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Intelligent Integration of Renewable Energy Resources Review: Generation and Grid Level Opportunities and Challenges

Author

Listed:
  • Aras Ghafoor

    (Department of Electrical and Electronic Engineering, School of Engineering, The University of Manchester, Manchester M13 9PL, UK)

  • Jamal Aldahmashi

    (School of Engineering, Lancaster University, Lancaster LA1 4YW, UK
    Department of Electrical Engineering, College of Engineering, Northern Border University, Arar 73213, Saudi Arabia)

  • Judith Apsley

    (Department of Electrical and Electronic Engineering, School of Engineering, The University of Manchester, Manchester M13 9PL, UK)

  • Siniša Djurović

    (Department of Electrical and Electronic Engineering, School of Engineering, The University of Manchester, Manchester M13 9PL, UK)

  • Xiandong Ma

    (School of Engineering, Lancaster University, Lancaster LA1 4YW, UK)

  • Mohamed Benbouzid

    (Institut de Recherche Dupuy de Lôme (UMR CNRS 6027), University of Brest, 29238 Brest, France)

Abstract

This paper reviews renewable energy integration with the electrical power grid through the use of advanced solutions at the device and system level, using smart operation with better utilisation of design margins and power flow optimisation with machine learning. This paper first highlights the significance of credible temperature measurements for devices with advanced power flow management, particularly the use of advanced fibre optic sensing technology. The potential to expand renewable energy generation capacity, particularly of existing wind farms, by exploiting thermal design margins is then explored. Dynamic and adaptive optimal power flow models are subsequently reviewed for optimisation of resource utilisation and minimisation of operational risks. This paper suggests that system-level automation of these processes could improve power capacity exploitation and network stability economically and environmentally. Further research is needed to achieve these goals.

Suggested Citation

  • Aras Ghafoor & Jamal Aldahmashi & Judith Apsley & Siniša Djurović & Xiandong Ma & Mohamed Benbouzid, 2024. "Intelligent Integration of Renewable Energy Resources Review: Generation and Grid Level Opportunities and Challenges," Energies, MDPI, vol. 17(17), pages 1-29, September.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:17:p:4399-:d:1469933
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    References listed on IDEAS

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    1. Soonwoo Lee & Hui-Myoung Oh & Jung Min Pak, 2024. "Event-Triggered Transmission of Sensor Measurements Using Twin Hybrid Filters for Renewable Energy Resource Management Systems," Energies, MDPI, vol. 17(22), pages 1-18, November.

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