A fuzzy logic controlled solar tilt angle optimization for renewable energy applications

This paper examines the improvement of the performance of photovoltaic (PV) panel by means of introducing fuzzy logic controller (FLC) that simultaneously determines the best tilt angle and implements maximum power point tracking (MPPT). Traditional PV systems have fixed tilt, or they install expensive trackers, an aspect that makes them have reduced energy production under changing irradiance and temperature. The suggested structure uses the FLC to dynamically regulate the tilt on the angle and to maximize the power generation in the real-time, by introducing the measurement of solar irradiance and temperature online. We use a buck-boost DC-DC converter to implement voltage control wherein the modulation of a buck-boost controller duty cycle is a fuzzy rule-based design. The one-year simulation showed tilt angle of 9.4 o in June and 39.4 o in December. The designed MPPT algorithm achieved an average efficiency of 89.25% whereas the peak power measured 17.84W. This value was lower than the targeted 19.82W, but still, it is a 20% better result in comparison to the classic Perturb and Observe (P&O) MPPT algorithm. Such results validate the fuzzy logic control based PV system as a low-cost, adaptive, and intelligent alternative to a static or mechanically tracking system. Comparison (in relation to traditional Perturb and Observe (P&O) algorithms) has shown a steady increase in harvested power by 20% over a one-year period. These findings point to strength, flexibility, and overall exaltation of this proposed FLC-based PV control system in promoting solar energy harvesting.