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

The Korean Institute of Electrical Engineers (대한전기학회)
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Electric Load Forecasting using Data Preprocessing and Fuzzy Logic System

데이터 전처리와 퍼지 논리 시스템을 이용한 전력 부하 예측

  • Bang, Young-Keun (Dept. of Electrical Engineering, Kangwon National University) ;
  • Lee, Chul-Heui (Dept. of Electrical and Electronic Engineering, Kangwon National University)
  • Received : 2017.07.25
  • Accepted : 2017.11.07
  • Published : 2017.12.01
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Abstract

This paper presents a fuzzy logic system with data preprocessing to make the accurate electric power load prediction system. The fuzzy logic system acceptably treats the hidden characteristic of the nonlinear data. The data preprocessing processes the original data to provide more information of its characteristics. Thus the combination of two methods can predict the given data more accurately. The former uses TSK fuzzy logic system to apply the linguistic rule base and the linear regression model while the latter uses the linear interpolation method. Finally, four regional electric power load data in taiwan are used to evaluate the performance of the proposed prediction system.

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References

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