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Model Predictive Control for Power Networks

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Encyclopedia of Systems and Control

Abstract

Large-scale power systems rely on a hierarchical control structure to operate reliably through a wide variety of disturbances. As operating strategies adapt to incorporate emerging technologies and distributed resources such as renewable generation and storage, model predictive control (MPC) offers a systematic approach to coordinating diverse controls and providing decision support. MPC uses an approximate system model to determine an optimal control sequence over a finite horizon. The first instance of that control sequence is implemented on the system, the resulting system response is measured, and the process repeats. Power system applications of MPC include prevention of voltage instability, corrective control, and secondary frequency control.

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Author information

Authors and Affiliations

  1. University of Michigan, Ann Arbor, MI, USA

    Ian A. Hiskens

  2. Electrical and Electronic Engineering, University of Melbourne, Melbourne, VIC, Australia

    Maria Vrakopoulou

Authors
  1. Ian A. Hiskens
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  2. Maria Vrakopoulou
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Corresponding author

Correspondence to Ian A. Hiskens .

Editor information

Editors and Affiliations

  1. College of Engineering, Boston University, Boston, MA, USA

    John Baillieul

  2. Technological Leadership Institute, University of Minnesota, Minneapolis, MA, USA

    Tariq Samad

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Hiskens, I.A., Vrakopoulou, M. (2021). Model Predictive Control for Power Networks. In: Baillieul, J., Samad, T. (eds) Encyclopedia of Systems and Control. Springer, Cham. https://doi.org/10.1007/978-3-030-44184-5_100126

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