Electric Vehicles Charging Management for Real-Time Pricing Considering the Preferences of Individual Vehicles

The paper proposes a real-time model for electric vehicles (EVs) controlled load charging. The proposed demand-side management (DSM) of EVs is implemented based on queuing analysis with a nonhomogeneous arrival rate and charging service periods dataset. An electric vehicle model is used which is bas...

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Bibliographic Details
Published in:Applied sciences 2021-07, Vol.11 (14), p.6632
Main Authors: Selim, Ali, Abdel-Akher, Mamdouh, Kamel, Salah, Jurado, Francisco, Almohaimeed, Sulaiman A.
Format: Article
Language:English
Subjects:
Alternative energy sources
controllable loads
Electric power demand
Electric power generation
Electric vehicles
electric vehicles (EVs)
Electricity
Electricity pricing
Industrial plant emissions
intermittent demand load
Markov analysis
Mathematical models
Monte Carlo simulation
Optimization techniques
peak shifting
Power plants
Probability distribution
Queuing theory
Random variables
Real time
Simulation
smart grids
Statistical analysis
Time series
Wind power
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Summary:The paper proposes a real-time model for electric vehicles (EVs) controlled load charging. The proposed demand-side management (DSM) of EVs is implemented based on queuing analysis with a nonhomogeneous arrival rate and charging service periods dataset. An electric vehicle model is used which is based on a statistical survey to represent the uncontrolled demand of the EVs. A probability distribution for the time at which EVs are plugged and the corresponding value of the state of charges (SOCs) are considered. The preferences of individual EVs have been fully exploited through a set of instructions to fulfill the needs of the vehicles’ owners. The designated preferences include the owner setting for both, charging price preferences (OPR), and the maximum estimated parking time duration (EPTD). The quasi-static time-series (QSTS) simulation is used to simulate real-time scenarios of the 24-h simulation period. The IEEE 123 nodes radial test feeder is analyzed with different daily load curves, EV charging scenarios, and wind power penetrations. The results show the effectiveness of the proposed DSM in avoiding excessive levels of charging with/without penetration of non-dispatchable wind power generation. The proposed DSM enables the EVs to charge with low tariff rates either at excessive renewable power generation or late evening hours with available committed bulk power plants and light loading conditions.
ISSN:2076-3417
2076-3417
DOI:10.3390/app11146632