Spatio-temporal variability of solar radiation is the main variable affecting the photovoltaic power feed-in to the grid. Clouds are the main source of such variability and their velocity is a principal input to most short-term forecast models. The main goal in this study is to estimate cloud speed using radio-metric data using measurements from 8 sensors located at the UC San Diego Solar Energy test bed.
Two different methods were developed to estimate the cloud speed based on the correlation between the signals from different sensors. Our analysis showed good agreement between both methods. Additional measurements from nearby METAR and radiosonde stations also show comparable results. Both methods require high variability in the input radiation.
