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IoT-based monitoring and control of substations and smart grids with renewables and electric vehicles integration

Author

Listed:
  • Ullah, Zia
  • Rehman, Anis Ur
  • Wang, Shaorong
  • Hasanien, Hany M.
  • Luo, Peng
  • Elkadeem, Mohamed R.
  • Abido, Mohammad A.

Abstract

The integrated renewable energy resources (RERs) based smart grid in the power distribution network (PDN) has financial and ecological benefits. However, the emergence of RER-based microgrids and substations without real-time monitoring of their power parameters leads to various challenges in the PDN, such as suboptimal resource allocation, poor load management, grid instability, and lack of real-time decision-making capabilities. To mitigate these challenges, increase the system's visibility, and make efficient decisions, intelligent monitoring and control system is required for both smart grid and power substation. This proposed study develops IoT-based monitoring and control of power substations and associated distributed smart grids to make effective decisions of integration/segregation into the PDN. The proposed IoT-based integration/segregation of smart grids and load management can mitigate the stated challenges effectively. Using the HOMER Grid®, the research also investigates the annualized power production pattern of smart grids and the power consumption pattern of integrated loads to enable proactive decisions about energy management. The proposed study implements IoT technology for power parameters monitoring of substations and smart grids for their effective use, as it considers four types of load management, including industrial, domestic, commercial, and electric vehicles, with the aid of IoT technology to avoid power fluctuations and contingencies. Effective load management has been adopted based on annualized energy consumption, load patterns and real-time monitoring, and active decisions making. The results highlight that the proposed IoT-based approach helps advance smart grid integration into the PDN and enhance energy load management, consequently reducing energy costs and suppressing carbon emissions. The validation of the proposed model is verified by the constructed prototype, where the achieved real-time monitoring and control of power substations and smart grids into PDN is performed to make effective decisions related to energy and load management. Moreover, it effectively allows power distribution companies to manage loads during high demand or crises and enhances grid stability and energy efficiency.

Suggested Citation

  • Ullah, Zia & Rehman, Anis Ur & Wang, Shaorong & Hasanien, Hany M. & Luo, Peng & Elkadeem, Mohamed R. & Abido, Mohammad A., 2023. "IoT-based monitoring and control of substations and smart grids with renewables and electric vehicles integration," Energy, Elsevier, vol. 282(C).
    • Handle: RePEc:eee:energy:v:282:y:2023:i:c:s0360544223023186
    DOI: 10.1016/j.energy.2023.128924
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    References listed on IDEAS

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    1. Ullah, Zia & Wang, Shaorong & Wu, Guan & Hasanien, Hany M. & Rehman, Anis Ur & Turky, Rania A. & Elkadeem, Mohamed R., 2023. "Optimal scheduling and techno-economic analysis of electric vehicles by implementing solar-based grid-tied charging station," Energy, Elsevier, vol. 267(C).
    2. Rehman, Anis Ur & Ullah, Zia & Shafiq, Aqib & Hasanien, Hany M. & Luo, Peng & Badshah, Fazal, 2023. "Load management, energy economics, and environmental protection nexus considering PV-based EV charging stations," Energy, Elsevier, vol. 281(C).
    3. Ullah, Zia & Elkadeem, M.R. & Kotb, Kotb M. & Taha, Ibrahim B.M. & Wang, Shaorong, 2021. "Multi-criteria decision-making model for optimal planning of on/off grid hybrid solar, wind, hydro, biomass clean electricity supply," Renewable Energy, Elsevier, vol. 179(C), pages 885-910.
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