• DocumentCode
    2016531
  • Title

    Decentralized sliding mode control for load frequency problem in three - Area power systems

  • Author

    Klimontowicz, Maksmilian Lukasz ; Al-Hinai, A. ; Peng, Jimmy Chih-Hsien

  • Author_Institution
    IEnergy Center, Masdar Inst. of Sci. & Technol., Abu Dhabi, United Arab Emirates
  • fYear
    2015
  • fDate
    1-4 Feb. 2015
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Frequency issues exist in generation, transmission and load sectors. From the load point of view, frequency sensitive devices like engines or clocks require quasi constant frequency to work properly. Whereas in the transmission system, power losses like hysteresis and eddy currents in transformers are frequency dependent. At the generation side, it is essential to prevent rotor angle from exceeding maximal threshold value; thus avoiding generators becoming out-of-step. Many techniques and model predictive control were published to solve the load frequency control (LFC) problem. Moreover, current optimization methods and high performance computers allow engineers to optimize complicated linear and nonlinear problems within reasonable time. Among optimization techniques, genetic algorithm (GA) optimization is utilized by control designers. It is also supported by Optimtool - MATLAB toolbox. This paper presented a comparative study of conventional and sliding mode control (SMC) designs for LFC. Optimized conventional controllers (PI and PID) were applied into a three - area system. Generated responses from conventional controllers were compared to responses from systems equipped with decentralized SMC.
  • Keywords
    frequency control; genetic algorithms; load regulation; power system control; rotors; variable structure systems; MATLAB toolbox; Optimtool; clocks; eddy currents; engines; frequency sensitive devices; genetic algorithm; hysteresis; load frequency control; power losses; power systems; rotor angle; sliding mode control; transformers; transmission system; Control systems; Frequency control; Genetic algorithms; Optimization; Power system stability; Time-frequency analysis; LFC; genetic algorithm; power system; sliding mode control;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    GCC Conference and Exhibition (GCCCE), 2015 IEEE 8th
  • Conference_Location
    Muscat
  • Type

    conf

  • DOI
    10.1109/IEEEGCC.2015.7060100
  • Filename
    7060100