Methods for online identification of photovoltaic module ageing by series resistance from measured current–voltage curves

Abstract

Photovoltaic (PV) modules are prone to ageing and degradation during their lifespan. Ageing of PV cells damages them permanently, thus impairing their electrical performance and causing significant economic losses. Thus, ageing must be detected in time. Condition of the PV modules can be monitored by analyzing current–voltage curves measured from the PV modules by fitting a mathematical model, such as the widely-used single-diode model, to the curves. The magnitude and drift of the model parameters provide information of the condition of the modules. Specifically, increments in the series resistance parameter values indicate ageing-like degradation that hinders the optimal utilization of the power system. Only few single-diode model parameter identification methods presented in literature are applicable in practical PV sites. However, it is unclear which of these methods performs best in PV cell ageing detection and quantification. This article addresses this issue by comparing the ageing detection capabilities of these methods. In this spirit, a novel single-diode model parameter identification method is developed that suits even better for real-case PV systems. It is shown that the accuracy of ageing detection depends on the selected parameter identification method as well as on the ageing level of the PV modules.