Optimalisasi Stand-Alone Photovoltaic System dengan Implementasi Algoritma P&O-Fuzzy MPPT

Dimas Juniyanto, Tatyantoro Andrasto, Suryono Suryono


The need for electrical energy continues to increase every time. Concerns about the depletion of fossil energy reserves encourage the acceleration of the development of renewable energy use. One of renewable energy is the solar energy. Due to the irreversible irradiation conditions, it takes controls to keep the solar panel's maximum power. The most widely in Maximum Power Point Tracking (MMPT) is Perturb Algorithm and Observe (P&O) but P&O Algorithm has deficiency of oscillations when steady state and MPP trace errors when irradiation changes rapidly. In this paper proposed P & O-Fuzzy algorithm is a modification of conventional P & O to improve the efficiency of solar panels. This research uses Matlab for simulation and hardware implementation using microcontroller Arduino Uno and buck converter topology. The result of simulation and hardware implementation, conventional P & O has an average efficiency of 85.03% while MPPT modification with P & O-Fuzzy algorithm can improve MPP tracking efficiency with 89.67%.


MPPT; P&O; Fuzzy; Arduino; Matlab

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D. Choudhary dan A. R. Saxena, DC-DC Buck-Converter for MPPT of PV System, IJETAE 4(7): 813-821, 2014.

S. C. Hipparagi dan D. K. Prasanna, Maximum Power Point Tracker for PV Solar Panels Using SEPIC Converter, IJSR 4(5): 403-407, 2015.

S.M. Cinar dan E. Akarslan, On the Design an Intelligent Battery Charge Controller for PV Panels, JESTR 5(4): 30-34, .2012.

Z. El Khadmiri, et al, A Novel Solar tracker Bassed on Omnidirectional Computer Vision, Journal of Solar Energy 2015(149852): 1-6, 2015.

M.S. Ait Cheik, C. Larbes, G.F. Tchoketch Kebir, dan A. Zerguerras, Maximum Power Point Tracking using Fuzzy Logic Control Scheme, Revue des Energies Renouvelables 10(3): 387-395, 2007.

D. K. Sharma dan G. Purohit, Advanced Perturbation and Observation (P&O) based Maximum Power Point Tracking (MPPT) of Solar Photo-Voltaic System, Conference Paper IEEE.1-5, 2012.

T. Esram dan P. L. Chapman, Comparison of Photovoltaic Array Maximum Power Point Tracking Techniques, IEE Transaction on Energy Conversion 22(2): 439-449, 2007.

A.K Abdelsalam, M.M. Ahmed, S. Ahmed, dan N.E.Prasad, High-Performance Adaptive Perturb and Observe MPPT Technoque for photovoltaic-Based Microgrid, IEEE Transactions on Power Electronics 26(4), 1010-1021, 2011.

B. Bendip, F. Krim, H. Belmili, M. F. Almi, dan S. Boulouma, Advanced Fuzzy MPPT Controller for a stand-alone PV system, International Conference on Technologies and Materias for Renewable Energy, Environment and Sustainability, Energy Procedia 50(2014): 383-392 2014.

R. Arulmurugan dan N. S. Vanitha, Intellegent Fuzzy MPPT Controller using Analysis of DC to DC Novel Buck Converter for Photovoltaic Energy System Applications, Proceedings of the 2013 International Conference on Pattern Recognition, Informatics and Mobile Engineering, IEEE, 21-22, 2013.

S. Selvan, K. J. M. Feros, V. Umayal, dan M. Indumathi, Simulation of Fuzzy Logic Control Based MPPT Technique for Photovoltaic System, International Conference on Inovations in Engineering and Technology, 10-14, 2014.

A. Subiyanto, Mohamed dan M. A. Hannan, Iintelligent photovoltaic Maximum Power Point Tracking Controller for Energy Enhancement in Renewable Energy System, Journal of Renewable Energy 2013(901962): 1-9.

Saidi, Ahmed dan C. Benachaiba, Comparison of IC and P&O algoritms oin MPPT for Grid Conected PV Module, International Conference on Modeling, Identification and Control (ICMIC), IEEE, 213-218, 2016.

F. L. Tofoli, P. D. D. Castro, dan W. J. D. Paula, Comparative Study of Maximum Power Point Tracking Technique for Photovoltaic System, International Journal of Photoenergy 2015(812582): 1-10, 2015.

DOI: https://doi.org/10.15294/jte.v10i1.14108


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