Abstract
Fast charging stations are critical infrastructures to enable high penetration of plug-in electric vehicles (PEVs) into future distribution networks. They need to be carefully planned to meet charging demand as well as ensure economic benefits. Accurate estimation of PEV charging demand is the prerequisite of such planning, but a nontrivial task. This paper addresses the sizing (number of chargers and waiting spaces) problem of fast charging stations and presents an optimal planning solution based on an explicit temporal-state of charge characterization of PEV fast charging demand. The characteristics of PEV charging demand are derived through a vehicle travel behavior analysis using available statistics. The PEV dynamics in charging stations is modelled with a Markov chain and queuing theory. As a result, the optimal number of chargers and waiting spaces in fast charging stations can be jointly determined to maximize expected operator profits, considering profit of charging service, penalty of waiting and rejection, as well as maintenance cost of idle facilities. The proposed solution is validated through a case study with mathematical justifications and simulation results.
| Original language | English (US) |
|---|---|
| Article number | 8421601 |
| Pages (from-to) | 4457-4466 |
| Number of pages | 10 |
| Journal | IEEE Transactions on Smart Grid |
| Volume | 10 |
| Issue number | 4 |
| DOIs | |
| State | Published - Jul 2019 |
| Externally published | Yes |
All Science Journal Classification (ASJC) codes
- General Computer Science
Keywords
- Markov model
- Monte Carlo simulation
- Plug-in electric vehicle (PEV)
- charging station planning
- queuing theory
- state of charge (SoC)