Abstract: Aiming at the performance evaluation for the fault and abnormality detection of the photovoltaic (PV) array and utilizing the theory of prognostic and health management and data mining, the health state evaluation of the PV array based on the current-voltage (Ⅰ-Ⅴ) characteristics and grey relational analysis is proposed in this paper. First, the simulation model of the PV array is studied, and the simulation speed is improved by numerical calculation. Then, the particle swarm optimizer is used to extract the model parameters. Besides, the grey correlation analysis is used to evaluate the health state of the PV array. Further the health index is figured up, which quantitatively describes the health state of the PV array. The simulation and experimental results show that the proposed method for evaluating the health state of the PV array is effective and can accurately describe the health state of PV array. It is helpful in guiding the maintenance and ensuring the safe operation of the PV plant.