| Title |
Electric Load Forecasting using Data Preprocessing and Fuzzy Logic System |
| Authors |
방영근(Bang, Young-Keun) ; 이철희(Lee, Chul-Heui) |
| DOI |
https://doi.org/10.5370/KIEE.2017.66.12.1751 |
| Keywords |
TSK fuzzy logic system ; data preprocessing ; linear interpolation ; electric power load data |
| 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. |