Abstract
This work is aimed at analysing the impact of real-time weather forecasting on the simulation of solar thermal electricity plants. A novel method is presented that allows generating random solar radiation profiles to assess the uncertainty of forecasting solar thermal electricity production. Rather than a weather prediction model, this work proposes a fast and simple method for the generation of synthetic solar radiation data that focuses on the dynamics relevant for electricity production, not requiring long historical data series or meteorological details. Variable window lengths are used to reproduce the growing uncertainty of forecasts with longer time horizons. In addition, a simplified model of solar thermal power plant is described and implemented in MATLAB®. Both the solar profile generator and the plant model are used to simulate massive cases for four representative days with eight forecasting hours based on electricity markets. The results show uncertainty values for day-ahead predictions from 15% to 60% in cloudy days and from 2% to 40% in sunny days, with decreasing ranges for intra-day forecasts.
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