Comparative Analysis of Voltage Segmentation (0.8Voc) and Sensorless MPPT Algorithms in PV Pump Systems Operating Under Partial Shading Conditions

Abstract

When photovoltaic (PV) irrigation systems operate under partial shading conditions (PSC), traditional methods are insufficient. In addition to modified traditional methods, artificial intelligence and optimization-based smart methods are used to obtain maximum power from PV systems operating under PSC. These methods use one or more of the PV system's current, voltage, and atmospheric environment variables. In this study, a sensorless Maximum Power Point Tracking (MPPT) algorithm was developed. The proposed algorithm uses the values of the current and speed of the Brushless Direct Current Motor(BLDC) which used in the PV irrigation system. The current, voltage and other parameters of the PV system was not used. The proposed algorithm was compared the 0.8Voc method that used panel data. The proposed MPPT algorithm was tested with a simulation study created in the MATLAB/Simulink environment. In the simulation study, four different PSCs were created and the 0.8Voc method was compared with the proposed method. The obtained results are shown graphically. Accordingly, the superiority of the proposed method was observed in all cases except for the PSC2 case. On the other hand, there is a clear superiority in the speed of the 0.8Voc method. The proposed sensorless MPPT technique operated the PV pump system with high efficiency as 99.9% in the case of PSC1, 95% in the case of PSC2, 99.9% in the case of PSC3 and 99.7% in the case of PSC4.

Keywords

• PV pump
• Partial shading
• Sensorless MPPT
• BLDC
• 0.8Voc

Kısmi Gölgelenme Koşullarında Çalışan FV Pompa Sistemlerinde 0.8Voc ve Algılayıcısız MGNİ Algoritmalarının Karşılaştırılmalı Analizi

Abstract

Fotovoltaik (FV) sulama sistemleri kısmi gölgeleme koşullarında (KGK) çalıştığında geleneksel yöntemler yetersiz kalmaktadır. KGK altında FV sistemlerden maksimum güç elde etmek için modifiye edilmiş geleneksel yöntemlerin yanı sıra yapay zekâ ve optimizasyona dayalı akıllı yöntemler de kullanılmaktadır. Bu yöntemler FV sistemin akım, gerilim ve atmosferik ortam değişkenlerinden bir veya daha fazlasını kullanır. Bu çalışmada algılayıcısız bir Maksimum Güç Noktası İzleme (MGNİ) algoritması geliştirilmiştir. Önerilen algoritma, FV sulama sisteminde kullanılan Fırçasız Doğru Akım Motorunun (FDAM) akım ve hız değerlerini kullanmaktadır. FV sistemin akım, gerilim ve diğer parametreleri kullanmamaktadır. Önerilen algoritma, panel verileri kullanan 0.8Voc yöntemiyle karşılaştırılmıştır. Önerilen MGNİ algoritması MATLAB/Simulink ortamında oluşturulan bir simülasyon çalışmasıyla test edilmiştir. Simülasyon çalışmasında dört farklı KGK oluşturulmuş ve 0.8Voc yöntemi önerilen yöntemle karşılaştırılmıştır. Elde edilen sonuçlar grafiksel olarak gösterilmektedir. Buna göre önerilen yöntemin üstünlüğü KGK2 durumu dışındaki tüm durumlarda gözlenmiştir. Öte yandan 0.8Voc yönteminin hızında da bariz bir üstünlük görülmektedir.

Keywords

• FV pompa
• Kısmi gölgelenme
• Algılayıcısız MGNİ
• FDAM
• 0.8Voc

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