Hierarchical Optimal Power Flow with Improved Gradient Evaluation

Heng Liang, Xinyang Zhou, Changhong Zhao

Research output: Contribution to conferencePaperpeer-review


Existing algorithms to solve alternating-current optimal power flow (AC-OPF) often exploit linear approximations to simplify system models and accelerate computations. In this paper, we improve a recent hierarchical OPF algorithm, which rested on primal-dual gradients evaluated in a linearized distribution power flow model. Specifically, we identify a risk of voltage violation arising from the model linearization, and propose a more accurate gradient evaluation method to eliminate that risk. We further develop a hierarchical primal-dual algorithm to solve OPF based on the proposed gradient evaluation method. Numerical results on IEEE networks show that our algorithm can enhance voltage safety with satisfactory computational efficiency.

Original languageAmerican English
Number of pages6
StatePublished - 2022
Event2022 American Control Conference, ACC 2022 - Atlanta, United States
Duration: 8 Jun 202210 Jun 2022


Conference2022 American Control Conference, ACC 2022
Country/TerritoryUnited States

Bibliographical note

Publisher Copyright:
© 2022 American Automatic Control Council.

NREL Publication Number

  • NREL/CP-5D00-84186


  • distributed algorithm
  • distritbution system
  • hierarchical algorithm
  • optimal power flow


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