Abstract: Aiming at the problem that the output power of photovoltaic（PV） power is affected by a variety of factors, showing randomness and intermittency, which leads to the difficulty of accurately predicting PV output. A method of distributed PV output forecastmodel construction and optimization considering multiple real-time meteorological factors is proposed. Firstly, according to solar irradiance, temperature, wind speed, daily irradiation duration and relative humidity,the abnormal PV data return to by Newton interpolation, and the missing data are filled in to complete the preprocessing of PV data. On this basis,the characteristics of numerical weather prediction under uncertainties are quantitatively selected and the PV predictors are extracted based on fuzzy weighted convolutional neural network. Finally, a PV power output forecastmodel is constructed based on least square support vector regression, and the model is solved. The experimental results show that the research method has a very high precision for the prediction of distributed PV output.

Key words: multiple real-time meteorological factors, distributed photovoltaic(PV）, output forecast