Intelligent Approach to Maximum Power Point Tracking Control Strategy for Photovoltaic Generation Systems

Rihab Mahjoub Essefi(1*), Mansour Souissi(2), Hsan Hadj Abdallah(3)

(1) National School of Engineering of Sfax, University of SFAX ( Tunisia ), Tunisia
(2) Université de Sfax, Ecole Nationale d’Ingénieurs de Sfax (ENIS), Control and Energy Management Laboratory (CEM_lab), Route Soukra km 3.5- BP N° 1173- 3038 Sfax, Tunisia
(3) Université de Sfax, Ecole Nationale d’Ingénieurs de Sfax (ENIS), Control and Energy Management Laboratory (CEM_lab), Route Soukra km 3.5- BP N° 1173- 3038 Sfax, Tunisia
(*) Corresponding author


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Abstract


The output characteristic of solar photovoltaic arrays vary nonlinearly when temperature or irradiation conditions change. For an efficient operation of the photovoltaic system, a control strategy based on the use of maximum power point tracking (MPPT) technique is essential. Over the past decades many MPPT techniques have been developed and published. In this paper an intelligent method using neural networks to track the maximum power point, for stand-alone photovoltaic system, is introduced.
Theoretical analysis of the work, carried out to develop and implement the MPPT controller, is presented. Attention has been also paid to the command of the power electronic converter to achieve maximum power point tracking. Simulation results, using Matlab/Simulink software, presented for this approach under rapid variation of irradiation and temperatures scenarios, confirm the effectiveness of the proposed method both in terms of efficiency and fast response time.
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Keywords


Maximum Power Point Tracking (MPPT); Photovoltaic System; Neural Networks; DC/DC Converter

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References


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