A novel method for performance estimation of photovoltaic module without setting reference condition

In traditional methods, the process of performance estimation of a photovoltaic (PV) module is achieved through two steps. First, the model parameters are determined under some reference condition, and then, the model parameters are determined under varying operating conditions based on the reference values and the dependence of the model parameters on environmental conditions. This paper presents a novel method for the performance estimation of PV modules under varying operating conditions without setting a reference condition. In the proposed method, the dependence of the model parameters on environmental conditions is modeled and modified without setting a reference condition or using reference values. The model parameters are determined from experimental data using guaranteed convergence particle swarm optimization technology, and are suitable for all operating conditions. Thus, the performance of PV modules can be directly determined under varying operating conditions, which simplifies the process and improves the accuracy. The effectiveness and accuracy of the proposed method are validated by large amounts of experimental data for different types of PV modules at different locations. In comparison with the traditional methods, the proposed method exhibits better accuracy in terms of the I-V and P-V curve and maximum power point estimation under different irradiance and temperature conditions. It can be further used to estimate the output power of PV system under varying operating conditions.

Automated summary

A novel method for performance estimation of PV modules under varying operating conditions without setting a reference condition is proposed in this paper. The method models and modifies the dependence of model parameters on environmental conditions, and uses guaranteed convergence particle swarm optimization technology to determine the model parameters from experimental data. The proposed method shows better accuracy in estimating the I-V and P-V curves and maximum power point under different irradiance and temperature conditions compared to traditional methods, and can be further applied to estimate the output power of PV systems.