MPPT Method Supported by Particle Swarm Optimization for Increasing Power Efficiency in Solar Energy Systems
Abstract
With the increasing global interest in renewable energy sources, enhancing the power generation capacity of photovoltaic (PV) systems has become a critical research focus. Due to the continuously changing environmental conditions such as solar irradiance and temperature accurate and real-time tracking of the Maximum Power Point (MPP) is essential for efficient energy conversion. In this study, a Particle Swarm Optimization (PSO)-based approach is proposed to improve the accuracy and response speed of the Maximum Power Point Tracking (MPPT) process. Compared to conventional MPPT algorithms, the proposed method demonstrates more stable performance and significantly enhances the overall energy efficiency of the system. Simulation results show that the PSO-assisted MPPT algorithm provides rapid response under transient conditions and exhibits reduced oscillations in steady-state operation. Accordingly, the proposed method offers an effective and reliable solution for real-time implementation in photovoltaic systems.
Keywords
Particle Swarm Optimization, Maximum Power Point Tracking, Photovoltaic Systems, Renewable Energy, Energy Efficiency
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