<![CDATA[Solar energy is a promising renewable energy source; however, its efficiency is highly dependent on constantly changing environmental conditions such as solar irradiance and temperature. The non-linear output characteristic of solar panels results in a single, dynamic Maximum Power Point (MPP), necessitating a Maximum Power Point Tracking (MPPT) algorithm to maximize the energy harvest. This research aims to analyze and compare the energy efficiency of two commonly used MPPT algorithms: Perturb and Observe (P&O) and Incremental Conductance (IncCond). The research method employed is a quantitative simulation using MATLAB/Simulink software, where both algorithms were tested on an identical photovoltaic (PV) system model under three irradiance scenarios: constant, step-change, and ramp-change conditions. The simulation results demonstrate that the Incremental Conductance algorithm consistently outperforms the Perturb and Observe algorithm. IncCond exhibited a higher tracking efficiency (reaching 99.6%) with superior stability under steady-state conditions, as well as a faster and more accurate dynamic response during sudden changes in irradiance. In conclusion, the IncCond algorithm is proven to be more reliable and efficient for maximizing energy production, making it the more recommended choice for photovoltaic system applications, especially in tropical regions with high weather variability, such as Medan, Indonesia.]]>
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