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Comparative Assessment of P&O, PSO Sliding Mode, and PSO-ANFIS Controller MPPT for Microgrid Dynamics

Mohammed Yassine Dennai, Hamza Tédjini, Abdelfatah Nasri

2024Elektronika ir Elektrotechnika11 citationsDOIOpen Access PDF

Abstract

This paper compares different maximum power point tracking (MPPT) control strategies in microgrid dynamics, focussing on perturb and observe (P&O), adaptive neuro-fuzzy inference system (ANFIS), particle swarm optimisation (PSO), and PSO sliding mode controller techniques. The study investigates their performance under varying microgrid conditions, considering factors like weather and load variations. The simulation results provide a detailed comparative analysis of the power at the point of common coupling (PCC) for MPPT techniques at different time intervals. Both the P&O and PSO sliding mode recorded a power output of 287 kW, while PSO-ANFIS achieved a slightly higher power output of 294 kW. At 2.5 seconds, the P&O method recorded a power output of 712 kW, while the PSO sliding mode and the PSO-ANFIS techniques achieved 717 kW and 738 kW, respectively. Overall, the PSO-ANFIS technique consistently outperformed the other methods in terms of power output, demonstrating its effectiveness in maximising energy extraction and adaptability to dynamic conditions. These findings provide valuable insights for designing and implementing MPPT controllers in microgrid systems, emphasising the efficiency of the hybrid PSO-ANFIS technique in enhancing the overall performance and stability of renewable energy systems.

Topics & Concepts

Adaptive neuro fuzzy inference systemMicrogridControl theory (sociology)Particle swarm optimizationMaximum power point trackingController (irrigation)Power (physics)Photovoltaic systemComputer scienceEngineeringControl engineeringFuzzy logicFuzzy control systemRenewable energyVoltageInverterControl (management)Artificial intelligenceAgronomyBiologyMachine learningPhysicsElectrical engineeringQuantum mechanicsMicrogrid Control and OptimizationSmart Grid Energy ManagementFrequency Control in Power Systems