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Math. Comput. Appl. 2008, 13(2), 71-80; doi:10.3390/mca13020071

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.
Published: 1 August 2008
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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 genetic programming; load forecasting; symbolic regression
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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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.

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Math. Comput. Appl. EISSN 2297-8747 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
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