Power Performance Evaluation of a New MPPT Control Design Based on Synergetic Adaptive Control Optimized by PSO Algorithm for a Photovoltaic System
Keywords:
Synergetic adaptive control, Maximum power point tracking, PSO algorithm, Photovoltaic system, Power transfer optimization.Abstract
This study introduces an innovative approach to maximizing power point tracking (MPPT) within solar power systems, utilizing a synergetic adaptive control (SAC) mechanism. The setup includes a solar panel, a DC-DC boost converter, a resistive load, and a synergetic adaptive controller. The control system operates on a two-loop framework; the first loop identifies the peak voltage from the solar panel, providing a baseline for the second loop. This secondary loop, a sophisticated synergetic adaptive controller, maintains the system's closed-loop equilibrium by employing Lyapunov's principle. The optimization of the controller's settings is achieved through the particle swarm optimization (PSO) method. Tailored to maintain optimal power production under a range of environmental conditions, this method's effectiveness and dependability were verified through detailed mathematical simulations of a solar power system in Matlab/Simulink under varying climate scenarios. The outcomes of the simulations strongly validate the effectiveness of the proposed method.
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