Rukiye B.AYMAZ, Mehmet Ali YALÇIN, Talha Enes GÜMÜŞ

Kuzeybatı Anadolu Güç Sisteminde Yenilenebilir Enerji Kaynaklarının Optimal Boyutlandırılması ve Yerleşimi

Bu çalışmada güç sistemlerine eklenecek dağıtık üretim (DÜ) kaynaklarının bağlantı yeri ve güç değerlerinin belirlenmesi problemi, sezgisel optimizasyon yöntemlerinden genetik algoritma (GA) kullanılarak hesaplanmıştır. Optimizasyon probleminin çözümünde amaç fonksiyonu olarak aktif güç kayıplarının minimize edilmesi ve sistem bara gerilimlerin iyileştirilmesi amaçlanmıştır. Bu nedenle sistem bara gerilimlerinin belirli aralıkta tutulması kısıt olarak optimizasyon problemine eklenmiştir. Önerilen yaklaşım Kuzeybatı Anadolu (KBA) 114 baralı güç iletim sistemine 2 farklı amaç fonksiyonu için uygulanmıştır. Bu yaklaşımla güç sisteminin ağ topolojisini değiştirmeksizin dağıtık üretim kaynaklarının eklenmesi halinde her durum için aktif güç kayıplarının azaldığı ve bara gerilim profilinin iyileştiği gözlenmiştir.

Anahtar Kelimeler:

Genetik algoritma, Dağıtık üretim, Optimizasyon, Yenilenebilir enerji kaynakları

Optimal Sizing and Allocation of Renewable Sources in Northwest Anatolia Power System

In this study, the problem of determining the location and sizing of the distributed generation (DG) resources added to the power systems has been calculated using genetic algorithms (GA), one of the heuristic optimization methods. The optimization problem aims to minimize the active power losses and improve the system bus voltages as an objective function. Therefore, keeping the system bus voltages within the defined limits has been added to the optimization problem as a constraint. The proposed approach has been applied for two objective function to 114 bus North West Anatolia (KBA) power system. With this approach, it has been observed that the active power losses for each case have been reduced and the bus voltage profile has been improved when distributed generation resources are added without changing the network topology of the power system.

Keywords:

Genetic algorithms, Distributed generation, Optimization, Renewable energy sources,

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