SCNN Based Electrical Characteristics of Solar Photovoltaic Cell Model

Purwahyudi, Bambang and Kuspijani, Kuspijani and Ahmadi, Ahmadi (2017) SCNN Based Electrical Characteristics of Solar Photovoltaic Cell Model. International Journal of Electrical and Computer Engineering (IJECE), 7 (6). pp. 3198-3206. ISSN p-ISSN 2088-8708, e-ISSN 2722-2578

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Abstract

Solar photovoltaic (PV) cell is one of the renewable energy sources and a main component of PV power systems. The design of PV power systems requires accurately its electrical output characteristics. The electrical characteristics of solar PV cell consist of I-V and P-V characteristics. They depend on the parameters of PV cell such as short circuit current, open circuit voltage and maximum power. Solar PV cell model can be described through an equivalent circuit including a current source, a diode, a series resistor and a shunt resistor. In this paper, the development solar PV cell model is built by using self constructing neural network (SCNN) methods. This SCNN technique is used to improve the accuracy of the electrical characteristic of solar PV cell model. SCNN solar PV cell model have three inputs and two outputs. They are respectively solar radiation, temperature, series resistance, current and power. The effectiveness of SCNN technique is verified using simulation results based on different physical and environmental conditions. Simulations are conducted by the change of the solar irradiation, temperature and series resistance. Simulation results show SCNN model can yield the I-V and P-V characteristics according to the characteristics of solar PV cell.

Item Type:	Article
Additional Information:	3.2 Scopus, Q2
Uncontrolled Keywords:	Solar photovoltaic cell Electrical characteristics Self constructing neural network Current-voltage characteristics Power-voltage characteristics
Subjects:	624 Civil Engineering
Divisions:	Faculty of Engineering > Bachelor of Electrical Engineering
Depositing User:	Perpus Ubhara Surabaya
Date Deposited:	05 Oct 2022 05:59
Last Modified:	14 Feb 2023 06:30
URI:	http://eprints.ubhara.ac.id/id/eprint/1409

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