A Two-Tier Comparison Study of Three MPPT Control Algorithms for a PV-Powered Smart Greenhouse

Abstract

In this research work, three maximum power point tracking (MPPT) control algorithms based on power feedback are applied to two types of converters, namely Zeta and buck-boost, in the photovoltaic (PV) system. The PV system is intended to guarantee the power supply to a remote smart greenhouse. The control algorithms investigated are perturb and observe (P&O), incremental conductance (IncCond), and fuzzy logic (FLC) methods. Their performance are investigated and compared for each converter. It is found that the maximum power is always achieved, even during abrupt changes in irradiation or/and in temperature. The three methods have shown to have good performance; fast response time and very low steady-state error, with minor preference of the P&O method where the output voltage followed the input with high efficiency. The comparative study revealed that the power response time of the PV generator under stable conditions (constant irradiance and constant temperature) for P&O and IncCond was longer in the buck-boost converter than in the Zeta. On the other hand, the ripple level was better for the buck-boost. For the FLC, the maximum power was reached in a shorter time (short response time) with the smallest ripple. As for operation under variable environmental conditions, the Zeta outperformed the buck-boost for each control technique.

Keywords

• dc-dc power converters
• fuzzy logic
• maximum power point trackers
• photovaltaic systems