Nanoşebekede Yapay Zeka Tabanlı Enerji Yönetim Sistemi Tasarımı

Öz

Günümüzde enerji bağımsızlığı ve sürdürülebilirlik hedefleri doğrultusunda nanoşebeke sistemleri giderek daha fazla önem kazanmaktadır. Bu sistemler, yerel enerji üretimi, depolaması ve tüketimini optimize ederek enerji verimliliğini artırmayı ve maliyetleri düşürmeyi amaçlamaktadır. Bu makalede, nanoşebekelerde yapay zeka tabanlı bir enerji yönetim sisteminin tasarımı ve MATLAB/Simulink ortamında simülasyonu sunulmaktadır. Çalışma, nanoşebeke kavramını, mikroşebekelerden farklarını ve enerji yönetim sistemlerinin kritik rolünü ele almaktadır. Yapay zeka tekniklerinin enerji yönetimindeki potansiyeli vurgulanarak, özellikle yük tahmini ve batarya yönetimi gibi alanlarda yapay sinir ağları (YSA) gibi algoritmaların kullanımı incelenmiştir. Geliştirilen model, enerji üretimi, tüketimi ve depolama verileri kullanılarak simüle edilmiş, elde edilen sonuçlar analiz edilmiş ve yapay zeka tabanlı enerji yönetim sistemlerinin klasik yöntemlere kıyasla sunduğu avantajlar değerlendirilmiştir. Simülasyon bulguları, önerilen yapay zeka tabanlı yaklaşımın nanoşebeke sistemlerinin performansını, güvenilirliğini ve ekonomik verimliliğini önemli ölçüde artırabileceğini göstermektedir.

Anahtar Kelimeler

• Yenilenebilir enerji
• yapay zeka
• yapay sinir ağı
• nanoşebeke
• enerji yönetim sistemleri

Artificial Intelligence-Based Energy Management System Design in Nanogrid

Öz

As energy independence and sustainability become more of a priority, nanogrid technologies are becoming more and more significant. These systenerji yönetim sistemleri aim to increase energy efficiency and reduce costs by optimizing local energy production, storage, and consumption. This article presents the design and simulation of an AI-based energy management system in nanogrids in the MATLAB/Simulink environment. The study examines the concept of nanogrids, their differences from microgrids, and the critical role of energy management systenerji yönetim sistemleri. The potential of AI techniques in energy management is emphasized, and the use of algorithms such as artificial neural networks (ANNs) is examined, particularly in areas such as load forecasting and battery management. The developed model was simulated using energy production, consumption, and storage data. The results were analyzed, and the advantages offered by AI-based energy management systenerji yönetim sistemleri over traditional methods were evaluated. Simulation findings demonstrate that the proposed AI-based approach can significantly improve the performance, reliability, and economic efficiency of nanogrid systenerji yönetim sistemleri.

Anahtar Kelimeler

• Renewable energy
• artificial intelligence
• artificial neural networks
• nanogrids
• energy management systenerji yönetim sistemleri

Kaynakça

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