• DocumentCode
    3045628
  • Title

    Improving power system stability and economy by coordination of controller settings and power constraints

  • Author

    Brook, D.P. ; Dunn, R.W.

  • Author_Institution
    Bath Univ., UK
  • Volume
    2
  • fYear
    2001
  • fDate
    2001
  • Firstpage
    499
  • Abstract
    It is a well known phenomena that some combinations of load and generation patterns can lead to system stability, and hence system security issues. This type of problem is generally alleviated by altering the generation pattern, since the utility has no, or only limited, control of the load pattern. In deregulated markets, this necessary operational function can incur costs, which is undesirable for the system operators. An alternative to changing generation pattern by imposing real power constraints is to attempt to modify the dynamic performance of the system to improve stability at its given (most economic or ideal) load and generation configuration. This paper details such a method of optimisation based on a genetic algorithm (GA) to manipulate system control plant parameters. The objective function used is based on time domain simulation of the system in order to retain full modelling detail, and the controllable parameters are based on existing controllers found within the UK system. In cases where adequate stability cannot be attained by controller parameter optimisation alone, a hybrid solution is found with a minimal level of real power constraint
  • Keywords
    control system analysis; control system synthesis; genetic algorithms; optimal control; power system control; power system economics; power system stability; UK; control design; control simulation; controllable parameters; controller settings coordination; deregulated markets; dynamic performance; electric utility; generation pattern; genetic algorithm; load pattern; objective function; power constraints coordination; power system economy improvement; power system stability improvement; time domain simulation; Control systems; Cost function; Genetic algorithms; Optimization methods; Power generation; Power generation economics; Power system economics; Power system modeling; Power system security; Power system stability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Power Engineering Society Winter Meeting, 2001. IEEE
  • Conference_Location
    Columbus, OH
  • Print_ISBN
    0-7803-6672-7
  • Type

    conf

  • DOI
    10.1109/PESW.2001.916898
  • Filename
    916898