전기학회논문지 (The Transactions of The Korean Institute of Electrical Engineers)

  • 제60권12호
  • /
  • Pages.2215-2220
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  • 2011
  • /
  • 1975-8359(pISSN)
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  • 2287-4364(eISSN)
대한전기학회 (The Korean Institute of Electrical Engineers)
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추석 연휴 전력수요 특성 분석을 통한 단기전력 수요예측 기법 개발

Development of Short-Term Load Forecasting Method by Analysis of Load Characteristics during Chuseok Holiday

  • 권오성 (숭실대학교 전기공학부) ;
  • 송경빈 (숭실대학교 전기공학부)
  • 투고 : 2011.08.31
  • 심사 : 2011.10.31
  • 발행 : 2011.12.01
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초록

The accurate short-term load forecasting is essential for the efficient power system operation and the system marginal price decision of the electricity market. So far, errors of load forecasting for Chuseok Holiday are very big compared with forecasting errors for the other special days. In order to improve the accuracy of load forecasting for Chuseok Holiday, selection of input data, the daily normalized load patterns and load forecasting model are investigated. The efficient data selection and daily normalized load pattern based on fuzzy linear regression model is proposed. The proposed load forecasting method for Chuseok Holiday is tested in recent 5 years from 2006 to 2010, and improved the accuracy of the load forecasting compared with the former research.

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참고문헌

  1. 한국전력공사, 전력연구원, "전력수급계획 및 운용해석 종합시스템 개발에 관한 연구", '98 전력연-단984, pp.170, 1998년 12월.
  2. D.J. Trudnowski, et al., "Real-time Very Short-Term Load Prediction for Power-System Automatic Generation Control," IEEE Trans. on Control Systems Technology, Vol.9, No. 2, pp.254-260, 2001. https://doi.org/10.1109/87.911377
  3. T. Senjyu, H. Takara, and T. Funabashi, "One- Hour-Ahead Load Forecasting Using Neural Network," IEEE Trans. on Power Systems, Vol. 17, No.1, pp.113-118, 2002. https://doi.org/10.1109/59.982201
  4. 위영민, 송경빈, 주성관, "특수일 최대 전력 수요 예측을 위한 결정계수를 사용한 데이터 마이닝", 전기학회논문지, 제 58권, 제1호, pp.18-22, 2009년 1월.
  5. 송경빈, "부하변동율을 이용한 선거일의 24시간 수요예측", 전기학회논문지, 제 59A권 6호, pp. 1041-1045, 2010년 6월.
  6. 구본석, 백영식, 송경빈, "추석과 설날 연휴에 대한 전력수요예측 알고리즘 개선", 전기학회논문지, 제 51D권 10호, pp. 453-459, 2002년 10월.
  7. Dug Hun Hong, Sungho Lee and Hae Young Do, "Fuzzy linear regression data using shape preserving operations", Fuzzy Sets and systems.
  8. D. Srinivasan, C. S. Chang, and A. C. Liew, "Demand forecasting Using fuzzy Neural Computation, With Special Emphasis On Weekend And Public Holiday Forecasting," IEEE Trans. on Power Systems, Vol.10, No. 4. pp. 1897-1903, Nov. 1996
  9. 송경빈, 하성관, "단기수요예측 알고리즘", 전기학회논문지, 제 53A권 10호, pp. 529-535, 2004년 10월.
  10. 송경빈, 구본석, 백영식, "특수일의 최대 전력수요예측 알고리즘 개선", 전기학회논문지, 제 51A권 3호, pp.109-116, 2002년 3월.
  11. K.H. Kim, "Short-Term Load Forecasting for Special Days in Anomalous Load Conditions Using Neural Networks and Fuzzy Inference Method", IEEE Transactions on Power Systems, Vol. 15, No. 2, pp. 559-565, May 2000. https://doi.org/10.1109/59.867141
  12. 송경빈, 구본석, 백영식, "퍼지 최소 자승 선형회귀분석 알고리즘을 이용한 특수일 전력수요예측", 전기학회논문지, 제 52D권 4호, pp. 233-237, 2003년 4월.

피인용 문헌

  1. Forecasting Daily Demand of Domestic City Gas with Selective Sampling vol.16, pp.10, 2015, https://doi.org/10.5762/KAIS.2015.16.10.6860
  2. Short-Term Load Forecasting for the Consecutive Holidays Considering Businesses' Operation Rates of Industries vol.62, pp.12, 2013, https://doi.org/10.5370/KIEE.2013.62.12.1657
  3. Representative Temperature Assessment for Improvement of Short-Term Load Forecasting Accuracy vol.27, pp.6, 2013, https://doi.org/10.5207/JIEIE.2013.27.6.039