Nature-Inspired Algorithm-Based PID Controller for Maximum Power Point Tracking (MPPT) of Solar Photovoltaic Array

The increasing demand for renewable energy has heightened the need for effective solar power generation systems. One critical challenge in solar photovoltaic (PV) systems is the dynamic nature of environmental conditions, which affects the extraction of maximum power. To address this, MPPT technique...

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Bibliographic Details
Published in2024 2nd International Conference on Signal Processing, Communication, Power and Embedded System (SCOPES) pp. 1 - 6
Main Authors Tripathy, Debashis, Sahoo, Amit Kumar
Format Conference Proceeding
LanguageEnglish
Published IEEE 19.12.2024
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DOI10.1109/SCOPES64467.2024.10991017

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Summary:The increasing demand for renewable energy has heightened the need for effective solar power generation systems. One critical challenge in solar photovoltaic (PV) systems is the dynamic nature of environmental conditions, which affects the extraction of maximum power. To address this, MPPT techniques are employed. This paper presents a nature-inspired algorithm i.e. TLBO-based PID controller for efficient MPPT of solar PV arrays. The proposed approach integrates the robustness of nature-inspired optimization algorithms with the well-established control capabilities of PID controllers, ensuring optimal power extraction under varying irradiance and temperature conditions. The nature-inspired algorithms i.e. TLBO dynamically tune the PID controller parameters. These algorithms help overcome the limitations of conventional methods, providing faster convergence and reducing oscillations around the maximum power point. The results demonstrate that the TLBO based PID controller consistently tracks the maximum power point (MPP) with higher accuracy and stability than traditional MPPT methods. This creative method contributes to the wider adoption of clean energy technology by providing a dependable and affordable means of increasing the efficiency of solar PV installations.
DOI:10.1109/SCOPES64467.2024.10991017