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Decomposed Iterative Optimal Power Flow with Automatic Regionalization

Author

Listed:
  • Xinhu Zheng

    (Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN 55455, USA)

  • Dongliang Duan

    (Department of Electrical and Computer Engineering, University of Wyoming, Laramie, WY 82071, USA)

  • Liuqing Yang

    (Department of Electrical and Computer Engineering, University of Minnesota, Minneapolis, MN 55455, USA)

  • Haonan Wang

    (Department of Statistics, Colorado State University, Fort Collins, CO 80523, USA)

Abstract

The optimal power flow (OPF) problem plays an important role in power system operation and control. The problem is nonconvex and NP-hard, hence global optimality is not guaranteed and the complexity grows exponentially with the size of the system. Therefore, centralized optimization techniques are not suitable for large-scale systems and an efficient decomposed implementation of OPF is highly demanded. In this paper, we propose a novel and efficient method to decompose the entire system into multiple sub-systems based on automatic regionalization and acquire the OPF solution across sub-systems via a modified MATPOWER solver. The proposed method is implemented in a modified solver and tested on several IEEE Power System Test Cases. The performance is shown to be more appealing compared with the original solver.

Suggested Citation

  • Xinhu Zheng & Dongliang Duan & Liuqing Yang & Haonan Wang, 2020. "Decomposed Iterative Optimal Power Flow with Automatic Regionalization," Energies, MDPI, vol. 13(18), pages 1-22, September.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:18:p:4987-:d:417567
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    References listed on IDEAS

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    1. Francisco Nogales & Francisco Prieto & Antonio Conejo, 2003. "A Decomposition Methodology Applied to the Multi-Area Optimal Power Flow Problem," Annals of Operations Research, Springer, vol. 120(1), pages 99-116, April.
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