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Parallel Power Flow Computation Trends and Applications: A Review Focusing on GPU

Author

Listed:
  • Dong-Hee Yoon

    (Department of Railway, Kyungil University, Gyeongsan 38428, Korea)

  • Youngsun Han

    (Department of Computer Engineering, Pukyong National University, Pusan 48513, Korea)

Abstract

A power flow study aims to analyze a power system by obtaining the voltage and phase angle of buses inside the power system. Power flow computation basically uses a numerical method to solve a nonlinear system, which takes a certain amount of time because it may take many iterations to find the final solution. In addition, as the size and complexity of power systems increase, further computational power is required for power system study. Therefore, there have been many attempts to conduct power flow computation with large amounts of data using parallel computing to reduce the computation time. Furthermore, with recent system developments, attempts have been made to increase the speed of parallel computing using graphics processing units (GPU). In this review paper, we summarize issues related to parallel processing in power flow studies and analyze research into the performance of fast power flow computations using parallel computing methods with GPU.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:9:p:2147-:d:352730
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    References listed on IDEAS

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    1. 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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    Cited by:

    1. 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.
    2. Shadi G. Alawneh & Lei Zeng & Seyed Ali Arefifar, 2023. "A Review of High-Performance Computing Methods for Power Flow Analysis," Mathematics, MDPI, vol. 11(11), pages 1-20, May.

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