DOI: 10.7763/IJCEE.2012.V4.454
Maximum Power Point Tracking Control for Photovoltaic System Using Neural Fuzzy
Abstract—At present around the world including Indonesia have an energy crisis that is necessary to find renewable energy as a replacement. One of renewable energy is solar energy that use photovoltaic (PV) system to convert into electrical energy. The weakness of this PV system is the low energy conversion efficiency. . To increase the efficiency of PV panels, it must operate around the maximum power point which is influenced by cell temperature and sun irradiation. A controller therefore is needed to determine MPP and control PV output voltage according MPP voltage although there change in temperature and sun irradiation. The aim of this paper is design neural fuzzy controller for control the PV system output voltage using the buck converter to operate at the MPP although occur disturbance with MATLAB/SIMULINK. Neural fuzzy define MPP point and the MPPT controlling done by adjusting the duty cycle of converter so that the PV array voltage remains at MPP operating point. In particular, the simulation of neural fuzzy will be discussed.
Index Terms—Neural Fuzzy, Photovoltaic, controller
The authors are with the Electronics Department Faculty of Electrical Engineering, Malang State Polytechnic, (e-mail: ikaputri_ratna@yahoo.com; e-mail; muhamad.arrifai@yahoo.co.id
Cite: Ratna Ika Putri and M. Rifa’i, "Maximum Power Point Tracking Control for Photovoltaic System Using Neural Fuzzy," International Journal of Computer and Electrical Engineering vol. 4, no. 1, pp. 75-81 , 2012.
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