Optimal location of fast charging stations in Barcelona: A flow-capturing approach

Cruz-Zambrano, Miguel; Corchero, Cristina; Igualada-Gonzalez, L.; Bernardo, Valeria

doi:10.1109/eem.2013.6607414

Cited by 36 publications

(27 citation statements)

References 14 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Studies focusing on the positioning of charging stations for passenger vehicles have to predict the customer behavior in order to get information on the demand [21][22][23]. However, in the field of public transport buses, the operating conditions of the energy consumers are well known.…”

Section: Positioning Of Fast Charging Infrastructurementioning

confidence: 99%

Fast Charging Battery Buses for the Electrification of Urban Public Transport—A Feasibility Study Focusing on Charging Infrastructure and Energy Storage Requirements

2015

View full text Add to dashboard Cite

Abstract:The electrification of public transport bus networks can be carried out utilizing different technological solutions, like trolley, battery or fuel cell buses. The purpose of this paper is to analyze how and to what extent existing bus networks can be electrified with fast charging battery buses. The so called opportunity chargers use mainly the regular dwell time at the stops to charge their batteries. This results in a strong linkage between the vehicle scheduling and the infrastructure planning. The analysis is based on real-world data of the bus network in Muenster, a mid-sized city in Germany. The outcomes underline the necessity to focus on entire vehicle schedules instead on individual trips. The tradeoff between required battery capacity and charging power is explained in detail. Furthermore, the impact on the electricity grid is discussed based on the load profiles of a selected charging station and a combined load profile of the entire network.

show abstract

Section: Positioning Of Fast Charging Infrastructurementioning

confidence: 99%

Fast Charging Battery Buses for the Electrification of Urban Public Transport—A Feasibility Study Focusing on Charging Infrastructure and Energy Storage Requirements

2015

View full text Add to dashboard Cite

show abstract

“…A vehicle commuting between an OD is assumed to be "captured" (or charged) if there is at least one facility located along the shortest path between this OD pair. A handful of studies have presented models for the optimal locations of the facilities to capture traffic flows [17][18][19][20][21]. The authors in [17] proposed a flow-capturing location allocation model (FCLM) to maximize the number of served customers.…”

Section: Related Workmentioning

confidence: 99%

“…Moreover, the same group of authors presented an effective mixed-binary-integer programming formulation to solve the FRLM [20]. Applying the FCLM mentioned above, the authors in [21] presented two optimization models of FCS locations and illustrated its effectiveness on a case study of the City of Barcelona. However, most of the early works assume that a vehicle is charged when it passes through a located station.…”

Section: Related Workmentioning

confidence: 99%

A Hierarchical Optimization Model for a Network of Electric Vehicle Charging Stations

et al. 2017

View full text Add to dashboard Cite

Abstract:Charging station location decisions are a critical element in mainstream adoption of electric vehicles (EVs). The consumer confidence in EVs can be boosted with the deployment of carefully-planned charging infrastructure that can fuel a fair number of trips. The charging station (CS) location problem is complex and differs considerably from the classical facility location literature, as the decision parameters are additionally linked to a relatively longer charging period, battery parameters, and available grid resources. In this study, we propose a three-layered system model of fast charging stations (FCSs). In the first layer, we solve the flow capturing location problem to identify the locations of the charging stations. In the second layer, we use a queuing model and introduce a resource allocation framework to optimally provision the limited grid resources. In the third layer, we consider the battery charging dynamics and develop a station policy to maximize the profit by setting maximum charging levels. The model is evaluated on the Arizona state highway system and North Dakota state network with a gravity data model, and on the City of Raleigh, North Carolina, using real traffic data. The results show that the proposed hierarchical model improves the system performance, as well as the quality of service (QoS), provided to the customers. The proposed model can efficiently assist city planners for CS location selection and system design.

show abstract

“…The approach comprises a mixed-integer non-linear (MINLP) optimization in order to minimize the total cost associated with supplying the energy demand of EV based on the number of charging stations. By comparing two different approaches to identify the optimal location of fast charging stations, Cruz-Zambrano [17] highlight the importance of considering installation cost. The two methodologies are based on Flow-Capturing Location-Allocation Model (FCLM) and differ in their objective function.…”

Section: Literature Reviewmentioning

confidence: 99%

Electrification of a City Bus Network: An Optimization Model for Cost-Effective Placing of Charging Infrastructure and Battery Sizing of Fast Charging Electric Bus Systems

Kunith

Mendelevitch²,

Goehlich

2016

SSRN Journal

View full text Add to dashboard Cite

Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. Terms of use: Documents in AbstractThe deployment of battery-powered electric bus systems within the public transportation sector plays an important role to increase energy efficiency and to abate emissions. Rising attention is given to bus systems using fast charging technology. This concept requires a comprehensive infrastructure to equip bus routes with charging stations. The combination of charging infrastructure and bus batteries needs a reliable energy supply to maintain a stable bus operation even under demanding conditions. An efficient layout of the charging infrastructure and an appropriate dimensioning of battery capacity are crucial to minimize the total cost of ownership and to enable an energetically feasible bus operation. In this work, the central issue of jointly optimizing the charging infrastructure and battery capacity is described by a capacitated set covering problem. A mixed-integer linear optimization model is developed to determine the minimum number and location of required charging stations for a bus network as well as the adequate battery capacity for each bus line of the network. The bus energy consumption for each route segments is determined based on individual route, bus type, traffic and other information. Different scenarios are examined in order to assess the influence of charging power, climate and changing operating conditions. The findings reveal significant differences in terms of needed infrastructure depending on the scenarios considered. Moreover, the results highlight a trade-off between battery size and charging infrastructure under different operational and infrastructure conditions. The paper addresses upcoming challenges for transport authorities during the electrification process of the bus fleets and sharpens the focus on infrastructural issues related to the fast charging concept. JEL codes: C61; L92; R42

show abstract

Optimal location of fast charging stations in Barcelona: A flow-capturing approach

Cited by 36 publications

References 14 publications

Fast Charging Battery Buses for the Electrification of Urban Public Transport—A Feasibility Study Focusing on Charging Infrastructure and Energy Storage Requirements

Fast Charging Battery Buses for the Electrification of Urban Public Transport—A Feasibility Study Focusing on Charging Infrastructure and Energy Storage Requirements

A Hierarchical Optimization Model for a Network of Electric Vehicle Charging Stations

Electrification of a City Bus Network: An Optimization Model for Cost-Effective Placing of Charging Infrastructure and Battery Sizing of Fast Charging Electric Bus Systems

Contact Info

Product

Resources

About