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A Comparative Analysis of Different Maximum Power Point Tracking Algorithms of Solar Photovoltaic System

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Applications of Computing, Automation and Wireless Systems in Electrical Engineering

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 553))

Abstract

The demand for power is increasing day by day, and working with fossil fuels is associated with global warming problem, so renewable resource is better option to fulfil ever-increasing power demand without affecting climate. Among renewable resources, solar energy is widely adopted due to its availability in abundance. The power output for a solar photovoltaic (SPV) cell depends on the operating temperature, solar irradiation and load impedance. So maximum power point of SPV is not constant and keeps on changing under different conditions. Therefore, maximum power point tracking is used to uphold the point to extract maximum power from PV system under different working conditions. In this paper, we have described many maximum power point tracking algorithms commonly used for extracting maximum power out of a solar panel. We have also done a comparative analysis among them for various parameters using a common Simulink model in MATLAB. It has been found that among different methods, artificial intelligence method is most efficient compared to all existing methods and perform well under different conditions of solar irradiations and temperatures.

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Correspondence to Md. Sabir Hassan .

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Hassan, M.S., Mughal, S.N., Jarial, R.K., Sood, Y.R. (2019). A Comparative Analysis of Different Maximum Power Point Tracking Algorithms of Solar Photovoltaic System. In: Mishra, S., Sood, Y., Tomar, A. (eds) Applications of Computing, Automation and Wireless Systems in Electrical Engineering. Lecture Notes in Electrical Engineering, vol 553. Springer, Singapore. https://doi.org/10.1007/978-981-13-6772-4_20

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  • DOI: https://doi.org/10.1007/978-981-13-6772-4_20

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-13-6771-7

  • Online ISBN: 978-981-13-6772-4

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