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Assessment and Mitigation of Electric Vehicle Charging Demand Impact to Transformer Aging for an Apartment Complex

Author

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  • Shin-Ki Hong

    (School of Electrical Engineering, Chungbuk National University, Cheongju 28644, Korea)

  • Sung Gu Lee

    (Department of Electrical Engineering, Dong-A University, Busan 49315, Korea)

  • Myungchin Kim

    (School of Electrical Engineering, Chungbuk National University, Cheongju 28644, Korea)

Abstract

Due to the increasing use of Electric Vehicles (EVs), the effect of the EV charging power demand on the reliability of the power system infrastructure needs to be addressed. In apartment complexes, which have emerged as a common residential type in metropolitan areas and highly populated districts, high charging demand could result in substantial stress to distribution networks. In this work, the effect of EV charging power demand in an apartment complex on the aging of the Distribution Transformer (DT) is studied. A methodology based on the stochastic characterization of vehicle usage profiles and user charging patterns is developed to obtain realistic EV charging demand profiles. Based on the modeled EV charging profile and the transformer thermal model, the effect of different EV penetration ratios on DT aging for an apartment complex in the Republic of Korea is studied. Results for an EV penetration ratio of up to 30% indicated that DT aging could be accelerated by up to 40%, compared to the case without EV charging. To mitigate this accelerated DT aging caused by EV charging, the effectiveness of two integration approaches of Photovoltaic (PV) sources was studied. Based on a case study that included a realistic PV generation profile, it was demonstrated that a significant contribution to DT reliability could be achieved via the operation of PV sources. A more apparent contribution of PV integration was observed with an energy storage installation at higher EV penetration ratios. At an EV penetration ratio of 30%, a maximum decrease of 41.8% in the loss-of-life probability of the DT was achieved. The effects of different PV integration approaches and power management details on DT aging were also studied. The results demonstrate that the EV charging demand could introduce a significant level of stress to DTs and that this impact can be effectively mitigated by installing PV sources. These observations are expected to contribute toward the effective planning of power system infrastructures that support the design of sustainable cities with the widespread use of EVs.

Suggested Citation

  • Shin-Ki Hong & Sung Gu Lee & Myungchin Kim, 2020. "Assessment and Mitigation of Electric Vehicle Charging Demand Impact to Transformer Aging for an Apartment Complex," Energies, MDPI, vol. 13(10), pages 1-23, May.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:10:p:2571-:d:360075
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    References listed on IDEAS

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    1. Nouha Mansouri & Abderezak Lashab & Dezso Sera & Josep M. Guerrero & Adnen Cherif, 2019. "Large Photovoltaic Power Plants Integration: A Review of Challenges and Solutions," Energies, MDPI, vol. 12(19), pages 1-16, October.
    2. Shokrzadeh, Shahab & Ribberink, Hajo & Rishmawi, Issa & Entchev, Evgueniy, 2017. "A simplified control algorithm for utilities to utilize plug-in electric vehicles to reduce distribution transformer overloading," Energy, Elsevier, vol. 133(C), pages 1121-1131.
    3. Godina, Radu & Rodrigues, Eduardo M.G. & Matias, João C.O. & Catalão, João P.S., 2016. "Smart electric vehicle charging scheduler for overloading prevention of an industry client power distribution transformer," Applied Energy, Elsevier, vol. 178(C), pages 29-42.
    4. Muhammad Azmat & Sebastian Kummer, 2020. "Potential applications of unmanned ground and aerial vehicles to mitigate challenges of transport and logistics-related critical success factors in the humanitarian supply chain," Asian Journal of Sustainability and Social Responsibility, Springer, vol. 5(1), pages 1-22, December.
    5. Ugochukwu Kenechi Elinwa & Mehrshad Radmehr & John Emmanuel Ogbeba, 2017. "Alternative Energy Solutions Using BIPV in Apartment Buildings of Developing Countries: A Case Study of North Cyprus," Sustainability, MDPI, vol. 9(8), pages 1-14, August.
    6. Dong-Shang Chang & Sheng-Hung Chen & Chia-Wei Hsu & Allen H. Hu & Gwo-Hshiung Tzeng, 2015. "Evaluation Framework for Alternative Fuel Vehicles: Sustainable Development Perspective," Sustainability, MDPI, vol. 7(9), pages 1-25, August.
    7. Arias, Mariz B. & Kim, Myungchin & Bae, Sungwoo, 2017. "Prediction of electric vehicle charging-power demand in realistic urban traffic networks," Applied Energy, Elsevier, vol. 195(C), pages 738-753.
    8. Sanchari Deb & Kari Tammi & Karuna Kalita & Pinakeshwar Mahanta, 2018. "Impact of Electric Vehicle Charging Station Load on Distribution Network," Energies, MDPI, vol. 11(1), pages 1-25, January.
    9. Aadil Latif & Wolfgang Gawlik & Peter Palensky, 2016. "Quantification and Mitigation of Unfairness in Active Power Curtailment of Rooftop Photovoltaic Systems Using Sensitivity Based Coordinated Control," Energies, MDPI, vol. 9(6), pages 1-16, June.
    10. Eunil Park & Ki Joon Kim & Sang Jib Kwon & Taeil Han & Wongi S. Na & Angel P. Del Pobil, 2017. "Economic Feasibility of Renewable Electricity Generation Systems for Local Government Office: Evaluation of the Jeju Special Self-Governing Province in South Korea," Sustainability, MDPI, vol. 9(1), pages 1-13, January.
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    Cited by:

    1. Ana Pavlićević & Saša Mujović, 2022. "Impact of Reactive Power from Public Electric Vehicle Stations on Transformer Aging and Active Energy Losses," Energies, MDPI, vol. 15(19), pages 1-24, September.
    2. Ahmad Almaghrebi & Fares Aljuheshi & Mostafa Rafaie & Kevin James & Mahmoud Alahmad, 2020. "Data-Driven Charging Demand Prediction at Public Charging Stations Using Supervised Machine Learning Regression Methods," Energies, MDPI, vol. 13(16), pages 1-21, August.
    3. Ahmad Almaghrebi & Kevin James & Fares Al Juheshi & Mahmoud Alahmad, 2024. "Insights into Household Electric Vehicle Charging Behavior: Analysis and Predictive Modeling," Energies, MDPI, vol. 17(4), pages 1-20, February.
    4. Mostafa Shibl & Loay Ismail & Ahmed Massoud, 2020. "Machine Learning-Based Management of Electric Vehicles Charging: Towards Highly-Dispersed Fast Chargers," Energies, MDPI, vol. 13(20), pages 1-24, October.

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