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Arithmetic optimization algorithm based maximum power point tracking for grid-connected photovoltaic system

M. A. Ebrahim, Shymaa Nasser Ahmed, Mohamed Eladly Metwally

2023Scientific Reports49 citationsDOIOpen Access PDF

Abstract

This paper suggests an optimal maximum power point tracking (MPPT) control scheme for a grid-connected photovoltaic (PV) system using the arithmetic optimization algorithm (AOA). The parameters of the proportional-integral (PI) controller-based incremental conductance (IC) MPPT are optimally selected using AOA. To accomplish this study, a 100-kW benchmark PV system connected to a medium distribution utility is constructed and analyzed employing MATLAB/SIMULINK. The optimization framework seeks to minimize four standard benchmark performance indices, then select the best of the best among them. To verify the efficacy of the recommended methodology, a comprehensive comparison is conducted between AOA-based PI-IC-MPPT, modified incremental conductance MPPT (MIC), grey wolf optimization (GWO), genetic algorithm (GA), and particle swarm optimization (PSO)-based MPPT. The proposed control approach has achieved a reduction of 61, 3, 4.5, and 26.9% in the rise time and a decrease of 94, 84.7, 86.6, and 79.3% in the settling time compared with MIC, GWO, GA, and PSO in extracting MPPT of the proposed system, respectively.

Topics & Concepts

Maximum power point trackingPhotovoltaic systemBenchmark (surveying)Particle swarm optimizationSettling timeMATLABControl theory (sociology)Computer scienceGenetic algorithmInterior point methodController (irrigation)Maximum power principleAlgorithmGridMathematical optimizationPower (physics)MathematicsEngineeringControl (management)Control engineeringInverterStep responseArtificial intelligenceBiologyAgronomyElectrical engineeringPhysicsGeographyGeometryOperating systemGeodesyQuantum mechanicsPhotovoltaic System Optimization TechniquesMicrogrid Control and Optimizationsolar cell performance optimization
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