IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i16p5037-d615775.html
   My bibliography  Save this article

Stochastic Modelling to Analyze the Impact of Electric Vehicle Penetration in Thailand

Author

Listed:
  • Narongkorn Uthathip

    (Department of Electrical and Computer Engineering, Thammasat School of Engineering, Thammasat University, Pathum Thani 12120, Thailand)

  • Pornrapeepat Bhasaputra

    (Department of Electrical and Computer Engineering, Thammasat School of Engineering, Thammasat University, Pathum Thani 12120, Thailand)

  • Woraratana Pattaraprakorn

    (Department of Chemical Engineering, Thammasat School of Engineering, Thammasat University, Pathum Thani 12120, Thailand)

Abstract

Electric Vehicle (EV) technology is one of the most promising solutions to reduce dependence on fossil fuels and greenhouse gas (GHG) emissions in the transportation sector. However, a large increase of EVs raises concerns about negative impacts on electricity generation, transmission, and distribution systems. This study analyzes the benefits and trade-offs for EV penetration in Thai road transport based on EV penetration scenarios from 2019 to 2036. Two charging strategies are considered to assess the impact of EV charging: free charging and off-peak charging. Uncertainty variables are considered by a stochastic approach based on Monte-Carlo simulation (MCS). The simulation results shown that the adoption of EVs can reduce both energy consumption and GHG emissions. The results also indicate that the increased load due to EV charging demand in all scenarios is still within the buffer level, compared to the installed generation capacity in the Power Development Plan 2018 revision 1 (PDP2018r1), and the off-peak charging strategy is more beneficial than the free-charging strategy. However, the increased load demand caused by all EV charging strategies has a direct impact on the power generating schedule, and also decreases the system reliability level.

Suggested Citation

  • Narongkorn Uthathip & Pornrapeepat Bhasaputra & Woraratana Pattaraprakorn, 2021. "Stochastic Modelling to Analyze the Impact of Electric Vehicle Penetration in Thailand," Energies, MDPI, vol. 14(16), pages 1-23, August.
  • Handle: RePEc:gam:jeners:v:14:y:2021:i:16:p:5037-:d:615775
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/16/5037/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/14/16/5037/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ramteen Sioshansi & Paul Denholm, 2010. "The Value of Plug-In Hybrid Electric Vehicles as Grid Resources," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 1-24.
    2. Daina, Nicolò & Sivakumar, Aruna & Polak, John W., 2017. "Modelling electric vehicles use: a survey on the methods," Renewable and Sustainable Energy Reviews, Elsevier, vol. 68(P1), pages 447-460.
    3. Piotr Wróblewski & Jerzy Kupiec & Wojciech Drożdż & Wojciech Lewicki & Jarosław Jaworski, 2021. "The Economic Aspect of Using Different Plug-In Hybrid Driving Techniques in Urban Conditions," Energies, MDPI, vol. 14(12), pages 1-17, June.
    4. Jing Lian & Shuang Liu & Linhui Li & Xuanzuo Liu & Yafu Zhou & Fan Yang & Lushan Yuan, 2017. "A Mixed Logical Dynamical-Model Predictive Control (MLD-MPC) Energy Management Control Strategy for Plug-in Hybrid Electric Vehicles (PHEVs)," Energies, MDPI, vol. 10(1), pages 1-18, January.
    5. Jong Hui Moon & Han Na Gwon & Gi Ryong Jo & Woo Yeong Choi & Kyung Soo Kook, 2020. "Stochastic Modeling Method of Plug-in Electric Vehicle Charging Demand for Korean Transmission System Planning," Energies, MDPI, vol. 13(17), pages 1-14, August.
    6. Foley, Aoife & Tyther, Barry & Calnan, Patrick & Ó Gallachóir, Brian, 2013. "Impacts of Electric Vehicle charging under electricity market operations," Applied Energy, Elsevier, vol. 101(C), pages 93-102.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Kantapich Preedakorn & David Butler & Jörn Mehnen, 2023. "Challenges for the Adoption of Electric Vehicles in Thailand: Potential Impacts, Barriers, and Public Policy Recommendations," Sustainability, MDPI, vol. 15(12), pages 1-21, June.
    2. Anna Auza & Ehsan Asadi & Behrang Chenari & Manuel Gameiro da Silva, 2023. "A Systematic Review of Uncertainty Handling Approaches for Electric Grids Considering Electrical Vehicles," Energies, MDPI, vol. 16(13), pages 1-25, June.
    3. Pramote Jaruwatanachai & Yod Sukamongkol & Taweesak Samanchuen, 2023. "Predicting and Managing EV Charging Demand on Electrical Grids: A Simulation-Based Approach," Energies, MDPI, vol. 16(8), pages 1-22, April.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Szinai, Julia K. & Sheppard, Colin J.R. & Abhyankar, Nikit & Gopal, Anand R., 2020. "Reduced grid operating costs and renewable energy curtailment with electric vehicle charge management," Energy Policy, Elsevier, vol. 136(C).
    2. Schill, Wolf-Peter & Gerbaulet, Clemens, 2015. "Power System Impacts of Electric Vehicles in Germany: Charging with Coal or Renewables," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 156, pages 185-196.
    3. Weis, Allison & Jaramillo, Paulina & Michalek, Jeremy, 2014. "Estimating the potential of controlled plug-in hybrid electric vehicle charging to reduce operational and capacity expansion costs for electric power systems with high wind penetration," Applied Energy, Elsevier, vol. 115(C), pages 190-204.
    4. Jiang, Qinhua & Zhang, Ning & Yueshuai He, Brian & Lee, Changju & Ma, Jiaqi, 2024. "Large-scale public charging demand prediction with a scenario- and activity-based approach," Transportation Research Part A: Policy and Practice, Elsevier, vol. 179(C).
    5. Zhao, Yang & Noori, Mehdi & Tatari, Omer, 2016. "Vehicle to Grid regulation services of electric delivery trucks: Economic and environmental benefit analysis," Applied Energy, Elsevier, vol. 170(C), pages 161-175.
    6. Mokhele Edmond Moeletsi, 2021. "Future Policy and Technological Advancement Recommendations for Enhanced Adoption of Electric Vehicles in South Africa: A Survey and Review," Sustainability, MDPI, vol. 13(22), pages 1-10, November.
    7. Ramos-Real, Francisco J. & Ramírez-Díaz, Alfredo & Marrero, Gustavo A. & Perez, Yannick, 2018. "Willingness to pay for electric vehicles in island regions: The case of Tenerife (Canary Islands)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 98(C), pages 140-149.
    8. Youssef Amry & Elhoussin Elbouchikhi & Franck Le Gall & Mounir Ghogho & Soumia El Hani, 2022. "Electric Vehicle Traction Drives and Charging Station Power Electronics: Current Status and Challenges," Energies, MDPI, vol. 15(16), pages 1-30, August.
    9. Saxena, Samveg & Gopal, Anand & Phadke, Amol, 2014. "Electrical consumption of two-, three- and four-wheel light-duty electric vehicles in India," Applied Energy, Elsevier, vol. 115(C), pages 582-590.
    10. Hu, Dingding & Zhou, Kaile & Li, Fangyi & Ma, Dawei, 2022. "Electric vehicle user classification and value discovery based on charging big data," Energy, Elsevier, vol. 249(C).
    11. Dowds, Jonathan & Howerter, Sarah & Hines, Paul & Aultman-Hall, Lisa, 2024. "Integrated Modeling of Electric Vehicle Energy Demand and Regional Electricity Generation," Institute of Transportation Studies, Working Paper Series qt9nv8z4kc, Institute of Transportation Studies, UC Davis.
    12. Murphy, M.D. & O’Mahony, M.J. & Upton, J., 2015. "Comparison of control systems for the optimisation of ice storage in a dynamic real time electricity pricing environment," Applied Energy, Elsevier, vol. 149(C), pages 392-403.
    13. Mariusz Niekurzak & Jerzy Mikulik, 2021. "Modeling of Energy Consumption and Reduction of Pollutant Emissions in a Walking Beam Furnace Using the Expert Method—Case Study," Energies, MDPI, vol. 14(23), pages 1-22, December.
    14. Shi You & Junjie Hu & Charalampos Ziras, 2016. "An Overview of Modeling Approaches Applied to Aggregation-Based Fleet Management and Integration of Plug-in Electric Vehicles †," Energies, MDPI, vol. 9(11), pages 1-18, November.
    15. Kuang, Yanqing & Chen, Yang & Hu, Mengqi & Yang, Dong, 2017. "Influence analysis of driver behavior and building category on economic performance of electric vehicle to grid and building integration," Applied Energy, Elsevier, vol. 207(C), pages 427-437.
    16. Asadi, Amin & Nurre Pinkley, Sarah, 2021. "A stochastic scheduling, allocation, and inventory replenishment problem for battery swap stations," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 146(C).
    17. García-Triviño, Pablo & Torreglosa, Juan P. & Fernández-Ramírez, Luis M. & Jurado, Francisco, 2016. "Control and operation of power sources in a medium-voltage direct-current microgrid for an electric vehicle fast charging station with a photovoltaic and a battery energy storage system," Energy, Elsevier, vol. 115(P1), pages 38-48.
    18. Dai, Ziyi & Liu, Haobing & Rodgers, Michael O. & Guensler, Randall, 2022. "Electric vehicle market potential and associated energy and emissions reduction benefits," Applied Energy, Elsevier, vol. 322(C).
    19. Schill, Wolf-Peter, 2011. "Electric Vehicles in Imperfect Electricity Markets: The case of Germany," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 39(10), pages 6178-6189.
    20. Dominik Franjo Dominković & Greg Stark & Bri-Mathias Hodge & Allan Schrøder Pedersen, 2018. "Integrated Energy Planning with a High Share of Variable Renewable Energy Sources for a Caribbean Island," Energies, MDPI, vol. 11(9), pages 1-15, August.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:14:y:2021:i:16:p:5037-:d:615775. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.