Digital modeling and control of multiple time-delayed distributed power grid

V. V. Joshi, L. B. Xie, J. J. Park, L. S. Shieh, Y. H. Chen, K. Grigoriadis, J. S.H. Tsai

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)

Abstract

Distributed power grid (DPG) control systems are so highly interconnected that the effects of local disturbances as well as transmission time delays can be amplified as they propagate through a complex network of transmission lines. These effects deteriorate control performance and could possibly destabilize the overall system. In this paper, a new approximated discretization method and digital design for DPG control systems with multiple state, input and output delays as well as a generalized bilinear transformation method are presented. Based on a procedure for the generation of impulse response data, the multiple fractional/integer time-delayed continuous-time system is transformed to a discrete-time model with multiple integer time delays. To implement the digital modeling, the singular value decomposition (SVD) of a Hankel matrix together with an energy loss level is employed to obtain an extended discrete-time state space model. Then, the extended discrete-time state space model of the DPG control system is reformulated as an integer time-delayed discrete-time system by computing its observable canonical form. The proposed method can closely approximate the step response of the original continuous time-delayed DPG control system by choosing various energy loss levels. For completeness, an optimal digital controller design for the DPG control system and a generalized bilinear transformation method with a tunable parameter are also provided, which can re-transform the integer time-delayed discrete-time model to its continuous-time model. Illustrative examples are given to demonstrate the effectiveness of the developed method.

Original languageEnglish
Pages (from-to)4118-4134
Number of pages17
JournalApplied Mathematical Modelling
Volume36
Issue number9
DOIs
Publication statusPublished - 2012 Sep

All Science Journal Classification (ASJC) codes

  • Modelling and Simulation
  • Applied Mathematics

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