Photovoltaic output power performance assessment and forecasting: Impact of meteorological variables

Meteorological variables have an important effect on the performance of a grid-connected photovoltaic station, in this paper, the impact of meteorological variables on the 6 mWp grid-connected photovoltaic station in the desert of Adrar has been explored through performance assessment and output power forecasting. The impact of the meteorological variables on performance parameters has been investigated by performing interdependence and correlation studies. A clear interdependence between some variables has been observed, but the complete separation between each variable correlation effect has proven to be a difficult task. A combination of random forest method and pre-processing techniques namely feature selection and Principal component analysis has been developed in order to predict power production using meteorological variables as inputs. The forecasting models have been evaluated in terms of computation time, accuracy, and several statistical indicators.

Automated summary

Meteorological variables have a significant impact on the performance of grid-connected photovoltaic stations in desert areas. The study found clear interdependence and correlations between performance parameters and meteorological variables. A forecasting model using random forest method and preprocessing techniques showed promising results in predicting power production based on meteorological inputs, with evaluation based on computation time, accuracy, and statistical indicators.