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
Article, Bibliographie
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%.
| Item Type: | Article |
|---|---|
| Erschienen: | 2021 |
| Creators: | Blat-Belmonte, Benjamin ; Rinderknecht, Stephan |
| Type of entry: | Bibliographie |
| Title: | Optimization Approach for Long-Term Planning of Charging Infrastructure for Fixed-Route Transportation Systems |
| Language: | English |
| Date: | 10 December 2021 |
| Publisher: | MDPI |
| Journal or Publication Title: | World Electric Vehicle Journal |
| Volume of the journal: | 12 |
| Issue Number: | 4 |
| DOI: | 10.3390/wevj12040258 |
| URL / URN: | https://www.mdpi.com/2032-6653/12/4/258 |
| 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%. |
| Uncontrolled Keywords: | cost optimization, charging infrastructure, fixed-route transportation systems, electric vehicle fleets, operations research, electromobility |
| Divisions: | 16 Department of Mechanical Engineering 16 Department of Mechanical Engineering > Institute for Mechatronic Systems in Mechanical Engineering (IMS) |
| Date Deposited: | 25 Jan 2022 06:12 |
| Last Modified: | 25 Jan 2022 09:46 |
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