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A Review of Optimal Charging Strategy for Electric Vehicles under Dynamic Pricing Schemes in the Distribution Charging Network

Author

Listed:
  • Adil Amin

    (Department of Electrical Engineering, Mirpur University of Science & Technology, (MUST), AJ&K, Mirpur 10250, Pakistan)

  • Wajahat Ullah Khan Tareen

    (Department of Electrical and Electronic Engineering, College of Engineering, University of Jeddah, Jeddah 21589, Saudi Arabia)

  • Muhammad Usman

    (Department of Electrical Engineering, Mirpur University of Science & Technology, (MUST), AJ&K, Mirpur 10250, Pakistan)

  • Haider Ali

    (Department of Electrical and Electronic Engineering Technology, University of Technology Nowshera, Nowshera 24100, Pakistan)

  • Inam Bari

    (Department of System Engineering, Military Technological College, Al Matar Street, Muscat 111, Oman)

  • Ben Horan

    (School of Engineering, Deakin University, Waurn Ponds, VIC 3216, Australia)

  • Saad Mekhilef

    (Power Electronics and Renewable Energy Research Laboratory (PEARL), Department of Electrical Engineering, University of Malaya, Kuala Lumpur 50603, Malaysia
    School of Software and Electrical Engineering, Swinburne University of Technology, Hawthorn, Melbourne, VIC 3122, Australia
    Center of Research Excellence in Renewable Energy and Power Systems, King Abdulaziz University, Jeddah 21589, Saudi Arabia)

  • Muhammad Asif

    (Department of Electrical Engineering, Mirpur University of Science & Technology, (MUST), AJ&K, Mirpur 10250, Pakistan)

  • Saeed Ahmed

    (Department of Electrical Engineering, Mirpur University of Science & Technology, (MUST), AJ&K, Mirpur 10250, Pakistan)

  • Anzar Mahmood

    (Department of Electrical Engineering, Mirpur University of Science & Technology, (MUST), AJ&K, Mirpur 10250, Pakistan)

Abstract

This study summarizes a critical review on EVs’ optimal charging and scheduling under dynamic pricing schemes. A detailed comparison of these schemes, namely, Real Time Pricing (RTP), Time of Use (ToU), Critical Peak Pricing (CPP), and Peak Time Rebates (PTR), is presented. Globally, the intention is to reduce the carbon emissions (CO 2 ) has motivated the extensive practice of Electric Vehicles (EVs). The uncoordinated charging and uncontrolled integration however of EVs to the distribution network deteriorates the system performance in terms of power quality issues. Therefore, the EVs’ charging activity can be coordinated by dynamic electricity pricing, which can influence the charging activities of the EVs customers by offering flexible pricing at different demands. Recently, with developments in technology and control schemes, the RTP scheme offers more promise compared to the other types of tariff because of the greater flexibility for EVs’ customers to adjust their demands. It however involves higher degree of billing instability, which may influence the customer’s confidence. In addition, the RTP scheme needs a robust intelligent automation system to improve the customer’s feedback to time varying prices. In addition, the review covers the main optimization methods employed in a dynamic pricing environment to achieve objectives such as power loss and electricity cost minimization, peak load reduction, voltage regulation, distribution infrastructure overloading minimization, etc.

Suggested Citation

  • Adil Amin & Wajahat Ullah Khan Tareen & Muhammad Usman & Haider Ali & Inam Bari & Ben Horan & Saad Mekhilef & Muhammad Asif & Saeed Ahmed & Anzar Mahmood, 2020. "A Review of Optimal Charging Strategy for Electric Vehicles under Dynamic Pricing Schemes in the Distribution Charging Network," Sustainability, MDPI, vol. 12(23), pages 1-28, December.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:23:p:10160-:d:457258
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    2. Kaur, Amrit Pal & Singh, Mukesh, 2023. "Time-of-Use tariff rates estimation for optimal demand-side management using electric vehicles," Energy, Elsevier, vol. 273(C).
    3. Tuğba Yeğin & Muhammad Ikram, 2022. "Analysis of Consumers’ Electric Vehicle Purchase Intentions: An Expansion of the Theory of Planned Behavior," Sustainability, MDPI, vol. 14(19), pages 1-27, September.
    4. Monica Alonso & Hortensia Amaris & David Martin & Arturo de la Escalera, 2023. "Proximal Policy Optimization for Energy Management of Electric Vehicles and PV Storage Units," Energies, MDPI, vol. 16(15), pages 1-20, July.
    5. Luigi Pio di Noia & Fabio Mottola & Daniela Proto & Renato Rizzo, 2022. "Real Time Scheduling of a Microgrid Equipped with Ultra-Fast Charging Stations," Energies, MDPI, vol. 15(3), pages 1-18, January.
    6. Muhammad Usman & Wajahat Ullah Khan Tareen & Adil Amin & Haider Ali & Inam Bari & Muhammad Sajid & Mehdi Seyedmahmoudian & Alex Stojcevski & Anzar Mahmood & Saad Mekhilef, 2021. "A Coordinated Charging Scheduling of Electric Vehicles Considering Optimal Charging Time for Network Power Loss Minimization," Energies, MDPI, vol. 14(17), pages 1-16, August.
    7. Vamsi Krishna Reddy, Aala Kalananda & Venkata Lakshmi Narayana, Komanapalli, 2022. "Meta-heuristics optimization in electric vehicles -an extensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
    8. Nur Ayeesha Qisteena Muzir & Md. Rayid Hasan Mojumder & Md. Hasanuzzaman & Jeyraj Selvaraj, 2022. "Challenges of Electric Vehicles and Their Prospects in Malaysia: A Comprehensive Review," Sustainability, MDPI, vol. 14(14), pages 1-40, July.
    9. Bireswar Dutta & Hsin-Ginn Hwang, 2021. "Consumers Purchase Intentions of Green Electric Vehicles: The Influence of Consumers Technological and Environmental Considerations," Sustainability, MDPI, vol. 13(21), pages 1-23, October.
    10. Ajit Kumar Mohanty & Perli Suresh Babu & Surender Reddy Salkuti, 2022. "Optimal Allocation of Fast Charging Station for Integrated Electric-Transportation System Using Multi-Objective Approach," Sustainability, MDPI, vol. 14(22), pages 1-22, November.
    11. Rajaa Naji EL idrissi & Mohammed Ouassaid & Mohamed Maaroufi & Zineb Cabrane & Jonghoon Kim, 2023. "Optimal Cooperative Power Management Framework for Smart Buildings Using Bidirectional Electric Vehicle Modes," Energies, MDPI, vol. 16(5), pages 1-22, February.
    12. Andre Leippi & Markus Fleschutz & Michael D. Murphy, 2022. "A Review of EV Battery Utilization in Demand Response Considering Battery Degradation in Non-Residential Vehicle-to-Grid Scenarios," Energies, MDPI, vol. 15(9), pages 1-22, April.

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