Statistical Analysis and Modeling of Plug-in Electric Vehicle Charging Demand in Distribution Systems Conference Paper

abstract

• 2017 IEEE. This paper establishes stochastic model of plug-in electric vehicle (PEV) charging and derives the probabilistic description of the electricity needs from EV charging for one charging station at any hour of a day. Three key variables are used to characterize the stochastic behavior of EV charging: starting time of charging, state of charge (SOC), and total number of charging EVs. The electricity needs of an EV charging station is a function of time, which can be depicted by the expectation of charging needs at a certain time of day. Numerical simulations are implemented to validate the proposed analysis approach and illustrate the impact of EVs' charging demand on the distribution systems.

name of conference

• 2017 19th International Conference on Intelligent System Application to Power Systems (ISAP)

authors

• Kezunovic, Mladen

published proceedings

• 2017 19TH INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEM APPLICATION TO POWER SYSTEMS (ISAP)

author list (cited authors)

• Yan, Q., Qian, C., Zhang, B., & Kezunovic, M.

citation count

• 17

complete list of authors

• Yan, Qin||Qian, Cheng||Zhang, Bei||Kezunovic, Mladen

publication date

• January 2017

publisher

• Institute of Electrical and Electronics Engineers (IEEE)  Publisher

keywords

• Charging Stations
• Plug-in Electric Vehicles
• Statistical Analysis

Digital Object Identifier (DOI)

• 10.1109/isap.2017.8071365

International Standard Book Number (ISBN) 13

• 9781509040001

start page

• 1

end page

• 6

URL

• http://dx.doi.org/10.1109/isap.2017.8071365

user-defined tag

• 7 Affordable and Clean Energy