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http://dx.doi.org/10.5370/JEET.2015.10.3.832

Short-term Electric Load Forecasting Based on Wavelet Transform and GMDH  

Koo, Bon-Gil (Dept. of Electrical and Electronic Engineering, Pusan National University)
Lee, Heung-Seok (Dept. of Electrical and Electronic Engineering, Pusan National University)
Park, Juneho (Dept. of Electrical and Electronic Engineering, Pusan National University)
Publication Information
Journal of Electrical Engineering and Technology / v.10, no.3, 2015 , pp. 832-837 More about this Journal
Abstract
The group method of data handling (GMDH) algorithm has proven to be a powerful and effective way to extract rules or polynomials from an electric load pattern. However, because it is nonstationary, the load pattern needs to be decomposed using a discrete wavelet transform. In addition, if a load pattern has a complicated curve pattern, GMDH should use a higher polynomial, which requires complex computing and consumes a lot of time. This paper suggests a method for short-term electric load forecasting that uses a wavelet transform and a GMDH algorithm. Case studies with the proposed algorithm were carried out for one-day-ahead forecasting of hourly electric loads using data during the years 2008-2011. To prove the effectiveness of our proposed approach, the results were evaluated and compared with those obtained by Holt-Winters method and artificial neural network. Our suggested method resulted in better performance than either comparison group.
Keywords
Discrete wavelet transform; GMDH; Short-term electric load forecasting;
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