Salih ERMİŞ, Ramazan BAYINDIR, Mehmet YEŞİLBUDAK

İyileştirilmiş Öğretme-Öğrenme Tabanlı Optimizasyon Algoritmasıyla Güç Sistemlerinde Gerilim Kararlılığı Çalışması

Bu çalışmada, son yıllarda geliştirilen öğrenme-öğretme tabanlı optimizasyon algoritması (ÖÖTO) yeniden düzenlenerek, güç sistemlerinde gerilim kararlılığı için yeni bir optimizasyon yöntemi geliştirilmiştir. Düzenlenen öğrenme-öğretme tabanlı optimizasyon (D-ÖÖTO) algoritması, IEEE 14 baralı ve Türkiye, İstanbul Anadolu yakasında 17 baralı gerçek bir güç sistemi kullanılarak gerilim kararlılığı optimizasyonu olarak sunulmuştur. Bu güç sistemlerinde, beş farklı durum (temel durum, temel durumda ki talep edilen yükün %20, %40 ve %60 artışı ve 1-5 nolu hat kesintisi) oluşturulmuş ve analizler gerçekleştirilmiştir. Daha sonra yük baralarına şönt reaktif güç kompansatörleri (RGK) bağlanarak gerilim kararlılığı açısından etkisi incelenmiştir. Sunulan D-ÖÖTO algoritmasının etkinliğini kanıtlamak için orijinal ÖÖTO ve literatürde kullanılan Yerçekimi arama algoritması (YAA), parçacık sürü optimizasyonu (PSO) ve Newton-Raphson güç akış yönetimi sonuçlarıyla karşılaştırılmıştır. Tüm çalışma koşullarında sunulan D-ÖÖTO algoritması diğer yöntemlere göre üstünlüğü kanıtlanmıştır. Tüm analizler, Intel Core(TM) i7-2620 2.7GHz ve 8.00 (64 bit) Gb Ram PC kullanılarak, Matlab R2017b programında çözümlenmiştir.

Anahtar Kelimeler:

Güç sistemleri, Gerilim karalılığı, Güç akışı, Optimizasyon

Voltage Stabılıty Study In Power Systems Wıth Improved Teachıng-Learnıng Based Optımızatıon Algorıthm

In this study, a new optimization method has been developed for voltage stability in power systems by rearranging the learning-teaching based optimization algorithm (ÖÖTO) developed in recent years. The designed learning-teaching based optimization (D-ÖÖTO) algorithm is presented as voltage stability optimization using a real power system with IEEE 14 bus and 17 bus on the Anatolian side of Istanbul, Turkey. In these power systems, five different situations (base state, 20%, 40% and 60% increase of the demanded load in the base state and line 1-5 interruption) were created and analyzes were carried out. Then, shunt reactive power compensators (RGK) were connected to the load busbars and their effect in terms of voltage stability was examined. In order to prove the effectiveness of the presented D-ÖÖTO algorithm, the original ÖÖTO and the gravity search algorithm (YAA) used in the literature were compared with the results of particle swarm optimization (PSO) and Newton-Raphson power flow management. The D-ÖÖTO algorithm presented in all operating conditions has been proven to be superior to other methods. All analyzes were analyzed in Matlab R2017b program using Intel Core(TM) i7-2620 2.7GHz and 8.00 (64 bit) Gb Ram PC.

Keywords:

Power systems, Voltage stability, Power flow, Optimization,

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