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High-Performance and Parallel Computing Techniques Review: Applications, Challenges and Potentials to Support Net-Zero Transition of Future Grids

Author

Listed:
  • Ahmed Al-Shafei

    (Department of Electrical and Software Engineering, University of Calgary, Calgary, AB T2N 1N4, Canada)

  • Hamidreza Zareipour

    (Department of Electrical and Software Engineering, University of Calgary, Calgary, AB T2N 1N4, Canada)

  • Yankai Cao

    (Department of Chemical and Biological Engineering, University of British Colombia, Vancouver, BC V6T 1Z3, Canada)

Abstract

The transition towards net-zero emissions is inevitable for humanity’s future. Of all the sectors, electrical energy systems emit the most emissions. This urgently requires the witnessed accelerating technological landscape to transition towards an emission-free smart grid. It involves massive integration of intermittent wind and solar-powered resources into future power grids. Additionally, new paradigms such as large-scale integration of distributed resources into the grid, proliferation of Internet of Things (IoT) technologies, and electrification of different sectors are envisioned as essential enablers for a net-zero future. However, these changes will lead to unprecedented size, complexity and data of the planning and operation problems of future grids. It is thus important to discuss and consider High Performance Computing (HPC), parallel computing, and cloud computing prospects in any future electrical energy studies. This article recounts the dawn of parallel computation in power system studies, providing a thorough history and paradigm background for the reader, leading to the most impactful recent contributions. The reviews are split into Central Processing Unit (CPU) based, Graphical Processing Unit (GPU) based, and Cloud-based studies and smart grid applications. The state-of-the-art is also discussed, highlighting the issue of standardization and the future of the field. The reviewed papers are predominantly focused on classical imperishable electrical system problems. This indicates the need for further research on parallel and HPC approaches applied to future smarter grid challenges, particularly to the integration of renewable energy into the smart grid.

Suggested Citation

  • Ahmed Al-Shafei & Hamidreza Zareipour & Yankai Cao, 2022. "High-Performance and Parallel Computing Techniques Review: Applications, Challenges and Potentials to Support Net-Zero Transition of Future Grids," Energies, MDPI, vol. 15(22), pages 1-58, November.
  • Handle: RePEc:gam:jeners:v:15:y:2022:i:22:p:8668-:d:977148
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    References listed on IDEAS

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    1. Kargarian, A. & Raoofat, M. & Mohammadi, M., 2011. "Reactive power market management considering voltage control area reserve and system security," Applied Energy, Elsevier, vol. 88(11), pages 3832-3840.
    2. Bai, Yang & Zhong, Haiwang & Xia, Qing & Kang, Chongqing & Xie, Le, 2015. "A decomposition method for network-constrained unit commitment with AC power flow constraints," Energy, Elsevier, vol. 88(C), pages 595-603.
    3. Kim, M.K. & Park, J.K. & Nam, Y.W., 2011. "Market-clearing for pricing system security based on voltage stability criteria," Energy, Elsevier, vol. 36(2), pages 1255-1264.
    4. Koltsaklis, Nikolaos E. & Dagoumas, Athanasios S., 2018. "State-of-the-art generation expansion planning: A review," Applied Energy, Elsevier, vol. 230(C), pages 563-589.
    5. Rajeev, T. & Ashok, S., 2015. "Dynamic load-shifting program based on a cloud computing framework to support the integration of renewable energy sources," Applied Energy, Elsevier, vol. 146(C), pages 141-149.
    6. Ajagekar, Akshay & You, Fengqi, 2019. "Quantum computing for energy systems optimization: Challenges and opportunities," Energy, Elsevier, vol. 179(C), pages 76-89.
    7. PAPAVASILIOU, Anthony & OREN, Shmuel & ROUNTREE, Barry, 2015. "Applying high performance computing to transmissions-consstrained stochastic unit commitment for renewable energy integration," LIDAM Reprints CORE 2679, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    8. Juan M. Morales & Antonio J. Conejo & Henrik Madsen & Pierre Pinson & Marco Zugno, 2014. "Integrating Renewables in Electricity Markets," International Series in Operations Research and Management Science, Springer, edition 127, number 978-1-4614-9411-9, September.
    9. Dong-Hee Yoon & Youngsun Han, 2020. "Parallel Power Flow Computation Trends and Applications: A Review Focusing on GPU," Energies, MDPI, vol. 13(9), pages 1-18, May.
    10. Monya Baker, 2016. "1,500 scientists lift the lid on reproducibility," Nature, Nature, vol. 533(7604), pages 452-454, May.
    11. Dong-Hee Yoon & Sang-Kyun Kang & Minseong Kim & Youngsun Han, 2018. "Exploiting Coarse-Grained Parallelism Using Cloud Computing in Massive Power Flow Computation," Energies, MDPI, vol. 11(9), pages 1-15, August.
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