We propose an artificial neural network for photovoltaic energy forecasting.

We analyze its sensitivity with respect to the input data sets and error definitions.

Data are taken from experimental activities carried out on a real photovoltaic plant.

The hourly energy prediction covers all the daylight hours of the following day.