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http://dx.doi.org/10.5370/KIEE.2013.62.11.1590

Electric Power Load Forecasting using Fuzzy Prediction System  

Bang, Young-Keun (Dept. of Electrical Engineering, Kangwon National University)
Shim, Jae-Sun (Dept. of Electrical Engineering, Kangwon National University)
Publication Information
The Transactions of The Korean Institute of Electrical Engineers / v.62, no.11, 2013 , pp. 1590-1597 More about this Journal
Abstract
Electric power is an important part in economic development. Moreover, an accurate load forecast can make a financing planning, power supply strategy and market research planned effectively. This paper used the fuzzy logic system to predict the regional electric power load. To design the fuzzy prediction system, the correlation-based clustering algorithm and TSK fuzzy model were used. Also, to improve the prediction system's capability, the moving average technique and relative increasing rate were used in the preprocessing procedure. Finally, using four regional electric power load in Taiwan, this paper verified the performance of the proposed system and demonstrated its effectiveness and usefulness.
Keywords
Electric power load; Prediction system; Correlation-based clustering algorithm; TSK fuzzy logic system;
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Times Cited By KSCI : 1  (Citation Analysis)
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