An adaptive current–voltage step size solver for accurate and efficient modeling of solar photovoltaic modules
- 1Department of Applied Sciences and Social Studies, Arusha Technical College, Arusha, Tanzania
- 2School of Materials, Energy, Water and Environmental Sciences (MEWES), The Nelson Mandela African Institution of Science and Technology (NM-AIST), Arusha, Tanzania
Abstract
Accurate modeling of photovoltaic (PV) modules is critical for system design, energy yield prediction, and maximum power point tracking (MPPT). Conventional single-diode models (SDM) provide a balance between simplicity and physical realism but require iterative numerical methods to solve the implicit current–voltage (I–V) equation, often leading to slow convergence and reduced stability under dynamic conditions. This paper introduces a novel adaptive current–voltage step-size solver (AIVSS) that dynamically adjusts both voltage and current increments based on the local slope of the I–V curve, thereby improving numerical accuracy and convergence efficiency. The proposed method was validated through 500 simulations under standard test conditions (STC), partial shading, high temperature, and dynamic irradiance, and was compared with the conventional adaptive voltage-step solver (AVSS). Performance was evaluated using mean absolute error (MAE), root mean square error (RMSE), iteration count, and computation time. Results show that AIVSS reduced the average iteration count by 35–40%, decreased the average MAE from 6.15 W to 2.18 W, and reduced the average RMSE from 7.68 W to 2.85 W across all operating conditions. In addition, the proposed method achieved faster convergence and smoother dynamic response under rapidly changing irradiance. These findings confirm the strong potential of AIVSS for real-time PV system simulation and MPPT applications, providing a robust and computationally efficient tool for accurate PV module characterization.
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BibTeX
@article{mlazi2026adaptive,
title = {{An adaptive current–voltage step size solver for accurate and efficient modeling of solar photovoltaic modules}},
author = {Nsulwa John Mlazi and Baraka Kichonge},
journal = {PLOS One},
year = {2026},
month = oct,
doi = {10.1371/journal.pone.0359796},
url = {https://doi.org/10.1371/journal.pone.0359796},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - An adaptive current–voltage step size solver for accurate and efficient modeling of solar photovoltaic modules
AU - Nsulwa John Mlazi
AU - Baraka Kichonge
PY - 2026
DA - 2026/10/06
JO - PLOS One
DO - 10.1371/journal.pone.0359796
UR - https://doi.org/10.1371/journal.pone.0359796
AB - Accurate modeling of photovoltaic (PV) modules is critical for system design, energy yield prediction, and maximum power point tracking (MPPT). Conventional single-diode models (SDM) provide a balance between simplicity and physical realism but require iterative numerical methods to solve the implicit current–voltage (I–V) equation, often leading to slow convergence and reduced stability under dynamic conditions. This paper introduces a novel adaptive current–voltage step-size solver (AIVSS) that dynamically adjusts both voltage and current increments based on the local slope of the I–V curve, thereby improving numerical accuracy and convergence efficiency. The proposed method was validated through 500 simulations under standard test conditions (STC), partial shading, high temperature, and dynamic irradiance, and was compared with the conventional adaptive voltage-step solver (AVSS). Performance was evaluated using mean absolute error (MAE), root mean square error (RMSE), iteration count, and computation time. Results show that AIVSS reduced the average iteration count by 35–40%, decreased the average MAE from 6.15 W to 2.18 W, and reduced the average RMSE from 7.68 W to 2.85 W across all operating conditions. In addition, the proposed method achieved faster convergence and smoother dynamic response under rapidly changing irradiance. These findings confirm the strong potential of AIVSS for real-time PV system simulation and MPPT applications, providing a robust and computationally efficient tool for accurate PV module characterization.
SN - 1932-6203
ER -