Design and development of extract maximum power from single-double diode PV model for different environmental condition using BAT optimization algorithm

Author:

Thangamuthu Logeswaran1,Albert Johny Renoald2,Chinnanan Kalaivanan3,Gnanavel Banu4

Affiliation:

1. Department of EEE, Kongu Engineering College, Perundurai, Tamilnadu, India

2. Department of EEE, Erode Sengunthar Engineering College, Erode, Tamilnadu, India

3. Department of EEE, Sona PERT R&D Centre, Sona College of Technology, Salem, Tamilnadu, India

4. Department of EEE, VSB College of Engineering Technical Campus, Coimbatore, Tamilnadu, India

Abstract

To minimize real-time errors in a Photovoltaic (PV) system performances must be forecasted through precise simulation design before continuing into a practical application. However, due to the scarcity of data in datasheets and the inherent transcendental connections are between PV current and PV voltage, to determining the Single Diode Model (SDM) parameters becomes a more challenging problems. This paper offers a simulated study of a SDM and Double Diode Model (DDM) solar PV system under various irradiation represents, and the performance was developed by incorporating an optimization-based Maximum Power Point (MPP) tracking techniques. According to the present simulation presented in this article, a mathematical model for a SDM/DDM as well as optimization methodologies has been estimated MATLAB platform. The present MPP circuit model designed and compared with BAT optimization algorithms. The nonlinear relationship between Voltage (V) - Current (I) and Voltage (V) –Power (W) acknowledged as characteristic curves for different temperature (∘c) and irradiance (W/m2) values are verified in numerical simulation results. MPP tracking power and efficiency are examined for maximum power (Pmax) to test the optimization based system. The simulation results show that the BAT optimization model was achieved the highest tracking efficiency better than other heuristic algorithms.

Publisher

IOS Press

Subject

Artificial Intelligence,General Engineering,Statistics and Probability

Reference49 articles.

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