Frequency Recovery in Power Grids Using High-Performance Computing

Vishwas Rao, Anirudh Subramanyam, Michael Schanen, Youngdae Kim, Ignas Satkauskas, Mihai Anitescu

Research output: Contribution to conferencePaperpeer-review


Maintaining electric power system stability is paramount, especially in extreme contingencies involving unexpected outages of multiple generators or transmission lines that are typical during severe weather events. Such outages often lead to large supply-demand mismatches followed by subsequent system frequency deviations from their nominal value. The extent of frequency deviations is an important metric of system resilience, and its timely mitigation is a central goal of power system operation and control. This paper develops a novel nonlinear model predictive control (NMPC) method to minimize frequency deviations when the grid is affected by an unforeseen loss of multiple components. Our method is based on a novel multi-period alternating current optimal power flow (ACOPF) formulation that accurately models both nonlinear electric power flow physics and the primary and secondary frequency response of generator control mechanisms. We develop a distributed parallel Julia package for solving the large-scale nonlinear optimization problems that result from our NMPC method and thereby address realistic test instances on existing high-performance computing architectures. Our method demonstrates superior performance in terms of frequency recovery over existing industry practices, where generator levels are set based on the solution of single-period classical ACOPF models.

Original languageAmerican English
Number of pages6
StatePublished - 29 Aug 2022
Event51st International Conference on Parallel Processing, ICPP 2022 - Virtual, Online, France
Duration: 29 Aug 20221 Sep 2022


Conference51st International Conference on Parallel Processing, ICPP 2022
CityVirtual, Online

Bibliographical note

Publisher Copyright:
© 2022 ACM.

NREL Publication Number

  • NREL/CP-2C00-85374

Other Report Number

  • Article No. 20


  • nonlinear model predictive control
  • optimal power flow
  • parallel computing
  • power systems planning


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