexible and scalable investment optimization toolbox for local energy systems incorporating electric vehicle fleets

Philipp Rosner, Markus Lienkamp, Brian Dietermann, Marcel Brödel, Anna Paper
article en
1 citations

Abstract

Electric vehicles (EVs) interact with their energy supply systems fundamentally differently than conventional internal combustion engine vehicles (ICEVs). Therefore, only joint consideration can leverage all integration synergies and show the most valuable transition pathway, accelerating EV proliferation, especially for commercial applications recharging in depots. However, openly available toolboxes lack easy-to-use functions for vehicle and mobile storage fleet modeling as well as multi-scenario investment decision making. With REVOL-E-TION, we present an open source local energy system investment optimization toolbox based on the open source oemof framework in Python, filling these gaps. This publication presents both the application spectrum and setup of REVOL-E-TION, and demonstrates its use in a hypothetical municipal fleet depot electrification.

SoftwareXVol. 31
Technical University of Munich (DE)
Affordable and clean energy
Openalex Percentile: Top 28%
Electric Vehicles and Infrastructure
0.73
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