Probabilistic modeling of electric vehicle charging pattern in a residential distribution network

Azhar Ul-Haq, Carlo Cecati, Ehab El-Saadany

Research output: Contribution to journalArticlepeer-review

85 Scopus citations


It has been recognized that an increased penetration of electric vehicles (EVs) may potentially alter load profile in a distribution network. Charging pattern of EVs and its corresponding electrical load pattern may be assessed and quantified by using either a deterministic method or stochastic approach. However, deterministic method does not account for stochastic nature of EV users which affects the load pattern and of stochastic nature of grid condition. Thus, a stochastic method is applied to develop a probabilistic model of EVs charging pattern that takes into account various factors such as vehicle class, battery capacity, state of charge (SOC), driving habit/need, i.e. involving trip type and purpose, plug-in time, mileage, recharging frequency per day, charging power rate and dynamic EV charging price under controlled and uncontrolled charging schemes. The probabilistic model gives EV charging pattern over a period of day for different months to represent the load pattern during different seasons of a year. The presented model gives a rigorous estimation of EV charging load pattern in a distribution network which is considered important for network operators.

Original languageBritish English
Pages (from-to)126-133
Number of pages8
JournalElectric Power Systems Research
StatePublished - Apr 2018


  • Distribution system
  • Electric vehicles


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