Optimalisasi Pelacakan Daya Maksimum pada Panel Fotovoltaik menggunakan Firefly Algorithm dalam Kondisi Partial Shading - Jamiyanti, Eva; Pratama, Berwyn Fawaaz; Murobby, Ahmad Khoirul (Jurnal Sains dan Teknologi (JSIT), 2025)
The use of solar energy as an alternative energy source continues to increase along with global energy needs and environmental awareness. However, the efficiency of the photovoltaic (PV) panel system is greatly influenced by variations in sunlight intensity, especially in partial shading conditions. This condition causes the emergence of several local maximum power points, which makes it difficult for conventional MPPT (Maximum Power Point Tracking) systems to find the global maximum power point (GMPP). In this study, an MPPT method based on the Firefly Algorithm (FA) was developed, a metaheuristic optimization algorithm inspired by the behavior of fireflies in attracting partners through light intensity. This method was chosen because of its ability to explore non-linear search spaces and avoid traps at local maximum points. The study was conducted through modeling of the PV panel system and simulations in various partial shading scenarios using MATLAB/Simulink software. The Firefly Algorithm was then applied to search for the maximum power point and its performance was compared with conventional MPPT methods such as Perturb and Observe (P&O) and Incremental Conductance (IC). The discussion plan includes analysis of power tracking efficiency, convergence time, and system stability under changing lighting conditions. It is expected that the results of this study can contribute to the development of a more adaptive and efficient MPPT control system for modern solar power systems, especially in areas with high levels of shade.