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

Research output: Contribution to Journal/Magazine › Review article › peer-review

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Intelligent Integration of Renewable Energy Resources Review: Generation and Grid Level Opportunities and Challenges. / Ghafoor, Aras ; Aldahmashi, Jamal; Apsley, Judith et al.
In: Energies, Vol. 17, No. 17, 4399, 02.09.2024.

Research output: Contribution to Journal/Magazine › Review article › peer-review

Harvard

Ghafoor, A, Aldahmashi, J, Apsley, J, Durovic, S, Ma, X & Benbouzid, M 2024, 'Intelligent Integration of Renewable Energy Resources Review: Generation and Grid Level Opportunities and Challenges', Energies, vol. 17, no. 17, 4399. https://doi.org/10.3390/en17174399

APA

Ghafoor, A., Aldahmashi, J., Apsley, J., Durovic, S., Ma, X., & Benbouzid, M. (2024). Intelligent Integration of Renewable Energy Resources Review: Generation and Grid Level Opportunities and Challenges. Energies, 17(17), Article 4399. https://doi.org/10.3390/en17174399

Vancouver

Ghafoor A, Aldahmashi J, Apsley J, Durovic S, Ma X, Benbouzid M. Intelligent Integration of Renewable Energy Resources Review: Generation and Grid Level Opportunities and Challenges. Energies. 2024 Sept 2;17(17):4399. doi: 10.3390/en17174399

Author

Ghafoor, Aras ; Aldahmashi, Jamal ; Apsley, Judith et al. / Intelligent Integration of Renewable Energy Resources Review : Generation and Grid Level Opportunities and Challenges. In: Energies. 2024 ; Vol. 17, No. 17.

Bibtex

@article{d355ed1de14849bca1fbb72a37400aeb,
title = "Intelligent Integration of Renewable Energy Resources Review: Generation and Grid Level Opportunities and Challenges",
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.",
keywords = "Renewable integration, Advanced solutions, Thermal margin, Fibre optic sensor, Power flow, Optimisation, Machine learning",
author = "Aras Ghafoor and Jamal Aldahmashi and Judith Apsley and Sinisa Durovic and Xiandong Ma and Mohamed Benbouzid",
year = "2024",
month = sep,
day = "2",
doi = "10.3390/en17174399",
language = "English",
volume = "17",
journal = "Energies",
issn = "1996-1073",
publisher = "Multidisciplinary Digital Publishing Institute (MDPI)",
number = "17",

}

RIS

TY - JOUR

T1 - Intelligent Integration of Renewable Energy Resources Review

T2 - Generation and Grid Level Opportunities and Challenges

AU - Ghafoor, Aras

AU - Aldahmashi, Jamal

AU - Apsley, Judith

AU - Durovic, Sinisa

AU - Ma, Xiandong

AU - Benbouzid, Mohamed

PY - 2024/9/2

Y1 - 2024/9/2

N2 - 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.

AB - 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.

KW - Renewable integration

KW - Advanced solutions

KW - Thermal margin

KW - Fibre optic sensor

KW - Power flow

KW - Optimisation

KW - Machine learning

U2 - 10.3390/en17174399

DO - 10.3390/en17174399

M3 - Review article

VL - 17

JO - Energies

JF - Energies

SN - 1996-1073

IS - 17

M1 - 4399

ER -