전기학회논문지P (The Transactions of the Korean Institute of Electrical Engineers P)

  • 제60권1호
  • /
  • Pages.6-12
  • /
  • 2011
  • /
  • 1229-800X(pISSN)
  • /
  • 2586-7792(eISSN)
대한전기학회 (The Korean Institute of Electrical Engineers)
권호 표지
DOI QR코드

DOI QR Code

뉴로-퍼지 추론 시스템 기반 주거용 부하의 모델링 기법

Residential Load Modeling Method Based on Neuro-Fuzzy Inference System

  • 투고 : 2010.11.08
  • 심사 : 2010.12.10
  • 발행 : 2011.03.01
PDF 다운로드
⟨ 이전 논문 다음 논문 ⟩

초록

In this study, we proposed a residential load modeling method based on neuro-fuzzy inference system by considering of various harmonics. The developed method was implemented by using harmonic information, fundamental frequency and voltage which are essential input factors in conventional method. Thus, the proposed method makes it possible to effectively estimate load characteristics in power lines with harmonics. To show the effectiveness, the proposed method has been intensively tested with various dataset acquired under the different frequency and voltage and compared it with a conventional method based on neural networks.

키워드

참고문헌

  1. IEEE Task Force on Load Representation for Dynamic Performance, "Load representation for dynamic performance analysis," IEEE Trans. on Power Systems, Vol. 8, No. 2, pp. 472-482, 1993. https://doi.org/10.1109/59.260837
  2. C. Concordia and S. Ihara, "Load Representation in Power System Stability Studies," IEEE Trans. on PAS, Vol. PAS-101 1982.
  3. 한국전력공사 기술연구원, "전력계통 안정도 해석을 위한 적정부하 모델에 관한 연구" KRC-88S-J02, 1989.
  4. 지평식, "신경회로망에 의한 부하모델링과 계통해석에 관한 연구", 충북대학교 대학원 박사학위 논문, 1998.
  5. 김정훈 외, "전력계통 안정도 정밀해석을 위한 적정부하모델에 대한 연구" 한국전력공사 전력연구원 연구보고서, 2000.
  6. 이병하, 김정훈, "전력산업구조개편하에서 전력계통 운용과 계획을 위한 부하역률모델 개발에 관한 연구", 기초전력연구원 연구보고서, 2004.
  7. D.M. Vilathgamuwa, Wijekoon, H.M, "Representation of Power System Load Dynamics with ANN for Real-time application," Power Engineering Society General Meeting, Vol. 3, pp. 13-17, 2003.
  8. Dingguo Chen, Ronald R. Mohler, "Neural-Network -Based Load Modeling and Its Use in Voltage Stability Analysis," IEEE Trans. on Control Systems Technology, Vol. 11, No. 11, pp. 460-470, 2003. https://doi.org/10.1109/TCST.2003.813400
  9. V. Knyazkin, C. A. Canizares, L. H. Soder, "On the Parameter Estimation and Modeling of Aggregate Power System Load," IEEE Trans. on Power System, Vol. 19, No. 2, pp. 0123-1031, 2004.
  10. A. Keyhani, W. Wu, G. T. Heydt, "Composite Neural Network Load Models for Power System Stability Analysis," IEEE PES 2004, Vol. 2, pp. 1159 - 1163, 2004.
  11. I. A. Hiskens, J. Alseddiqui, "Sensitivity, Approximation, and Uncertainty in Power System Dynamic Simulation," IEEE Trans. on Power Systems, Vol. 21, pp. 1808-1820, 2006. https://doi.org/10.1109/TPWRS.2006.882460
  12. Qian Ai, Danzhen Gu, Chen Chen, "New Load Modeling Approach Based on Field Tests for Fast Transient Stability Calculation," IEEE Trans. on Power Systems, Vol. 21, pp. 1864-1873, 2006. https://doi.org/10.1109/TPWRS.2006.882452
  13. He Renmu, Ma Jin, David J. Hill, "Composite Load Modeling via Measurement Approach," IEEE Trans. on Power Systems, Vol. 21, pp. 663-672, 2006. https://doi.org/10.1109/TPWRS.2006.873130
  14. J. S. R. Jang, C. T. Sun, and E. Mizutani, Neuro-Fuzzy and Soft Computing: A Computational Approach to Learning and Machine Intelligence, Prentice-Hall, 1997.