Genetik Algoritma Kullanılarak Hibrit Yenilenebilir Enerji Kaynaklarının Maliyet Minimizasyonu

Year 2017, Volume: 2 Issue: 2, 41 - 54, 29.12.2017

Kerim Karabacak , Ali Telli

Abstract

Özet 1 :

Bu yazıda güneş panelelleri,
rüzgâr jeneratörü ve batarya içeren bir hibrit yenilenebilir enerji sistemi
önerilmiştir. Bütün sistemin maliyet fonksiyonları belirlenmiştir. Her
yenilenebilir enerji modülü (fotovoltaik, rüzgâr jeneratörü, akü) için
güç-maliyet ilişkileri gösterilmiştir. Önerilen yenilenebilir enerji sisteminin
toplam maliyetini en aza indirmek için genetik algoritma kullanılır. Genetik
algoritma için hesaplamaları basitleştirmek için maliyet katsayısı tanımları
yapılmıştır. Geleneksel hesaplama algoritmalarının yanı sıra, hesaplama zamanı
ve hesaplama çabasını azaltmak için genetik algoritmanın olasılık yaklaşımı
kullanılmıştır. Sonuç olarak; genetik algoritma, yenilenebilir enerji maliyet
optimizasyonu problemlerinde hesaplama çabasını azalttığından, geleneksel
hesaplama algoritmalarından daha uygun olduğu gösterilmiştir.

Özet 2 :

In this paper, a hybrid renewable
energy system is proposed which includes PV, wind generator and batteries.  Cost functions of whole system is
determined.  Power-cost relations for
each renewable energy module (PV, wind generator, battery) are inspected.  Genetic algorithm is used to minimize the
total cost of proposed renewable energy system. For genetic algorithm, cost
coefficient definitions are made for simplifying calculations. Beside
conventional search algorithms, genetic algorithm’s probabilistic approach is
used for reducing calculation time and computation effort. In results, it is
shown that genetic algorithm is more suitable than conventional search
algorithms for reducing computation effort for renewable energy cost
optimization problems.

Keywords

Hibrit yenilenebilir enerji sistemi, yenilenebilir enerji, genetik algoritma, maliyet minimizasyonu, optimizasyon

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