Blat-Belmonte, Benjamin ; Rinderknecht, Stephan (2021)
Optimization Approach for Long-Term Planning of Charging Infrastructure for Fixed-Route Transportation Systems.
In: World Electric Vehicle Journal, 12 (4)
doi: 10.3390/wevj12040258
Artikel, Bibliographie
Kurzbeschreibung (Abstract)
As the electrification of the transportation sector advances, fleet operators have to rethink their approach regarding fleet management against the background of limiting factors, such as a reduced range or extended recharging times. Charging infrastructure plays a critical role, and it is worthwhile to consider its planning as an integral part for the long-term operation of an electric vehicle fleet. In the category of fixed route transportation systems, the predictable character of the routes can be exploited when planning charging infrastructure. After a prior categorization of stakeholders and their respective optimization objectives in the sector coupling domain, a cost optimization framework for fixed route transportation systems is presented as the main contribution of this work. We confirm previous literature in that there is no one-fits-all optimization method for this kind of problem. The method is tested on seven scenarios for the public transport operator of Darmstadt, Germany. The core optimization is formulated as a mixed integer linear programming (MILP) problem. All scenarios are terminated by the criterion of a maximum solving time of 48 h and provide feasible solutions with a relative MIP-gap between 7 and 24%.
| Typ des Eintrags: | Artikel |
|---|---|
| Erschienen: | 2021 |
| Autor(en): | Blat-Belmonte, Benjamin ; Rinderknecht, Stephan |
| Art des Eintrags: | Bibliographie |
| Titel: | Optimization Approach for Long-Term Planning of Charging Infrastructure for Fixed-Route Transportation Systems |
| Sprache: | Englisch |
| Publikationsjahr: | 10 Dezember 2021 |
| Verlag: | MDPI |
| Titel der Zeitschrift, Zeitung oder Schriftenreihe: | World Electric Vehicle Journal |
| Jahrgang/Volume einer Zeitschrift: | 12 |
| (Heft-)Nummer: | 4 |
| DOI: | 10.3390/wevj12040258 |
| URL / URN: | https://www.mdpi.com/2032-6653/12/4/258 |
| Kurzbeschreibung (Abstract): | As the electrification of the transportation sector advances, fleet operators have to rethink their approach regarding fleet management against the background of limiting factors, such as a reduced range or extended recharging times. Charging infrastructure plays a critical role, and it is worthwhile to consider its planning as an integral part for the long-term operation of an electric vehicle fleet. In the category of fixed route transportation systems, the predictable character of the routes can be exploited when planning charging infrastructure. After a prior categorization of stakeholders and their respective optimization objectives in the sector coupling domain, a cost optimization framework for fixed route transportation systems is presented as the main contribution of this work. We confirm previous literature in that there is no one-fits-all optimization method for this kind of problem. The method is tested on seven scenarios for the public transport operator of Darmstadt, Germany. The core optimization is formulated as a mixed integer linear programming (MILP) problem. All scenarios are terminated by the criterion of a maximum solving time of 48 h and provide feasible solutions with a relative MIP-gap between 7 and 24%. |
| Freie Schlagworte: | cost optimization, charging infrastructure, fixed-route transportation systems, electric vehicle fleets, operations research, electromobility |
| Fachbereich(e)/-gebiet(e): | 16 Fachbereich Maschinenbau 16 Fachbereich Maschinenbau > Institut für Mechatronische Systeme im Maschinenbau (IMS) |
| Hinterlegungsdatum: | 25 Jan 2022 06:12 |
| Letzte Änderung: | 25 Jan 2022 09:46 |
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