Long Term Energy Consumption Forecasting Using Genetic Programming
1
Department of Computer Engineering, Yasar University, 35500 Izmir, Turkey
2
Department of Electrical and Electronics Engineering, Kahramanmaras Sutcu Imam University, Kahramanmaras, Turkey
*
Authors to whom correspondence should be addressed.
Math. Comput. Appl. 2008, 13(2), 71-80; https://doi.org/10.3390/mca13020071
Published: 1 August 2008
Abstract
Managing electrical energy supply is a complex task. The most important part of electric utility resource planning is forecasting of the future load demand in the regional or national service area. This is usually achieved by constructing models on relative information, such as climate and previous load demand data. In this paper, a genetic programming approach is proposed to forecast long term electrical power consumption in the area covered by a utility situated in the southeast of Turkey. The empirical results demonstrate successful load forecast with a low error rate.
Keywords:
genetic programming; load forecasting; symbolic regression
Share and Cite
MDPI and ACS Style
Karabulut, K.; Alkan, A.; Yilmaz, A.S. Long Term Energy Consumption Forecasting Using Genetic Programming. Math. Comput. Appl. 2008, 13, 71-80. https://doi.org/10.3390/mca13020071
AMA Style
Karabulut K, Alkan A, Yilmaz AS. Long Term Energy Consumption Forecasting Using Genetic Programming. Mathematical and Computational Applications. 2008; 13(2):71-80. https://doi.org/10.3390/mca13020071
Chicago/Turabian StyleKarabulut, Korhan, Ahmet Alkan, and Ahmet S. Yilmaz. 2008. "Long Term Energy Consumption Forecasting Using Genetic Programming" Mathematical and Computational Applications 13, no. 2: 71-80. https://doi.org/10.3390/mca13020071
