Output power attenuation rate prediction for photovoltaic panels considering dust deposition in hazy weather

Photovoltaic (PV) power prediction is a key technology to improve the control and scheduling performance of PV power plant and ensure safe and stable grid operation with high-ratio PV power generation. In recent years, the frequent occurrence of hazy weather has seriously influence on the output power of PV panels, aiming at this problem, output power attenuation characteristic test is implemented for PV panels with dust deposition, by taking PM accumulated concentration and installation angle as input variables, a output power attenuation rate prediction model for PV panels is proposed based on BP neural network. Experiment result indicates that the presented BP neural network prediction model has the virtues of high precision and good generalization ability.