Comparison Study Between Improved JAYA and Particle Swarm Optimization PSO Algorithms for Parameter Extraction of Photovoltaic Module Based on Experimental Test - Archive ouverte HAL
Article Dans Une Revue Recent Patents on Engineering Année : 2021

Comparison Study Between Improved JAYA and Particle Swarm Optimization PSO Algorithms for Parameter Extraction of Photovoltaic Module Based on Experimental Test

Farid Kadri
  • Fonction : Auteur

Résumé

Background: The need for a diagnosis today, becomes a necessity for variable speed AC drives in several industrial applications. An important research axis is oriented towards monitoring the state of the converter supplying the electric motor. Indeed, the voltage source inverter is likely to have switching faults. Therefore, an emergency stop of the motor drive must be done. Objective: After reviewing related patents and works, the objective of this paper is to identify the feasibility of fault detection and diagnosis in a three-phase inverter feeding an induction motor. Methods: The proposed approach is a simple threshold fault classification method applied to fault diagnosis of a Direct Torque Control (DTC) induction motor drive using the stator Concordia mean current vector. With a fault occurrence, a localization domain consisting of seven patterns is constructed. Results: Simulated results on 1.5-kW induction motor drive show the effectiveness of the proposed approach with a good classification performance. Conclusion: The classification performance of our simple diagnosis system is acceptable for one fault occurrence compared to other methods. Faulty switch detection and identification is completed within a few periods of current. Using intelligent technique should improve classification performances for multiple faults occurrence.
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Dates et versions

hal-03643928 , version 1 (17-04-2022)

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Citer

Mohamed Assaad Hamida, Farid Kadri. Comparison Study Between Improved JAYA and Particle Swarm Optimization PSO Algorithms for Parameter Extraction of Photovoltaic Module Based on Experimental Test. Recent Patents on Engineering, 2021, Lecture Notes in Networks and Systems, 174 (4), pp.210-221. ⟨10.1007/978-3-030-63846-7_21⟩. ⟨hal-03643928⟩
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