Abstract
Electric vehicles (EVs) have received considerable attention in dealing with severe environmental and energy crises. The capacity planning of public charging stations has been a major factor in facilitating the wide market penetration of EVs. In this paper, we present an optimization model for charging station capacity planning to maximize the fuzzy quality of service (FQoS) considering queuing behavior, blocking reliability, and multiple charging options classified by battery technical specifications. The uncertainty of the EV arrival and service time are taken into account and described as fuzzy numbers characterized by triangular membership functions. Meanwhile, an -cuts-based algorithm is proposed to defuzzify the FQoS. Finally, the numerical results illustrate that a more robust plan can be obtained by accounting for FQoS. The contribution of the proposed model allows decision-makers and operators to plan the capacity of charging stations with fuzzy EV arrival rate and service rate and provide a better service for customers with different charging options.
| Original language | English |
|---|---|
| Pages (from-to) | 12529-12541 |
| Number of pages | 13 |
| Journal | IEEE Transactions on Vehicular Technology |
| Volume | 70 |
| Issue number | 12 |
| DOIs | |
| Publication status | Published - 20 Oct 2021 |
Keywords
- capacity planning
- Capacity planning
- charging station
- Charging stations
- electric vehicle
- Electric vehicle charging
- fuzzy quality of service
- multiple charging options
- Power system reliability
- Quality of service
- Queueing analysis
- Sockets
ASJC Scopus subject areas
- Automotive Engineering
- Aerospace Engineering
- Electrical and Electronic Engineering
- Applied Mathematics