ANN based MPPT Algorithm Design using Real Operating Climatic Condition
Mohammed Salah Bouakkaz, Ahcene Boukadoum, Omar Boudebbouz, Ahmed Bouraiou, Nadir Boutasseta, Issam Attoui
Abstract
Maximum Power Point Tracking (MPPT) controller is an indispensable component to ensure the transfer of maximum energy from the photovoltaic generator to the load. In this paper, an intelligent MPPT based on Artificial Neural Network (ANN) is designed using Real Operating Conditions and implemented in Matlab/Simulink. The algorithm gives a reference operating point to a Step-up DC-DC converter with the objective of reaching the Maximum Power Point (MPP) in photovoltaic energy generation system. Simulation results prove the capability of the ANN-MPPT algorithm in tracking the MPP rapidly and accurately with low ripple.
Topics & Concepts
Maximum power point trackingPhotovoltaic systemMaximum power principleComputer scienceControl theory (sociology)MATLABRippleComponent (thermodynamics)Controller (irrigation)Power (physics)Operating pointArtificial neural networkControl engineeringEngineeringElectronic engineeringControl (management)Electrical engineeringArtificial intelligenceInverterBiologyPhysicsOperating systemAgronomyThermodynamicsQuantum mechanicsPhotovoltaic System Optimization TechniquesSolar Radiation and Photovoltaicssolar cell performance optimization