Maximum power point tracker control design of a photovoltaic-generator powered DC motor-pump system based on artificial neural networks

This paper presents the optimisation of a photovoltaic (PV) water pumping system using maximum power point tracker (MPPT) technique. The optimisation is suspended to reference optimal power. This optimisation technique is developed to assure the optimum chopping ratio of buck-boost converter. The pr...

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Bibliographic Details
Published in:Australian journal of electrical & electronics engineering 2012-06, Vol.9 (2), p.127
Main Author: Kassem, A.M
Format: Article
Language:English
Subjects:
Electric current converters
Emissions (Pollution)
Mathematical optimization
Neural networks
Solar energy industry
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Summary:This paper presents the optimisation of a photovoltaic (PV) water pumping system using maximum power point tracker (MPPT) technique. The optimisation is suspended to reference optimal power. This optimisation technique is developed to assure the optimum chopping ratio of buck-boost converter. The presented MPPT technique is used in PV water pumping system in order to optimise its efficiency. An adaptive controller with emphasis on non-linear autoregressive moving average (NARMA) based on artificial neural networks approach is applied in order to optimise the duty ratio for PV maximum power at any irradiation level. In this application, an indirect data-based technique is taken, where a model of the plant is identified on the basis of input-output data and then used in the model-based design of a neural network controller. The proposed controller has the advantages of robustness, fast response and good performance. The PV generator DC motor pump system with the proposed controller has been tested through a step change in irradiation level. Simulation results show that accurate MPPT tracking performance of the proposed system has been achieved. Further, the performance of the proposed artificial neural network (ANN) controller is compared with a proportional-integral-derivative controller through simulation studies. Obtained results demonstrate the effectiveness and superiority of the proposed approach. KEYWORDS: Photovoltaic; maximum power point tracker; drive systems; artificial neural network controller. REFERENCE: Kassem, A. M. 2012, "Maximum power point tracker control design of a photovoltaic-generator powered DC motor-pump system based on artificial neural networks", Australian Journal of Electrical & Electronics Engineering, Vol. 9, No. 2, pp. 127-136, doi: 10.7158/E10-894.2012.9.2
ISSN:1448-837X
DOI:10.7158/E10-894.2012.9.2