Journal of Advanced Marine Engineering and Technology

The Korean Society of Marine Engineering (한국마린엔지니어링학회)
권호 표지

Application of Neural Network Precompensated PID Controller for Load Frequency Control of Power Systems

전력계통의 부하주파수 제어를 위한 신경회로망 전 보상 PID 제어기 적용

  • 김상효 (동아대학교 전기공학과)
  • Published : 1999.07.01
Download PDF
⟨ Previous Next ⟩

Abstract

In this paper we propose a neural network precompensated PID(NNP PID) controller for load frequency control of 2-area power system. While proportional integral derivative(PID) controllers are used in power system they have many problems because of high nonlinearities of the power system So a neural network-based precompensation scheme is adopted into a conventional PID controller to obtain a robust control to the nonlinearities. The applied neural network precompen-sator uses an error back-propagation learning algorithm having error and change of error as inputand considers the changing component of forward term of weighting factor for reducing of learning time. Simulation results show that the proposed control technique is superior to a conventional PID controller and an optimal controller in dynamic responses about load disturbances. The pro-posed technique can be easily implemented by adding a neural network precompensator to an existing PID controller.

Keywords

References

  1. IEE Proceedings v.140 no.1 Robust load-frequency controller design for power systems Y. Wang;R. Zhou;C. Wen
  2. Power System Stability and Control P. Kundur
  3. IEEE Trans. Power App. and Syst. v.Pas-80 no.4 The Megawatt-Frequency Control Problem : A New Approach Via Optimal Control Theory C. E. Fosha;O. I. Elgerd
  4. IEEE Trans. Power App. Syst. v.Pas-89 no.4 Optimum megawatt-frequency control of multiarea electric energy systems O. I. Elgerd;C. E. Fosha
  5. IEEE Trans. Power App. Syst. v.Pas-92 no.5 State adaptation in power systems control F. D. Galiana;H. Glavitsch
  6. IEEE TRans. Power App. Syst. v.Pas-102 no.6 Problems associated with generator load following in system operation R. P. Schulte;D. E. Badley
  7. 대한전기학회논문지 v.26 no.2 주파수 제어를 위한 비례 제어기구의 최적설계에 관한 연구 장세훈;임화영
  8. 대한전기학회논문지 v.38 no.2 최적선형 추적법에 의한 부하-주파수 제어 김훈기;곽노홍;문영현
  9. IEE Proc. -D v.138 no.2 Refinements of the Ziegler-Nichols tuning formula C. C. Hang;K. J. Astrom;W. K. Ho
  10. IEEE Proc. Neuromorphic Self-Tuning PID Controller S. Akhyar;S. Omatu
  11. IEEE Trans. Cont. Syst. Tech. v.20 no.2 Fuzzy Logic in Control Systems : Fuzzy Logic Controller-Part Ⅰ, Ⅱ C. C. LEE
  12. Neural Networks v.7 no.1 Application of Neural Networks to Load-Frequency Control in Power Systems F. Beaufays;Y. A-M;B. Widrow
  13. 대한 전기학회 논문지 v.47 no.2 전력계통의 안정화를 위한 퍼지 PID 제어기의 적용과 제어특성 정형환;주석민;정동일;김상효;고희석
  14. IEEE Trans. Cont. Syst. Tech. v.2 no.4 Fuzzy Precompensated PID Controllers J. H. Kim;K. C. Kim;E. K. P. Chong
  15. Fuzzy Sets and Systems 92 Fuzzy-PID hybrid control : Automatic rule generation using genetic algorithms H. J. Cho;K. B. Cho;B-H. Wang