Swarm intelligence approaches to estimate electricity energy demand in Turkey
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Dosyalar
Tarih
2012
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
ELSEVIER SCIENCE BV
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
This paper proposes two new models based on artificial bee colony (ABC) and particle swarm optimization (PSO) techniques to estimate electricity energy demand in Turkey. ABC and PSO electricity energy estimation models (ABCEE and PSOEE) are developed by incorporating gross domestic product (GDP), population, import and export figures of Turkey as inputs. All models are proposed in two forms, linear and quadratic. Also different neighbor selection mechanisms are attempted for ABCEE model to increase convergence to minimum of the algorithm. In order to indicate the applicability and accuracy of the proposed models, a comparison is made with ant colony optimization (ACO) which is available for the same problem in the literature. According to obtained results, relative estimation errors of the proposed models are lower than ACO and quadratic form provides better-fit solutions than linear form due to fluctuations of the socio-economic indicators. Finally, Turkey's electricity energy demand is projected until 2025 according to three different scenarios. (C) 2012 Elsevier B.V. All rights reserved.
Açıklama
Anahtar Kelimeler
Ant colony optimization, Artificial bee colony, Particle swarm optimization, Electricity energy estimation, Swarm intelligence
Kaynak
KNOWLEDGE-BASED SYSTEMS
WoS Q Değeri
Q1
Scopus Q Değeri
Q1
Cilt
36
