Two-Stage Maximum Power Point Tracking Photovoltaic Converter for IoT Sensor Nodes with Hardware Validation

Continuous operation is increasingly expected of Internet of Things (IoT) and wireless sensor network (WSN) nodes, yet practical solar front ends must account for source variability, intermediate storage, conversion losses, sensing overhead, and battery-management constraints. This article develops and evaluates a discrete, two-stage photovoltaic front end for such nodes: a perturb-and-observe (P&O) buck stage tracks the maximum power point of a 20 W Solarland SLP020-12U module (rated 17.2 V, 1.16 A) and feeds an intermediate storage bus, while a PI-compensated SEPIC stage regulates the IoT rail to 3.2 V independently of that bus voltage. Closed-loop MATLAB/Simulink simulations are reported at 1000, 800, and 600 W/m2. The reported conversion figures originate from an idealized switching model and should therefore be interpreted as simulation-only values rather than measured prototype efficiency. A low-cost Arduino-based prototype confirms correct switching behavior and a 20.0048 kHz PWM signal, but the available captures lack synchronized, calibrated input/output power logging; consequently, no hardware efficiency, MPPT tracking efficiency, regulation error, ripple, or settling-time figure is claimed. The revised manuscript makes this simulation-to-hardware boundary explicit, adds the power cost of sensing and data conversion to the loss discussion, strengthens the battery-management and deployment caveats, and defines the measurements required for full quantitative validation.

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Publication Details

Journal
Energies
Published
2026-09-04
DOI
https://doi.org/10.3390/en19174195
Primary Topic
Photovoltaic System Optimization Techniques
Type
article
Field-Weighted Citation Impact
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article

Two-Stage Maximum Power Point Tracking Photovoltaic Converter for IoT Sensor Nodes with Hardware Validation

Hafiz Furqan Ahmed, Mohsin Jamil, Qasim Awais, Muhammad Hammas
Energies
Photovoltaic System Optimization Techniques
article

Two-Stage Maximum Power Point Tracking Photovoltaic Converter for IoT Sensor Nodes with Hardware Validation

Hafiz Furqan Ahmed, Mohsin Jamil, Qasim Awais, Muhammad Hammas
article en

Abstract

Continuous operation is increasingly expected of Internet of Things (IoT) and wireless sensor network (WSN) nodes, yet practical solar front ends must account for source variability, intermediate storage, conversion losses, sensing overhead, and battery-management constraints. This article develops and evaluates a discrete, two-stage photovoltaic front end for such nodes: a perturb-and-observe (P&O) buck stage tracks the maximum power point of a 20 W Solarland SLP020-12U module (rated 17.2 V, 1.16 A) and feeds an intermediate storage bus, while a PI-compensated SEPIC stage regulates the IoT rail to 3.2 V independently of that bus voltage. Closed-loop MATLAB/Simulink simulations are reported at 1000, 800, and 600 W/m2. The reported conversion figures originate from an idealized switching model and should therefore be interpreted as simulation-only values rather than measured prototype efficiency. A low-cost Arduino-based prototype confirms correct switching behavior and a 20.0048 kHz PWM signal, but the available captures lack synchronized, calibrated input/output power logging; consequently, no hardware efficiency, MPPT tracking efficiency, regulation error, ripple, or settling-time figure is claimed. The revised manuscript makes this simulation-to-hardware boundary explicit, adds the power cost of sensing and data conversion to the loss discussion, strengthens the battery-management and deployment caveats, and defines the measurements required for full quantitative validation.

EnergiesVol. 19(17)
Memorial University of Newfoundland (CA), National Sun Yat-sen University (TW), Brock University (CA), Fatima Jinnah Women University (PK)
Affordable and clean energy
Openalex Percentile: Top 28%
Photovoltaic System Optimization Techniques
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