Evaluating PWM Solar Charge Regulators for Off-Grid Solar PV Street Lighting Systems Using Linear Regression Approach

The global adoption of solar-powered streetlights has grown significantly, driven by their cost-effectiveness and potential to reduce dependence on fossil fuels associated with conventional street lighting. Battery storage represents a substantial portion of the total capital cost in solar-powered streetlight systems. Therefore, selecting an efficient charge regulator is crucial to protect battery lifespan and reduce energy losses. In this context, the choice of an appropriate charge regulator plays a vital role in enhancing system reliability and overall performance. This study presents a practical approach for evaluating three commercially available 6 A-rated Pulse Width Modulation (PWM) solar charge regulators intended for recharging lead-acid batteries in a proposed 12 V off-grid solar photovoltaic (PV) street lighting system. The regulators were evaluated concurrently in separate circuits, each experiencing similar meteorological conditions, including similar temperature and solar irradiance. The measured data for each regulator were acquired using LabVIEW-based virtual instruments. The performance comparison was conducted using the Linear Regression Algorithm (LRA) to support decision-making. Based on the analysis, the most suitable PWM charge regulator was identified as the one offering the best charging performance due to low internal losses. Hence, solar battery charge regulators with identical load current ratings do not necessarily deliver equivalent charge/discharge performance.

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Publication Details

Journal
Energies
Published
2025-10-28
DOI
https://doi.org/10.3390/en18215646
Primary Topic
Impact of Light on Environment and Health
Type
article
Field-Weighted Citation Impact
0.00
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article

Evaluating PWM Solar Charge Regulators for Off-Grid Solar PV Street Lighting Systems Using Linear Regression Approach

Sandile Phillip Koko, Mbuyu Sumbwanyambe, Xolani Yokwana
Energies
Impact of Light on Environment and Health
article

Evaluating PWM Solar Charge Regulators for Off-Grid Solar PV Street Lighting Systems Using Linear Regression Approach

Sandile Phillip Koko, Mbuyu Sumbwanyambe, Xolani Yokwana
article en

Abstract

The global adoption of solar-powered streetlights has grown significantly, driven by their cost-effectiveness and potential to reduce dependence on fossil fuels associated with conventional street lighting. Battery storage represents a substantial portion of the total capital cost in solar-powered streetlight systems. Therefore, selecting an efficient charge regulator is crucial to protect battery lifespan and reduce energy losses. In this context, the choice of an appropriate charge regulator plays a vital role in enhancing system reliability and overall performance. This study presents a practical approach for evaluating three commercially available 6 A-rated Pulse Width Modulation (PWM) solar charge regulators intended for recharging lead-acid batteries in a proposed 12 V off-grid solar photovoltaic (PV) street lighting system. The regulators were evaluated concurrently in separate circuits, each experiencing similar meteorological conditions, including similar temperature and solar irradiance. The measured data for each regulator were acquired using LabVIEW-based virtual instruments. The performance comparison was conducted using the Linear Regression Algorithm (LRA) to support decision-making. Based on the analysis, the most suitable PWM charge regulator was identified as the one offering the best charging performance due to low internal losses. Hence, solar battery charge regulators with identical load current ratings do not necessarily deliver equivalent charge/discharge performance.

EnergiesVol. 18(21)
University of South Africa (ZA)
Openalex Percentile: Top 71%
Impact of Light on Environment and Health
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Evaluating PWM Solar Charge Regulators for Off-Grid Solar PV Street Lighting Systems Using Linear Regression Approach — Sandile Phillip Koko, Mbuyu Sumbwanyambe, et al. · Energies (2025) | TGRS Research Map | TGRS