Smart grid photovoltaic system pilot scale using sunlight intensity and state of charge (SoC) battery based on Mamdani fuzzy logic control

Kamil Faqih, Wahyu Primadi, Anik Nur Handayani, Ari Priharta, Kohei Arai

Abstract

The Utilization of renewable energy such as a photovoltaic system is the foremost alternative in transfers generated by conventional power plants, but the lack of photovoltaics is support for light intensity. The purpose of this research is to develop a pilot-scale smart grid photovoltaic system that can regulate the supply of electrical energy from either the battery or the power supply. The control system in this study uses the Mamdani fuzzy logic method in determining automatic system performance. This system monitors the intensity of light and battery which are then used as automatic safety parameters on the power supply, battery, and photovoltaic. The results of this study display the indicator results from the microcontroller in supplying electrical energy for the use of electrical loads, Power Supply has been served the load when the battery is in a low state which have a voltage <11 Volts, the battery has been served the load when the condition of the battery is in a medium and high condition which has a voltage of 11.5 <; ....; <13 Volts. PV has been served batteries or loads when the light intensity is cloudy and bright which have a light intensity of 3585 <; ...; <10752 Lux. This system can reduce dependence on conventional energy without reducing the quality of the energy supply at load and Photovoltaic system dependence on light intensity does not affect the supply of energy consumption to electrical loads.



Keywords


renewable energy; photovoltaic systems; fuzzy logic.

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References


I. Mathews, S. N. Kantareddy, T. Buonassisi, and I. M. Peters, “Technology and Market Perspective for Indoor Photovoltaic Cells,” Joule. 2019.

R. F. Arritt and R. C. Dugan, “Distribution system analysis and the future smart grid,” IEEE Trans. Ind. Appl., 2011.

A. P. Sakis Meliopoulos et al., “Smart grid technologies for autonomous operation and control,” IEEE Trans. Smart Grid, 2011.

R. Kappagantu, S. A. Daniel, and M. Venkatesh, “Analysis of Rooftop Solar PV System Implementation Barrier in Puducherry Smart Grid Pilot Project,” Procedia Technol., 2015.

Dr. Eng. A. Naba, “Belajar Cepat Fuzzy Logic Menggunakan MATLAB,” in Belajar Cepat Fuzzy Logic Menggunakan MATLAB, 2009.

I. Iancu, “A Mamdani Type Fuzzy Logic Controller,” in Fuzzy Logic - Controls, Concepts, Theories and Applications, 2012.

R. Khosravanian, M. Sabah, D. A. Wood, and A. Shahryari, “Weight on drill bit prediction models: Sugeno-type and Mamdani-type fuzzy inference systems compared,” J. Nat. Gas Sci. Eng., 2016.

N. Rai and B. Rai, “Control of fuzzy logic based PV-battery hybrid system for stand-alone DC applications,” J. Electr. Syst. Inf. Technol., 2018.

S. Lalouni and D. Rekioua, “Modeling and simulation of a photovoltaic system using fuzzy logic controller,” in Proceedings - International Conference on Developments in eSystems Engineering, DeSE 2009, 2009.

C. S. Chim, P. Neelakantan, H. P. Yoong, and K. T. K. Teo, “Fuzzy logic based MPPT for photovoltaic modules influenced by solar irradiation and cell temperature,” in Proceedings - 2011 UKSim 13th International Conference on Modelling and Simulation, UKSim 2011, 2011.

R. Ramaprabha, M. Balaji, and B. L. Mathur, “Maximum power point tracking of partially shaded solar PV system using modified Fibonacci search method with fuzzy controller,” Int. J. Electr. Power Energy Syst., 2012.

A. Ahmad and L. Rajaji, “Modeling and design of a novel control algorithm for grid connected photovoltaic (PV) inverter system,” in Proceedings - 2013 3rd International Conference on Advances in Computing and Communications, ICACC 2013, 2013.

E. Bernal A., M. Bueno-López, and F. Salazar-Caceres, “Fuzzy-Based Reactive Power Control for Smart PV Inverters in LV Distribution Systems,” IFAC-Pap., vol. 50, no. 1, pp. 7705–7710, Jul. 2017.

F. Chekired, A. Mahrane, Z. Samara, M. Chikh, A. Guenounou, and A. Meflah, “Fuzzy logic energy management for a photovoltaic solar home,” in Energy Procedia, 2017.

J. Sun, Y. P. Li, P. P. Gao, and B. C. Xia, “A Mamdani fuzzy inference approach for assessing ecological security in the Pearl River Delta urban agglomeration, China,” Ecol. Indic., 2018.

X. Li, T. Zhao, P. Fan, and J. Zhang, “Rule-based fuzzy control method for static pressure reset using improved Mamdani model in VAV systems,” J. Build. Eng., 2019.


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