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Title:Prevention of Emergency Voltage Collapses in Electric Power Networks using Hybrid Predictive Control
Authors:S. Leirens, R.R. Negenborn

Book title:Intelligent Infrastructures

Abstract:The reliable operation of electricity transport and distribution networks plays a crucial role in modern societies. However, too often, when a fault occurs in electricity networks, such as a transmission line drop, loss of generation, or any other important failure, voltages start to decay, potentially leading to complete blackouts with dramatic consequences. Thus, techniques are required that improve the power grid operation in case of emergencies. In this chapter, to achieve this aim, an approach is presented that uses an adaptive predictive control scheme. Electric power transmission networks are hereby considered as large-scale interconnected dynamical systems. First, voltage instability issues are illustrated on a 9-bus benchmark system. Then, the details of the proposed approach are discussed: the power network modeling and the construction of a hybrid prediction model (i.e., including both continuous and discrete dynamics), and the formulation and the resolution of the adaptive predictive control problem. In simulation studies on the 9-bus benchmark system the performance of the proposed approach is illustrated in various emergency voltage control cases.

Reference:S. Leirens, R.R. Negenborn. Prevention of Emergency Voltage Collapses in Electric Power Networks using Hybrid Predictive Control. In Intelligent Infrastructures (R.R. Negenborn, Z. Lukszo, H. Hellendoorn, eds.), Springer, Dordrecht, The Netherlands, pp. 55-88, 2010.

BibTeX:
@incollection{Leirens:10,
  author =    {S. Leirens and R. R. Negenborn},
  title =     {Prevention of Emergency Voltage Collapses in Electric Power Networks
               using Hybrid Predictive Control},
  booktitle = {Intelligent Infrastructures},
  editor =    {R. R. Negenborn and Z. Lukszo and H. Hellendoorn},
  publisher = {Springer},
  address =   {Dordrecht, The Netherlands},
  pages =     {55--88},
  year =      {2010}
}
Download:Corresponding technical report


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