Long term energy consumption forecasting using genetic programming
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Date
2008
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Association for Scientific Research
Open Access Color
GOLD
Green Open Access
Yes
OpenAIRE Downloads
OpenAIRE Views
Publicly Funded
No
BIP! Indicators
Impulse
Average
Influence
Top 10%
Popularity
Top 10%
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.
Description
Keywords
Matematik, Symbolic Regression, Genetic Programming, Load Forecasting, genetic programming; load forecasting; symbolic regression
Fields of Science
0211 other engineering and technologies, 0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology
Citation
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WoS Q
Scopus Q
OpenCitations Citation Count
18
Source
Mathematical and Computational Applications
Volume
13
Issue
2
Start Page
71
End Page
80
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Citations
CrossRef : 16
Scopus : 45
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Mendeley Readers : 41
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