Impact of Charging Electric Vehicles under Different State of Charge Levels and Extreme Conditions

Claude Ziad El-Bayeh, Mohamed Zellagui, Brahim Brahmi, Walid Alqaisi and Ursula Eicker
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Claude Ziad El-Bayeh: Canada Excellence Research Chair Team, Concordia University, Montreal, QC H3G 1M8, Canada
Mohamed Zellagui: Department of Electrical Engineering, Faculty of Technology, University of Batna 2, Fesdis, Batna 05078, Algeria
Brahim Brahmi: Electrical and Computer Engineering Department, Miami University, 260Q Garland Hall, 650 East High Street, Oxford, OH 45056, USA
Walid Alqaisi: School of Engineering Technology, College of the North Atlantic, Al Tarafa, Jelaiah Street, Duhail North, Doha P.O. Box 24449, Qatar
Ursula Eicker: Canada Excellence Research Chair Team, Concordia University, Montreal, QC H3G 1M8, Canada

Energies, 2021, vol. 14, issue 20, 1-19

Abstract: High penetration levels of Plug-in Electric Vehicles (PEVs) could cause stress on the network and might violate the limits and constraints under extreme conditions, such as exceeding power and voltage limits on transformers and power lines. This paper defines extreme conditions as the state of a load or network that breaks the limits of the constraints in an optimization model. Once these constraints are violated, the optimization algorithm might not work correctly and might not converge to a feasible solution, especially when the complexity of the system increases and includes nonlinearities. Hence, the algorithm may not help in mitigating the impact of penetrating PEVs under extreme conditions. To solve this problem, an original algorithm is suggested that is able to adapt the constraints’ limits according to the energy demand and the energy needed to charge the PEVs. Different case scenarios are studied for validation purposes, such as charging PEVs under different state of charge levels, different energy demands at home, and different pricing mechanisms. Results show that our original algorithm improved the profiles of the voltage and power under extreme conditions. Hence, the algorithm is able to improve the integration of a high number of PEVs on the distribution system under extreme conditions while preserving its stability.

Keywords: distribution systems; electric vehicles; optimization; power systems; smart homes; smart grid; techno-economic impact; voltage stability (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2021
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