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Journals / Yalvaç Akademi Dergisi / 2017 / Cilt: 2 - Sayı: 2

Genetik Algoritma Kullanılarak Hibrit Yenilenebilir Enerji Kaynaklarının Maliyet Minimizasyonu

Kerim KARABACAK
Ali TELLİ
Pages
41–54
Publication Date
2017-12-29
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

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.

📌 3 Key Takeaways

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Objective & Hypothesis:Özet 1 : Bu yazıda güneş panelelleri, rüzgâr jeneratörü ve batarya içeren bir hibrit yenilenebilir enerji sistemi önerilmiştir.
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Key Findings & Data:Özet 2 : In this paper, a hybrid renewable energy system is proposed which includes PV, wind generator and batteries.
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Conclusion & Impact: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.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Hibrit yenilenebilir enerji sistemi · yenilenebilir enerji · genetik algoritma

Özet

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.

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Cite This Article

KARABACAK, K., TELLİ, A. (2017). Genetik Algoritma Kullanılarak Hibrit Yenilenebilir Enerji Kaynaklarının Maliyet Minimizasyonu. Yalvaç Akademi Dergisi, Cilt: 2 - Sayı: 2, 41–54. https://ajindex.com/articles/218225

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