Chen Zhang

TL;DR: A novel method based on the power-law model (PLM) is proposed to model and characterize the electrical properties of PV modules under various operating conditions, making it scalable for direct online application.

TL;DR: A novel method combining an artificial neural network (ANN) with an explicit analytical model (EAM) is proposed for predicting the I-V characteristics of PV modules under different operating conditions, which makes it efficient to obtain theI-V curves from the estimated model parameters due to its simplicity and explicit expression.

TL;DR: In this article, an explicit expression of voltage in terms of current is derived from the implicit I-V expression of the single-diode model for a single PV cell under different environmental conditions.

TL;DR: In this article, a new integrated current-voltage error criterion, named EC-I&V(x), which takes into account the intrinsic I-V properties of the PV module, is proposed.

TL;DR: In this article, a method and a system for predicting working characteristics of photovoltaic cell under different illumination temperature conditions is presented, where the shape parameters of the mathematical model under the reference condition are solved firstly, and then according to the relationship between shape parameters and physical parameters, combined with the law of the physical parameters changing with temperature and light, the relation between the shape parameter and the temperature and the light is obtained, which is brought into the light temperature to be predicted, then the working characteristics can be obtained under the predicted condition.