<![CDATA[The utilization of solar energy is an important solution in meeting renewable energy needs, especially in Indonesia which has high irradiation potential. However, photovoltaic (PV) systems face challenges in the form of irradiation fluctuations and partial shading effects that reduce efficiency. To overcome this, a reliable Maximum Power Point Tracking (MPPT) algorithm is needed. This study analyzes the performance of the Queen Honeybee Migration (QHBM) algorithm in tracking the maximum power point (MPP) under uncertain irradiation conditions in the Tulungagung region, using a Monte Carlo simulation approach. Simulations were conducted using MATLAB in two scenarios: standard conditions (1000 W/m²) and fluctuating conditions based on historical data. Results show that the QHBM achieves 99.98% efficiency with the fastest convergence time (5 iterations) under STC conditions, as well as an average efficiency of 98.99% (normal) and 97.86% (abnormal) under fluctuating conditions. In addition, the system successfully charged the battery, with SOC increasing by 0.038% (optimal) and 0.026% (volatile). The QHBM algorithm is proven to be adaptive to irradiation dynamics and superior to GWO, PSO, and P&O, making it a potentially effective solution for PV systems operating under changing irradiation conditions throughout the day]]>
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