Nonlinear predictive control scheme with immune optimization for voltage security control of power system

Yanjun Li, David J. Hill, Tiejun Wu

Research output: Contribution to journalArticleResearchpeer-review

4 Citations (Scopus)

Abstract

An immune algorithm based nonlinear predictive control scheme is proposed to solve power system voltage security control problems. A nonlinear differential-algebraic model is used to predict system behavior. A gradational targeting method is developed to decompose global horizon control targets into sub-objectives in receding prediction intervals via Pareto-type weighting functions. A novel immune algorithm is presented, using a multiple gene chain structure of antibodies to represent the solution candidates of the complicated optimization problem. A pattern recognition technique is employed to extract gene patterns of better antibodies. Similar antigen patterns are identified via learning, and memorized to create a better initial guess of solutions in order to accelerate the convergence of the optimal searching procedure. System performance comparative results are reported based on the emergency voltage control of a six-bus example power system. The results indicate the promising application potential of the method.

Original languageEnglish
Pages (from-to)25-31
Number of pages7
JournalDianli Xitong Zidonghua/Automation of Electric Power Systems
Volume28
Issue number16
Publication statusPublished - 25 Aug 2004
Externally publishedYes

Keywords

  • Immune algorithm
  • Model predictive control
  • Nonlinear system
  • Power system control
  • Voltage security control

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