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Design and hardware implementation of FLMPPT control of PV systems based on GA and small-signal analysis

This paper presents a cost effective control algorithm for standalone batteryless photovoltaic (PV) systems. The control is driven by a Fuzzy-based maximum power point tracker (MPPT) which has the capabilities to maintain high energy conversion efficiency under different weather and load conditions. General design considerations are presented based on the linearization of the dynamic model of the entire system which consists of PV panel, Cuk converter and motor load. For our particular Fuzzy-MPPT controller, these design considerations are combined with an artificial intelligent technique to achieve the optimum control design. Furthermore, the developed control algorithm has voltage regulation capability to protect the load from overvoltage during light load conditions and a fast digital overload protection. The transient and steady state performance of the entire system were modeled by non-linear state-space representation. The proposed control is simulated in MatLab and experimentally tested under the fast variation of climatic conditions for verification purposes. A very good agreement has been shown between theoretical, simulations and experimental results.