Long term energy consumption forecasting using genetic programming

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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

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Publicly Funded

No
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Average
Influence
Top 10%
Popularity
Top 10%

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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. © 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

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OpenCitations Citation Count
18

Source

Mathematical and Computational Applications

Volume

13

Issue

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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