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Monte Carlo analysis of Plug-in Hybrid Vehicles and Distributed Energy Resource growth with residential energy storage in Michigan

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  • Jung, Jaesung
  • Cho, Yongju
  • Cheng, Danling
  • Onen, Ahmet
  • Arghandeh, Reza
  • Dilek, Murat
  • Broadwater, Robert P.

Abstract

This paper considers system effects due to the addition of Plug-in Hybrid Vehicles (PHEV) and Distributed Energy Resource (DER) generation. The DER and PHEV are considered with energy storage technology applied to the residential distribution system load. Two future year scenarios are considered, 2020 and 2030. The models used are of real distribution circuits located near Detroit, Michigan, and every customer load on the circuit and type of customer are modeled. Monte Carlo simulations are used to randomly select customers that receive PHEV, DER, and/or storage systems. The Monte Carlo simulations provide not only the expected average result, but also its uncertainty. The adoption scenarios are investigated for both summer and winter loading conditions.

Suggested Citation

  • Jung, Jaesung & Cho, Yongju & Cheng, Danling & Onen, Ahmet & Arghandeh, Reza & Dilek, Murat & Broadwater, Robert P., 2013. "Monte Carlo analysis of Plug-in Hybrid Vehicles and Distributed Energy Resource growth with residential energy storage in Michigan," Applied Energy, Elsevier, vol. 108(C), pages 218-235.
    • Handle: RePEc:eee:appene:v:108:y:2013:i:c:p:218-235
    DOI: 10.1016/j.apenergy.2013.03.033
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    Cited by:

    1. Jung, Jaesung & Onen, Ahmet & Russell, Kevin & Broadwater, Robert P. & Steffel, Steve & Dinkel, Alex, 2015. "Configurable, Hierarchical, Model-based, Scheduling Control with photovoltaic generators in power distribution circuits," Renewable Energy, Elsevier, vol. 76(C), pages 318-329.
    2. Jung, Jaesung & Onen, Ahmet & Arghandeh, Reza & Broadwater, Robert P., 2014. "Coordinated control of automated devices and photovoltaic generators for voltage rise mitigation in power distribution circuits," Renewable Energy, Elsevier, vol. 66(C), pages 532-540.
    3. Ahmet Onen, 2016. "Energy Saving of Conservation Voltage Reduction Based on Load-Voltage Dependency," Sustainability, MDPI, vol. 8(8), pages 1-11, August.
    4. Xu, Jing & Wang, Xiaoying & Gu, Yujiong & Ma, Suxia, 2023. "A data-based day-ahead scheduling optimization approach for regional integrated energy systems with varying operating conditions," Energy, Elsevier, vol. 283(C).
    5. Jung, Jaesung & Onen, Ahmet & Russell, Kevin & Broadwater, Robert P., 2015. "Local steady-state and quasi steady-state impact studies of high photovoltaic generation penetration in power distribution circuits," Renewable and Sustainable Energy Reviews, Elsevier, vol. 43(C), pages 569-583.
    6. Jung, Jaesung & Villaran, Michael, 2017. "Optimal planning and design of hybrid renewable energy systems for microgrids," Renewable and Sustainable Energy Reviews, Elsevier, vol. 75(C), pages 180-191.
    7. Moreno, Rodrigo & Moreira, Roberto & Strbac, Goran, 2015. "A MILP model for optimising multi-service portfolios of distributed energy storage," Applied Energy, Elsevier, vol. 137(C), pages 554-566.
    8. Li, Ke & Yang, Fan & Wang, Lupan & Yan, Yi & Wang, Haiyang & Zhang, Chenghui, 2022. "A scenario-based two-stage stochastic optimization approach for multi-energy microgrids," Applied Energy, Elsevier, vol. 322(C).
    9. Arghandeh, Reza & Woyak, Jeremy & Onen, Ahmet & Jung, Jaesung & Broadwater, Robert P., 2014. "Economic optimal operation of Community Energy Storage systems in competitive energy markets," Applied Energy, Elsevier, vol. 135(C), pages 71-80.

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