  This paper presents a parametric model approach to address the problem of
photovoltaic generation forecasting in a scenario where measurements of
meteorological variables, i.e., solar irradiance and temperature, are not
available at the plant site. This scenario is relevant to electricity network
operation, when a large number of PV plants are deployed in the grid. The
proposed method makes use of raw cloud cover data provided by a meteorological
service combined with power generation measurements, and is particularly
suitable in PV plant integration on a large-scale basis, due to low model
complexity and computational efficiency. An extensive validation is performed
using both simulated and real data.
