A user-friendly and accurate machine learning tool for the evaluation of the worldwide yearly photovoltaic electricity production

Evaluation of technical and financial benefits of battery energy storage system control strategies

“…Daily and yearly data have been used in this study to get better results. First daily data was used to make sense of the system, and daily data was used again to include selling excess PV production to the grid, but in both of these scenarios using only daily data has not been precisely fruitful because irradiation changes through the year which causes PV production through the year [42].…”

Time-Dependent Photovoltaic Performance Assessment on a Global Scale Using Artificial Neural Networks

“…The reduced brightness coefficients F ′ 1 and F ′ 2 are functions of sky clearness ε and sky brightness Δ parameters that can be calculated with Eqs. ( 8) and (9).…”

“…They found a large application in the energy system field in the last decades [5][6][7]. ANNs possess the ability to learn intricate patterns and relationships within vast datasets, allowing them to capture the nonlinear and time-varying behaviors inherent in solar energy systems [8][9][10][11]. However, the large dependency of PV power on weather conditions brings a major challenge of uncertainty to system operation and efficiency [12].…”