Simulation and Experimental validation of Distributed MPPT algorithms for partially shaded Photovoltaic systems

• Autorzy: Muthuramalingam M , Manoharan P. S.

Warianty tytułu

PL

Symulacja i eksperymentalna weryfikacja algorytmów śledzenia mocy w systemach fotowoltaicznych

• Języki publikacji: EN

Abstrakty

EN

This paper analyzes the performance of two different maximum power point tracking (MPPT) algorithms for photovoltaic (PV) system: artificial neural network (ANN) and adaptive neuro fuzzy inference (ANFIS) as used by an interleaved soft switching boost converter (ISSBC) system with different conditions, such as partially shaded, condition, changing solar insolation and PV cell temperature. However, under partially shaded conditions, when the PV module characteristics get more complex with multiple peaks of output power. Both algorithms are methodically investigated by means of Matlab simulation and hardware experimental validation, compare in terms of parameters tracking speed, power extraction, and harmonic analysis. In this topology, each cascaded H-bridge inverter (CHBMLI) unit is connected to an individual PV module through an interleaved soft switching boost converter (ISSBC). The simulation and hardware results show that ANFIS algorithm is outperforming than the ANN algorithm.

PL

W artykule analizowane są dwa algorytmy śledzenia maksymalnej mocy (MPPT) stosowane w systemach fotowoltaicznych: jeden (ANN) wykorzystuje sieci neuronowe a drugi wykorzystuje ANFIS. Układ pozwla na załączanie przekształtnika w zależności od warunków, np. zacienienia czy temperatury.

Słowa kluczowe

EN

photovoltaic system; maximum power point tracking (PPT); microcontroller; interleaved boost converter; cascade H-bridge inverter

PL

system fotowoltaiczny; śledzenie mocy; ANFIS; sieć neuronowa

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2014
• Tom: R. 90, nr 8
• Strony: 92--96
• Opis fizyczny: Bibliogr. 13 poz., rys., tab., wykr.

Twórcy

autor

Muthuramalingam M

• College of Engineering and Technology, Madurai, India

autor

Manoharan P. S.

• Thiagarajar College of Engineering, Madurai, India

Bibliografia

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• [9] Faete Filho., Leon.M., Tolbert., Yue Cao., 2011, Real-time selective harmonic minimization for multilevel inverters connected to solar panels using artificial neural network angle generation, IEEE Transactions on Industry Applications, 47 (5), 2117-2124
• [10] Yi-Hua Liu., Chun-Liang Liu., Jia-Wei Huang., Jing-Hsiau Chen., 2013, Neural-network-based maximum power point tracking methods for photovoltaic systems operating under fast changing environments, Solar Energy, 89 (5), 42-53.
• [11] Whei-Min Lin., Chih-Ming Hong., Chiung Hsing Chen., 2011, Neural network based MPPT control of a stand-alone hybrid power generation system, IEEE Transactions on Power Electronics, 26 (12), 3571-3581
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