Long term energy consumption forecasting using genetic programming
Loading...

Date
2008
Authors
Korhan Karabulut
Ahmet Alkan
Ahmet Serdar Yilmaz
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
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. © Association for Scientific Research. © 2020 Elsevier B.V. All rights reserved.
Description
Keywords
Genetic Programming, Load Forecasting, Symbolic Regression, Electric Loads, Electric Power Utilization, Energy Management, Regression Analysis, Resource Allocation, Electrical Energy Supply, Load Forecasting, Symbolic Regression, Genetic Programming, Electric loads, Electric power utilization, Energy management, Regression analysis, Resource allocation, Electrical energy supply, Load forecasting, Symbolic regression, Genetic programming, 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
WoS Q
Scopus Q

OpenCitations Citation Count
18
Source
Mathematical and Computational Applications
Volume
13
Issue
Start Page
71
End Page
80
Collections
PlumX Metrics
Citations
CrossRef : 16
Scopus : 45
Captures
Mendeley Readers : 41
Google Scholar™


