Solar irradiance forecasting using spatial-temporal covariance structures and time-forward kriging

Electricity power grid operations require information about demand and supply on a variety of timescales and areas. The advent of significant generation contributions by time variable renewable energy sources means that forecasting methods are increasingly required. Some of the earliest requirements will be for spatial-temporal estimation of solar irradiance and the resulting photovoltaic-generated electricity. Accurate forecasts represent an important step towards building a smart grid for renewable energy driven cities or regions, and to this end we develop forecasting tools that use data from ground-based irradiance sensors.

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