Application of Type 2 Fuzzy for Maximum Power Point Tracker for Photovoltaic System

Photovoltaic systems (PV) are becoming more popular as a way to make electricity because they offer so many benefits, such free solar irradiation harvest and low maintenance costs. Moreover, the system is environmentally friendly it neither emits noxious gases nor generates environmental noise. Consequently, during operation of PV system, working environment all types pollution. Despite aforementioned advantages, photovoltaic system’s performance significantly impacted by fluctuation in electrical charges from panel, shading conditions (PSC), weather conditions, others, which lowers efficiency. To operate modules at their peak power, maximum-power point tracking (MPPT) employed. As result various peaks present fluctuating irradiance, P-V curves become complex. Traditional methods, Perturb Observe (P O) have also failed monitor Global Maximum Power Point (GMPP), therefore usually live Local (LMPP), drastically efficiency systems. This study compares type 2 fuzzy logic (T2-FLC) with traditional Method three different scenarios temperature, factors, order track maximum power photovoltaics. Type 1 (T1-FLC) not appropriate for high level uncertainty (complex non-linear systems). By modelling vagueness unreliability information, better equipped deal linguistic uncertainties, thereby reducing ambiguity system. The terms four variables; efficiency, settling time, overshoot, proves that this strategy offers dependability, resilience. proposed algorithm further validated compared other techniques, include methods O). particle swarm (PSO) incremental conductance method results show (IT2FLC) than mentioned above.