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Climatic sensorless maximum power point tracking based on adaptive neuro-extremum seeking control technique in PV generation systems

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Abstract

For several decades renewable energies such as solar energy have been increasing popularity in autonomous power generation. One of the major problems found in solar generation systems is the maximum power transfer from the photovoltaic panel (PV) to the load. Thus, various maximum power point tracking (MPPT) techniques have been developed in the literature to deal with inevitable variations of irradiation, temperature and shading. This paper presents a new control strategy based on the combination of an extremum seeking control (ESC) technique with a nonlinear neuro-adaptive method to achieve the Maximum Power Point Tracking (MPPT) in photovoltaic systems. In this new method, a RBF-neuro observer is used to estimate unknown PV system parameters (i.e. irradiation and temperature) and derive an optimal voltage signal. Then this signal is fed into a modified ESC to ensure a satisfactory MPPT, despite the varying atmospheric conditions. A detailed stability of the proposed combined approach is analysed using root locus theories. The effectiveness and the capability of the proposed MPPT approach are assessed, through numerical simulations using MATLAB/Simulink software, and compared to those of the modified ESC without the adaptive neuronal observer and the P &O algorithm under varying operating conditions. The proposed controller features the smallest maximum power tracking RMSE (2.4672) and highest power efficiency (0.98) while the P &O method exhibits the highest maximum power tracking RMSE (3.5877) and smallest power efficiency (0.953). A real time implementation is also carried out using Arduino Mega board to demonstrate the feasibility of the proposed method.

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Authors and Affiliations

  1. Unité de Recherche d’Automatique et d’Informatique Appliquée (UR-AIA), Département de Génie Electrique IUT FOTSO Victor Bandjoun, Université de Dschang, B.P. 134, Bandjoun, Cameroon

    Arnaud Flanclair Tchouani Njomo, René Kuate-Fochie, Rostand Marc Douanla, Lionel Leroy Sonfack & Godpromesse Kenne

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  1. Arnaud Flanclair Tchouani Njomo
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  2. René Kuate-Fochie
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  3. Rostand Marc Douanla
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Correspondence to Arnaud Flanclair Tchouani Njomo.

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Tchouani Njomo, A.F., Kuate-Fochie, R., Douanla, R.M. et al. Climatic sensorless maximum power point tracking based on adaptive neuro-extremum seeking control technique in PV generation systems. Energy Syst (2023). https://doi.org/10.1007/s12667-023-00606-y

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