A Comprehensive TCO Evaluation Method for Electric Bus Systems Based on Discrete-Event Simulation Including Bus Scheduling and Charging Infrastructure Optimisation

Bus operators around the world are facing the transformation of their fleets from fossil-fuelled to electric buses. Two technologies prevail: Depot charging and opportunity charging at terminal stops. Total cost of ownership (TCO) is an important metric for the decision between the two technologies;...

Full description

Bibliographic Details
Main Authors: Dominic Jefferies, Dietmar Göhlich
Format: Article
Language:English
Published: MDPI AG 2020-08-01
Series:World Electric Vehicle Journal
Subjects:
Online Access:https://www.mdpi.com/2032-6653/11/3/56
id doaj-cd6f5dacc07349a8816d2fbaddb9a5ed
record_format Article
spelling doaj-cd6f5dacc07349a8816d2fbaddb9a5ed2020-11-25T03:51:43ZengMDPI AGWorld Electric Vehicle Journal2032-66532020-08-0111565610.3390/wevj11030056A Comprehensive TCO Evaluation Method for Electric Bus Systems Based on Discrete-Event Simulation Including Bus Scheduling and Charging Infrastructure OptimisationDominic Jefferies0Dietmar Göhlich1Department of Methods for Product Development and Mechatronics, Technische Universität Berlin, Straße des 17. Juni 135, 10623 Berlin, GermanyDepartment of Methods for Product Development and Mechatronics, Technische Universität Berlin, Straße des 17. Juni 135, 10623 Berlin, GermanyBus operators around the world are facing the transformation of their fleets from fossil-fuelled to electric buses. Two technologies prevail: Depot charging and opportunity charging at terminal stops. Total cost of ownership (TCO) is an important metric for the decision between the two technologies; however, most TCO studies for electric bus systems rely on generalised route data and simplifying assumptions that may not reflect local conditions. In particular, the need to reschedule vehicle operations to satisfy electric buses’ range and charging time constraints is commonly disregarded. We present a simulation tool based on discrete-event simulation to determine the vehicle, charging infrastructure, energy and staff demand required to electrify real-world bus networks. These results are then passed to a TCO model. A greedy scheduling algorithm is developed to plan vehicle schedules suitable for electric buses. Scheduling and simulation are coupled with a genetic algorithm to determine cost-optimised charging locations for opportunity charging. A case study is carried out in which we analyse the electrification of a metropolitan bus network consisting of 39 lines with 4748 passenger trips per day. The results generally favour opportunity charging over depot charging in terms of TCO; however, under some circumstances, the technologies are on par. This emphasises the need for a detailed analysis of the local bus network in order to make an informed procurement decision.https://www.mdpi.com/2032-6653/11/3/56electric busbus networksimulationschedulingcharging infrastructuredepot charging
collection DOAJ
language English
format Article
sources DOAJ
author Dominic Jefferies
Dietmar Göhlich
spellingShingle Dominic Jefferies
Dietmar Göhlich
A Comprehensive TCO Evaluation Method for Electric Bus Systems Based on Discrete-Event Simulation Including Bus Scheduling and Charging Infrastructure Optimisation
World Electric Vehicle Journal
electric bus
bus network
simulation
scheduling
charging infrastructure
depot charging
author_facet Dominic Jefferies
Dietmar Göhlich
author_sort Dominic Jefferies
title A Comprehensive TCO Evaluation Method for Electric Bus Systems Based on Discrete-Event Simulation Including Bus Scheduling and Charging Infrastructure Optimisation
title_short A Comprehensive TCO Evaluation Method for Electric Bus Systems Based on Discrete-Event Simulation Including Bus Scheduling and Charging Infrastructure Optimisation
title_full A Comprehensive TCO Evaluation Method for Electric Bus Systems Based on Discrete-Event Simulation Including Bus Scheduling and Charging Infrastructure Optimisation
title_fullStr A Comprehensive TCO Evaluation Method for Electric Bus Systems Based on Discrete-Event Simulation Including Bus Scheduling and Charging Infrastructure Optimisation
title_full_unstemmed A Comprehensive TCO Evaluation Method for Electric Bus Systems Based on Discrete-Event Simulation Including Bus Scheduling and Charging Infrastructure Optimisation
title_sort comprehensive tco evaluation method for electric bus systems based on discrete-event simulation including bus scheduling and charging infrastructure optimisation
publisher MDPI AG
series World Electric Vehicle Journal
issn 2032-6653
publishDate 2020-08-01
description Bus operators around the world are facing the transformation of their fleets from fossil-fuelled to electric buses. Two technologies prevail: Depot charging and opportunity charging at terminal stops. Total cost of ownership (TCO) is an important metric for the decision between the two technologies; however, most TCO studies for electric bus systems rely on generalised route data and simplifying assumptions that may not reflect local conditions. In particular, the need to reschedule vehicle operations to satisfy electric buses’ range and charging time constraints is commonly disregarded. We present a simulation tool based on discrete-event simulation to determine the vehicle, charging infrastructure, energy and staff demand required to electrify real-world bus networks. These results are then passed to a TCO model. A greedy scheduling algorithm is developed to plan vehicle schedules suitable for electric buses. Scheduling and simulation are coupled with a genetic algorithm to determine cost-optimised charging locations for opportunity charging. A case study is carried out in which we analyse the electrification of a metropolitan bus network consisting of 39 lines with 4748 passenger trips per day. The results generally favour opportunity charging over depot charging in terms of TCO; however, under some circumstances, the technologies are on par. This emphasises the need for a detailed analysis of the local bus network in order to make an informed procurement decision.
topic electric bus
bus network
simulation
scheduling
charging infrastructure
depot charging
url https://www.mdpi.com/2032-6653/11/3/56
work_keys_str_mv AT dominicjefferies acomprehensivetcoevaluationmethodforelectricbussystemsbasedondiscreteeventsimulationincludingbusschedulingandcharginginfrastructureoptimisation
AT dietmargohlich acomprehensivetcoevaluationmethodforelectricbussystemsbasedondiscreteeventsimulationincludingbusschedulingandcharginginfrastructureoptimisation
AT dominicjefferies comprehensivetcoevaluationmethodforelectricbussystemsbasedondiscreteeventsimulationincludingbusschedulingandcharginginfrastructureoptimisation
AT dietmargohlich comprehensivetcoevaluationmethodforelectricbussystemsbasedondiscreteeventsimulationincludingbusschedulingandcharginginfrastructureoptimisation
_version_ 1724485999844655104