  We describe a simple and succinct methodology to develop hourly
auto-regressive moving average (ARMA) models to forecast power output from a
photovoltaic solar generator. We illustrate how to build an ARMA model, to use
statistical tests to validate it, and construct hourly samples. The resulting
model inherits nice properties for embedding it into more sophisticated
operation and planning models, while at the same time showing relatively good
accuracy. Additionally, it represents a good forecasting tool for sample
generation for stochastic energy optimization models.
