A model for electric vehicle charging load forecasting based on simulated driving path

H. Y. Ma, J. H. Wang, T. Zheng, Z. Li, H. Y. Wang

Research output: Contribution to journalConference articlepeer-review

Abstract

With the replacement of power sources of traditional vehicles, the penetration of EVs in the world is increasing year by year. When large-scale EVs are connected to the power grid, it will affect the structure and power flow of the grid. This paper simulates the vehicle route in the planning area, proposes a method to predict the probability distribution method for the users to choose the specific route based on the Markov process theory and the traffic network database. Refer to the habits and charging preferences of EV users, taking private EVs as the research object, Monte Carlo simulation is used to predict the charging demand generated by EVs in the function area and important road nodes in the planned area. In view of the difference of peak price and valley price, considering the low valley-time price, the probability of load transfer is large. Changing the discharge strategy to realize the peak load shifting in V2V mode.

Original languageEnglish
Article number012115
JournalIOP Conference Series: Materials Science and Engineering
Volume486
Issue number1
DOIs
StatePublished - 2019
Externally publishedYes
Event2019 4th Asia Conference on Power and Electrical Engineering, ACPEE 2019 - Hangzhou, China
Duration: Mar 28 2019Mar 31 2019

Fingerprint

Dive into the research topics of 'A model for electric vehicle charging load forecasting based on simulated driving path'. Together they form a unique fingerprint.

Cite this