Impact of Charging Electric Vehicles under Different State of Charge Levels and Extreme Conditions
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.
Other Information
Published in: Energies
License: https://creativecommons.org/licenses/by/4.0/
See article on publisher's website: https://dx.doi.org/10.3390/en14206589
Disclaimer: The University of Doha for Science and Technology replaced the now-former College of the North Atlantic-Qatar after an Amiri decision in 2022. UDST has become and first national applied University in Qatar; it is also second national University in the country.
Funding
Canada Excellence Research Chairs Program,Tri-Agency Institutional Program Secretariat (N/A)
History
Language
- English
Publisher
MDPIPublication Year
- 2021
License statement
This Item is licensed under the Creative Commons Attribution 4.0 International License.Institution affiliated with
- University of Doha for Science and Technology
- College of Engineering and Technology - UDST
- College of the North Atlantic - Qatar (2002-2022)
- School of Engineering Technology and Industrial Trades - CNA-Q (2002-2022)