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All Journal International Journal of Electrical and Computer Engineering Indonesian Journal of Electrical Engineering and Computer Science
Mohamed Seghir Boucherit
National Polytechnic School
Computer Science & IT Electrical & Electronics Engineering

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New improved hybrid MPPT based on neural network-model predictive control-kalman filter for photovoltaic system Nora Kacimi; Said Grouni; Abdelhakim Idir; Mohamed Seghir Boucherit
Indonesian Journal of Electrical Engineering and Computer Science Vol 20, No 3: December 2020
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijeecs.v20.i3.pp1230-1241

Abstract

In this paper, new hybrid maximum power point tracking (MPPT) strategy for Photovoltaic Systems has been proposed. The proposed technique for MPPT control based on a novel combination of an artificial neural network (ANN) with an improved model predictive control using kalman filter (NN-MPC-KF). In this paper the Kalman filter is used to estimate the converter state vector for minimized the cost function then predict the future value to track the maximum power point (MPP) with fast changing weather parameters. The proposed control technique can track the MPP in fast changing irradiance conditions and a small overshoot. Finally, the system is simulated in the MATLAB/Simulink environment. Several tests under stable and variable environmental conditions are made for the four algorithms, and results show a better performance of the proposed MPPT compared to conventional Perturb and Observation (P&O), neural network based proprtional integral control (NN-PI) and Neural Network based model predictive control (NN-MPC) in terms of response time, efficiency and steady-state oscillations.
A fast and accurate global maximum power point tracking controller for photovoltaic systems under complex partial shadings Adil Atoui; Mostefa Kermadi; Mohamed Seghir Boucherit; Khelifa Benmansour; Said Barkat; Fethi Akel; Saad Mekhilef
International Journal of Electrical and Computer Engineering (IJECE) Vol 13, No 1: February 2023
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.11591/ijece.v13i1.pp69-84

Abstract

The operating conditions of partially shaded photovoltaic (PV) generators created a need to develop highly efficient global maximum power point tracking (GMPPT) methods to increase the PV system performance. This paper proposes a simple, efficient, and fast GMPPT based on fuzzy logic control to reach the point of global maximum power. The approach measures the PV generator current in the areas where it is almost constant to estimate the local maximums powers and extracts the highest among them. The performance of this method is evaluated firstly by simulation versus four well-known recent methods, namely the hybrid particle swarm optimization, modified cuckoo search, scrutinization fast algorithm, and shade-tolerant maximum power point tracking (MPPT) based on current-mode control. Then, experimental verification is conducted to verify the simulation findings. The results confirm that the proposed method exhibits high performance for complex partial irradiances and can be implemented in low-cost calculators.
Co-Authors Abdelhakim Idir Adil Atoui Fethi Akel Khelifa Benmansour Mostefa Kermadi Nora Kacimi Saad Mekhilef Said Barkat Said Grouni