Divya, R and Pavithra, C V (2023) Investigation of various solar MPPT techniques in solar panel. In: Machine Learning and the Internet of Things in Solar Power Generation. CRC Press, Boca Raton, pp. 55-74. ISBN 9781003302964
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Abstract
Partial shading of solar panels diminishes their operating efficiency and energy synthesized as it disrupts the uniform absorption of sunlight. To tackle the issue of partial shading in photovoltaic (PV) systems, this article puts forward a comprehensive control strategy that takes into account a range of contributing factors. The proposed control approach is based on using multi-string PV system configuration in place of a central-type PV inverter for all PV modules with a single DC-DC converter. This adaptation enhances overall efficiency across varying radiation levels. Also, the proposed technique minimizes the overall system cost by reducing the required sensors number by utilizing a radiation estimation strategy. The converter switching strategy is synthesized considering direct duty-cycle control method to establish the maximum power point (MPP) location on the P–V curve. The direct duty-cycle tracking approach simplifies the control system and improves the system’s response during sudden partial shading restrictions. To validate the effectiveness of the suggested MPPT method, two system configurations were constructed using MATLAB/SIMULINK software and assessed under various partial shading scenarios. Additionally, a multi-string system was subjected to real irradiance conditions. The sensor-less MPPT algorithm proposed achieved an impressive system efficiency of 99.81% with a peak-to-peak ripple voltage of 1.3V. This solution offers clear advantages over alternative approaches by reducing tracking time and enhancing system efficiency. The system findings undoubtedly support the theoretical scrutiny of the intended technique.
Item Type: | Book Section |
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Subjects: | D Electrical and Electronics Engineering > Solar Energy |
Divisions: | Electrical and Electronics Engineering |
Depositing User: | Users 5 not found. |
Date Deposited: | 12 Jul 2024 11:33 |
Last Modified: | 12 Jul 2024 11:33 |
URI: | https://ir.psgitech.ac.in/id/eprint/750 |