Resumen
The use of photovoltaic (PV) panels in interior spaces is expected to increase due to the proliferation of low-power sensor devices in the IoT domain. PV models are critical for estimating the I?V curves that define their performance at various light intensities. These models and the extraction of their parameters have been extensively studied under outdoor conditions, but their indoor illumination performance is less studied. With respect to the latter, several studies have used the parameter-scaling technique. However, the model?s accuracy degrades when the light level decreases. In this study, we propose a simple PV modeling technique that can be applied at various illuminance levels by only using characteristic points (short-circuit current, open-circuit voltage, and maximum-power voltage points) at a reference illumination level. The model uses the characteristic point translation technique to translate the reference characteristic points to other operating conditions. Then, parameter extraction technique is used to extract the model?s parameters. The proposed model?s accuracy is verified using two commercial PV panels and different indoor lighting technologies. The results indicate that the proposed model outperforms the other examined works in terms of accuracy, with an average improvement of 15.75%.