Philipp Rosner , Brian Dietermann , Marcel Brödel, Anna Paper, Markus Lienkamp
{"title":"REVOL-E-TION: A flexible and scalable investment optimization toolbox for local energy systems incorporating electric vehicle fleets","authors":"Philipp Rosner , Brian Dietermann , Marcel Brödel, Anna Paper, Markus Lienkamp","doi":"10.1016/j.softx.2025.102178","DOIUrl":null,"url":null,"abstract":"<div><div>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.</div></div>","PeriodicalId":21905,"journal":{"name":"SoftwareX","volume":"31 ","pages":"Article 102178"},"PeriodicalIF":2.4000,"publicationDate":"2025-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"SoftwareX","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2352711025001451","RegionNum":4,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
引用次数: 0
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.
revolution - e - tion:一个灵活、可扩展的投资优化工具箱,适用于包含电动汽车车队的地方能源系统
电动汽车(ev)与传统内燃机汽车(icev)的能源供应系统的相互作用有着根本的不同。因此,只有共同考虑,才能充分发挥所有整合协同效应,展现最有价值的过渡路径,加速电动汽车的扩散,特别是在商业应用中,在车辆段充电。然而,公开可用的工具箱在车辆和移动存储车队建模以及多场景投资决策方面缺乏易于使用的功能。通过revolution - e - tion,我们提出了一个基于Python开源oemoof框架的开源本地能源系统投资优化工具箱,填补了这些空白。本出版物介绍了revolution - e - tion的应用范围和设置,并演示了其在假设的市政车队仓库电气化中的应用。
期刊介绍:
SoftwareX aims to acknowledge the impact of software on today''s research practice, and on new scientific discoveries in almost all research domains. SoftwareX also aims to stress the importance of the software developers who are, in part, responsible for this impact. To this end, SoftwareX aims to support publication of research software in such a way that: The software is given a stamp of scientific relevance, and provided with a peer-reviewed recognition of scientific impact; The software developers are given the credits they deserve; The software is citable, allowing traditional metrics of scientific excellence to apply; The academic career paths of software developers are supported rather than hindered; The software is publicly available for inspection, validation, and re-use. Above all, SoftwareX aims to inform researchers about software applications, tools and libraries with a (proven) potential to impact the process of scientific discovery in various domains. The journal is multidisciplinary and accepts submissions from within and across subject domains such as those represented within the broad thematic areas below: Mathematical and Physical Sciences; Environmental Sciences; Medical and Biological Sciences; Humanities, Arts and Social Sciences. Originating from these broad thematic areas, the journal also welcomes submissions of software that works in cross cutting thematic areas, such as citizen science, cybersecurity, digital economy, energy, global resource stewardship, health and wellbeing, etcetera. SoftwareX specifically aims to accept submissions representing domain-independent software that may impact more than one research domain.