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Akıllı Şebeke Uygulamalarında Derin Öğrenme Tekniklerinin Kullanımına İlişkin Kısa Bir İnceleme

Yıl 2023, Cilt: 13 Sayı: 1, 41 - 61, 23.01.2023

Öz

Akıllı şebeke, elektrik şebekesinden yüksek boyutlu ve çeşitli yapılardaki verilerin sürekli olarak toplanması ve anlamlandırılması ile enerjinin üretiminden son kullanıcıya ulaşmasına kadar olan süreçlerin optimum şekilde yönetilmesi esasına dayanır. Bu nedenle çağın gereklerine uygun gelişmiş ölçüm altyapısının, kontrol teknolojilerinin ve bilgi & iletişim teknolojilerinin (ICT) şebekeye entegrasyonu oldukça önemli bir konudur. Fakat, geleneksel modelleme, optimizasyon ve kontrol teknolojilerinin şebeke üzerinden toplanan verilerin işlenmesinde bazı sınırlamaları bulunmaktadır. Bu nedenle, son zamanlarda akıllı şebekede derin öğrenme (DL) tekniklerinin kullanımı daha popüler hale gelmektedir. Bu çalışmada bazı yaygın DL tekniklerinin akıllı şebekelerdeki kullanımına ilişkin yapılan mevcut araştırmaların yapılandırılmış bir incelemesi sunulmaktadır. İncelemede, özellikle yük tahmini ve kestirimi, mikro şebeke, talep yanıtı, hata tespiti ve durum tahmini, güç sistemi analizi ve kontrolü, siber güvenlik ve yenilenebilir enerji üretimi gibi akıllı şebeke problemlerine odaklanılmış, ve ilgili literatür sunulmuştur. Bu çalışma, DL teknikleri uygulamalarının hem akıllı şebeke sistemlerinde giderek artan oranda yer alacağını hem de şebekenin güvenilirliğini, güvenliğini ve dayanıklılığını iyileştirmede önemli katkılar sağlayacağını göstermektedir.

Kaynakça

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A Brief Review on the Use of Deep Learning Techniques in Smart Grid Applications

Yıl 2023, Cilt: 13 Sayı: 1, 41 - 61, 23.01.2023

Öz

The smart grid is based on the principle of continuous collection and interpretation of high-dimensional and diverse data from the electricity grid, and optimum management of the processes from the generation of energy to its delivery to the end user. Therefore, the integration of advanced measurement infrastructure, control technologies, and information & communication technologies (ICT) into the network is a quite crucial issue. However, traditional modeling, optimization, and control technologies have some limitations in processing data collected over the grid. Therefore, the use of deep learning (AI) techniques in the smart grid is becoming more popular lately. In this study, a brief review of current research on the use of some common DL techniques in smart grids is presented. The review focuses on smart grid problems such as load forecasting and estimation, microgrid, demand response, fault detection and state prediction, power system analysis and control, cyber security and renewable energy generation, and related literature is presented. This study shows that the applications of DL techniques will be increasingly involved in smart grid systems and will make significant contributions to improving the reliability, security, and durability of the grid.

Kaynakça

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Toplam 86 adet kaynakça vardır.

Ayrıntılar

Birincil Dil Türkçe
Konular Mühendislik
Bölüm Akademik ve/veya teknolojik bilimsel makale
Yazarlar

Reyhan Sağ

Zeynep Hasırcı Tuğcu 0000-0002-3950-4156

Yayımlanma Tarihi 23 Ocak 2023
Gönderilme Tarihi 29 Ekim 2022
Yayımlandığı Sayı Yıl 2023 Cilt: 13 Sayı: 1

Kaynak Göster

APA Sağ, R., & Hasırcı Tuğcu, Z. (2023). Akıllı Şebeke Uygulamalarında Derin Öğrenme Tekniklerinin Kullanımına İlişkin Kısa Bir İnceleme. EMO Bilimsel Dergi, 13(1), 41-61.
AMA Sağ R, Hasırcı Tuğcu Z. Akıllı Şebeke Uygulamalarında Derin Öğrenme Tekniklerinin Kullanımına İlişkin Kısa Bir İnceleme. EMO Bilimsel Dergi. Ocak 2023;13(1):41-61.
Chicago Sağ, Reyhan, ve Zeynep Hasırcı Tuğcu. “Akıllı Şebeke Uygulamalarında Derin Öğrenme Tekniklerinin Kullanımına İlişkin Kısa Bir İnceleme”. EMO Bilimsel Dergi 13, sy. 1 (Ocak 2023): 41-61.
EndNote Sağ R, Hasırcı Tuğcu Z (01 Ocak 2023) Akıllı Şebeke Uygulamalarında Derin Öğrenme Tekniklerinin Kullanımına İlişkin Kısa Bir İnceleme. EMO Bilimsel Dergi 13 1 41–61.
IEEE R. Sağ ve Z. Hasırcı Tuğcu, “Akıllı Şebeke Uygulamalarında Derin Öğrenme Tekniklerinin Kullanımına İlişkin Kısa Bir İnceleme”, EMO Bilimsel Dergi, c. 13, sy. 1, ss. 41–61, 2023.
ISNAD Sağ, Reyhan - Hasırcı Tuğcu, Zeynep. “Akıllı Şebeke Uygulamalarında Derin Öğrenme Tekniklerinin Kullanımına İlişkin Kısa Bir İnceleme”. EMO Bilimsel Dergi 13/1 (Ocak 2023), 41-61.
JAMA Sağ R, Hasırcı Tuğcu Z. Akıllı Şebeke Uygulamalarında Derin Öğrenme Tekniklerinin Kullanımına İlişkin Kısa Bir İnceleme. EMO Bilimsel Dergi. 2023;13:41–61.
MLA Sağ, Reyhan ve Zeynep Hasırcı Tuğcu. “Akıllı Şebeke Uygulamalarında Derin Öğrenme Tekniklerinin Kullanımına İlişkin Kısa Bir İnceleme”. EMO Bilimsel Dergi, c. 13, sy. 1, 2023, ss. 41-61.
Vancouver Sağ R, Hasırcı Tuğcu Z. Akıllı Şebeke Uygulamalarında Derin Öğrenme Tekniklerinin Kullanımına İlişkin Kısa Bir İnceleme. EMO Bilimsel Dergi. 2023;13(1):41-6.

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