Solar Photovoltaic Parameter Extraction for Three Different Technologies Using Particle Swarm Optimization Method

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Schematic experimental setup of PV module measurement system [20]
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Published: Jun 14, 2023
DOI: https://doi.org/10.17762/ijritcc.v11i6s.6967
Keywords:
photovoltaic, root mean square error, amorphous silicon, multi crystalline silicon, hetero junction with intrinsic thin layer, module temperature, particle swarm optimization, standard test condition

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Krupali Kanekar
Electrical Department, Sandip University, Nashik, India Electronics and Telecommunication Engg, Ramrao Adik Institute of Technology, D. Y. Patil Deemed to be University, Navi Mumbai, India
Prakash Burade
Electrical Department, Sandip University, Nashik, India
Diraj Magare
Electronics and Telecommunication Engg, Ramrao Adik Institute of Technology, D. Y. Patil Deemed to be University, Navi Mumbai, India

Abstract

Industry and academia are becoming more interested in solar energy. The problem of providing an alternative to fossil fuels and limiting the environmental damage brought on by their emissions is what has brought about this increased focus. Solar photovoltaic is the subject of a growing number of studies. The goal of the current investigation is to investigate how various technological modules namely single junction amorphous silicon (a-Si), Hetero junction with Intrinsic Thin-layer (HIT) and multi crystalline silicon (mc-Si) are affected by seasonal spectrum variation respond to Indian climatic circumstances. Compared to many other nations, the entire Indian subcontinent has a relatively distinct climate with distinct seasonal patterns. The four seasons that are considered in this study are summer, winter, monsoon, and post monsoon. The impact of each season varies on the spectrum. Such a study will be helpful to measure the parameter connected to the spectrum and assess its impact on the effectiveness of the PV array. In order to conduct accurate performance investigations, the extraction of the right circuit model parameters is essential. The estimation of the solar PV parameter is done by using Particle swarm optimization (PSO) algorithm.

Article Details

How to Cite
Kanekar, K. ., Burade, P. ., & Magare, D. . (2023). Solar Photovoltaic Parameter Extraction for Three Different Technologies Using Particle Swarm Optimization Method. International Journal on Recent and Innovation Trends in Computing and Communication, 11(6s), 568–574. https://doi.org/10.17762/ijritcc.v11i6s.6967
Issue
Vol. 11 No. 6s (2023): Advances in Computational Modeling and Simulation of Computing Systems
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Articles

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