A Fuzzy Inference Model for Efficient Power Stabilization Model in PV Systems

Assistant Professor, Department of Electrical, Kalinga University, Naya Raipur, Chhattisgarh, India .

^* ku.shaileshmadhavraodeshmukh@kalingauniversity.ac.in
^** ku.raviprakashmahobia@kalingauniversity.ac.in

Abstract

The power stabilization in photovoltaic systems is well studied. There exist number of approaches in stabilizing the output power of PV systems. The most approaches concern about the input power and residual energy of capacitors. Still they suffer to achieve higher performance in power stabilization. To handle this issue, an efficient Fuzzy inference based Power stabilization model (FIPSM) is presented in this paper. The model is focused on utilizing residual energy on different circuits and avoiding higher drain of energy on any of the circuit. The model fabricated with MOFSET device in each circuit which monitors the input and output voltage of any circuit. As the model has number of circuits framed in serial connection, the method generates fuzzy rules based on the conditions of different circuits for different input voltage with output voltage required. At each duty cycle, the method reads the input voltage and identifies set of circuits were in sleep or charging mode. With the list of circuits, the method computes the Fuzzy Inference Voltage Stabilization Support (FIVSS) for various circuits. Based on the value of FIVSS, the method identifies a unique or a subset of circuits to support stabilization. The proposed model improves the performance of power stabilization in photovoltaic systems.