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A Review of High-Performance Computing Methods for Power Flow Analysis

Author

Listed:
  • Shadi G. Alawneh

    (Electrical & Computer Engineering, Oakland University, 115 Library Drive, Rochester, MI 48309, USA)

  • Lei Zeng

    (Electrical & Computer Engineering, Oakland University, 115 Library Drive, Rochester, MI 48309, USA)

  • Seyed Ali Arefifar

    (Electrical & Computer Engineering, Oakland University, 115 Library Drive, Rochester, MI 48309, USA)

Abstract

Power flow analysis is critical for power systems due to the development of multiple energy supplies. For safety, stability, and real-time response in grid operation, grid planning, and analysis of power systems, it requires designing high-performance computing methods, accelerating power flow calculation, obtaining the voltage magnitude and phase angle of buses inside the power system, and coping with the increasingly complex large-scale power system. This paper provides an overview of the available parallel methods to fix the issues. Specifically, these methods can be classified into three categories from a hardware perspective: multi-cores, hybrid CPU-GPU architecture, and FPGA. In addition, from the perspective of numerical computation, the power flow algorithm is generally classified into iterative and direct methods. This review paper introduces models of power flow and hardware computing architectures and then compares their performance in parallel power flow calculations depending on parallel numerical methods on different computing platforms. Furthermore, this paper analyzes the challenges and pros and cons of these methods and provides guidance on how to exploit the parallelism of future power flow applications.

Suggested Citation

  • 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.
  • Handle: RePEc:gam:jmathe:v:11:y:2023:i:11:p:2461-:d:1156762
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    References listed on IDEAS

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    1. 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.
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