RETRACTION: DSTATCOM Based on Artificial Neural Networks and Particle Swarm Optimization for Voltage Profile Improvement

Year 2021, , 32 - 45, 21.06.2021

Fouad Zaro

https://doi.org/10.5281/zenodo.4742866

Abstract

Recently the demand for electric power is increased due to increasing the residential and industrial facilities which may contain sensitive nonlinear loads that needed high power quality (PQ) on the distribution system to avoid malfunction operation. One main PQ issue is voltage profile improvement with acceptable voltage harmonic distortion. It should be regulated to be within acceptable standard levels. In order to improve the voltage profile, the distribution static synchronous compensator (DSTATCOM) is used with a developed control strategy. In this research, DSTATCOM control is developed based on artificial intelligent (AI) using the artificial neural network (ANN), which depends on optimum values obtained by using particle swarm optimization (PSO). The results of the simulation proved the superiority and robustness of the proposed control strategy of DSTATCOM for improving the voltage profile on the distribution system. The validation of results has been done by MATLAB/Simulink software package.

This article was retracted on August 17, 2021.

Keywords

DSTATCOM, Artificial Neural Networks, PI controller, Power Quality, Voltage Profile

Geri Çekildi: Yapay Sinir Ağlarına ve Gerilim Profili İyileştirme için Parçacık Sürüsü Optimizasyonuna Dayalı DSTATCOM

Abstract

Son zamanlarda, arıza çalışmasını önlemek için dağıtım sisteminde yüksek güç kalitesi (PQ) gerektiren hassas doğrusal olmayan yükler içerebilen konut ve endüstriyel tesislerin artması nedeniyle elektrik gücüne olan talep artmıştır. Bir ana PQ sorunu, kabul edilebilir gerilim harmonik distorsiyonu ile gerilim profili iyileştirmesidir. Kabul edilebilir standart seviyelerde olacak şekilde düzenlenmelidir. Gerilim profilini iyileştirmek için, geliştirilmiş bir kontrol stratejisi ile dağıtım statik senkron kompansatör (DSTATCOM) kullanılır. Bu araştırmada, DSTATCOM kontrolü, parçacık sürüsü optimizasyonu (PSO) kullanılarak elde edilen optimum değerlere bağlı olan yapay sinir ağı (YSA) kullanılarak yapay zekaya (AI) dayalı olarak geliştirilmiştir. Simülasyonun sonuçları, dağıtım sistemindeki voltaj profilini iyileştirmek için DSTATCOM'un önerilen kontrol stratejisinin üstünlüğünü ve sağlamlığını kanıtladı. Sonuçların doğrulanması MATLAB / Simulink yazılım paketi ile yapılmıştır.

Bu makale 17-08-2021 tarihinde geri çekildi. 

Keywords

DSTATCOM, Yapay Sinir Ağları, PI denetleyici, Güç Kalitesi, Gerilim Profili

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