Maximum Power Point Tracking for Brushless DC Motor-Driven Photovoltaic Pumping Systems Using a Hybrid ANFIS-FLOWER Pollination Optimization Algorithm

Neeraj Priyadarshi, Sanjeevikumar Padmanaban, Lucian Mihet-Popa, Frede Blaabjerg and Farooque Azam
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Neeraj Priyadarshi: Department of Electrical and Electronics Engineering, Millia Institute of Technology, Purnea 854301, India
Sanjeevikumar Padmanaban: Department of Energy Technology, Aalborg University, 6700 Esbjerg, Denmark
Lucian Mihet-Popa: Faculty of Engineering, Østfold University College, Kobberslagerstredet 5, 1671 Kråkeroy-Fredrikstad, Norway
Frede Blaabjerg: Center for Reliable Power Electronics (CORPE), Department of Energy Technology, Aalborg University, Aalborg 9220, Denmark
Farooque Azam: Department of Electrical and Electronics Engineering, Millia Institute of Technology, Purnea 854301, India

Energies, 2018, vol. 11, issue 5, 1-16

Abstract: In this research paper, a hybrid Artificial Neural Network (ANN)-Fuzzy Logic Control (FLC) tuned Flower Pollination Algorithm (FPA) as a Maximum Power Point Tracker (MPPT) is employed to amend root mean square error (RMSE) of photovoltaic (PV) modeling. Moreover, Gaussian membership functions have been considered for fuzzy controller design. This paper interprets the Luo converter occupied brushless DC motor (BLDC)-directed PV water pump application. Experimental responses certify the effectiveness of the suggested motor-pump system supporting diverse operating states. The Luo converter, a newly developed DC-DC converter, has high power density, better voltage gain transfer and superior output waveform and can track optimal power from PV modules. For BLDC speed control there is no extra circuitry, and phase current sensors are enforced for this scheme. The most recent attempt using adaptive neuro-fuzzy inference system (ANFIS)-FPA-operated BLDC directed PV pump with advanced Luo converter, has not been formerly conferred.

Keywords: ANFIS; artificial neural network; brushless DC motor; FPA; maximum power point tracking; photovoltaic system; root mean square error (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2018
References: View complete reference list from CitEc
Citations: View citations in EconPapers (8)

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