An Optimization Model to Upgrade the Charging Network of Electric Vehicles

An Optimization Model to Upgrade the Charging Network of Electric Vehicles

Fu, Dawei (TU Delft Civil Engineering and Geosciences)

van Arem, B. (mentor)

Delft University of Technology

Civil Engineering | Construction Management and Engineering

2020-08-31

The current city charging network for electric vehicle (EV) is mainly composed of low-speed charging points. When the number of EVs increase dramatically in the future, the current charging network needs to be upgraded with more charging stations and fast-charging (FC) facilities. We build a mixed-integer programming (MIP) model to propose an upgrading scheme for a city’s public EV charging network, in which new stations can be constructed and some low-speed chargers will be upgraded to fast chargers. The model considers two charging patterns. Drivers can stay at the charging station or walk to their activity places during the charging process, which affects drivers’ satisfaction to a large extent if the waiting time or walking distance is unacceptable. Hence, our optimization model has the objective of minimizing the network upgrading cost and the drivers’ sacrifice of waiting at charging stations and walking to their activity places. In the case study, we obtain the features of the driver’s charging behavior from the analysis of Den Haag’s EV charging database and utilize these features as model inputs. The optimal solution shows that about 40% of the old charging stations are upgraded with faster chargers in the new charging network, and the network adopts more FC stations at the territory with a high vehicle density. Meanwhile, half of the drivers choose to charge at FC stations after upgrading, and every driver can find a charging position at their desirable charging time within an average walking distance of about 160m from the activity place. The new charging network has a great utilization situation during the day, and more than 65% of the charging positions are in operation at night. Through varying the budgets for network upgrading, waiting time cost and travel penalty, our model provides many different upgrading schemes for decision-makers. The solutions reveal that the travel penalty and budget have a noticeable influence on the network capacity, while the waiting time cost mainly influences the number of super-fast charging stations. If we take customer’s satisfaction level into the first place, the investor ought to provide an adequate budget for network upgrading and install a few super-fast charging stations to improve the charging speed.

Public charging network
electric vehicles
MIP model
charging demand satisfaction
upgrading cost
charging behaviors

http://resolver.tudelft.nl/uuid:b4ddc548-c1f6-47f3-9b5a-9ae27cab9738

Student theses

master thesis

© 2020 Dawei Fu