Neuro-Fuzzy Wavelet Based Adaptive MPPT Algorithm for Photovoltaic Systems

Syed Zulqadar Hassan, Hui Li, Tariq Kamal, Uğur Arifoğlu, Sidra Mumtaz and Laiq Khan
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Syed Zulqadar Hassan: State Key Laboratory of Power Transmission Equipment and System Security and New Technology, School of Electrical Engineering, Chongqing University, Chongqing 400044, China
Hui Li: State Key Laboratory of Power Transmission Equipment and System Security and New Technology, School of Electrical Engineering, Chongqing University, Chongqing 400044, China
Tariq Kamal: Department of Electrical and Electronics Engineering, Faculty of Engineering, Sakarya University, Serdivan/Sakarya 54050, Turkey
Uğur Arifoğlu: Department of Electrical and Electronics Engineering, Faculty of Engineering, Sakarya University, Serdivan/Sakarya 54050, Turkey
Sidra Mumtaz: Department of Electrical Engineering, COMSATS Institute of Information Technology, Abbottabad 22060, Pakistan
Laiq Khan: Department of Electrical Engineering, COMSATS Institute of Information Technology, Abbottabad 22060, Pakistan

Energies, 2017, vol. 10, issue 3, 1-16

Abstract: An intelligent control of photovoltaics is necessary to ensure fast response and high efficiency under different weather conditions. This is often arduous to accomplish using traditional linear controllers, as photovoltaic systems are nonlinear and contain several uncertainties. Based on the analysis of the existing literature of Maximum Power Point Tracking (MPPT) techniques, a high performance neuro-fuzzy indirect wavelet-based adaptive MPPT control is developed in this work. The proposed controller combines the reasoning capability of fuzzy logic, the learning capability of neural networks and the localization properties of wavelets. In the proposed system, the Hermite Wavelet-embedded Neural Fuzzy (HWNF)-based gradient estimator is adopted to estimate the gradient term and makes the controller indirect. The performance of the proposed controller is compared with different conventional and intelligent MPPT control techniques. MATLAB results show the superiority over other existing techniques in terms of fast response, power quality and efficiency.

Keywords: photovoltaic systems; maximum power point tracking; adaptive control; wavelets (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: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (12)

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