The forecast service offers a short and medium term prediction of the solar resource, photovoltaic electricity production and other meteorological or derived variables that may be of interest to the customer.

The service may include actual measurements provided by the client that can be used to adjust the estimation model thanks to machine learning techniques.

Predictions can be provided in different ways and in different formats to suit customer needs.


Solar power plants require a reliable forecast of the availability of their production source: the Sun.

IRSOLAV offers this prediction with different time resolutions, different prediction horizons and adjustable update times.

The model used is based on a set of global and regional weather forecasting models and machine learning techniques that improves estimates.

For a very short term prediction, IRSOLAV has its own methodologies using satellite or cloud camera.


Both the photovoltaic solar plants and the agents that manage the energy discharged into the grid require a forecast of photovoltaic power generation for an optimized operation of their systems.

IRSOLAV offers this forecast of the production of individual or aggregate photovoltaic plants, being able to offer a regional or national estimate of the value.

Thanks to historical generation data provided by the customer, the deviation of forecasts can be significantly reduced using machine learning techniques.
Share by: