  Owing to the growing concern of global warming and over-dependence on fossil
fuels, there has been a huge interest in last years in the deployment of
Photovoltaic (PV) systems for generating electricity. The output power of a PV
array greatly depends, among other parameters, on solar irradiation. However,
solar irradiation has an intermittent nature and suffers from rapid
fluctuations. This creates challenges when integrating PV systems in the
electricity grid and calls for accurate forecasting methods of solar
irradiance. In this paper, we propose a triple exponential-smoothing based
forecasting methodology for intra-hour forecasting of the solar irradiance at
future lead times. We use time-series data of measured solar irradiance,
together with clear-sky solar irradiance, to forecast solar irradiance up-to a
period of 20 minutes. The numerical evaluation is performed using 1 year of
weather data, collected by a PV outdoor test facility on the roof of an office
building in Utrecht University, Utrecht, The Netherlands. We benchmark our
proposed approach with two other common forecasting approaches: persistence
forecasting and average forecasting. Results show that the TES method has a
better forecasting performance as it can capture the rapid fluctuations of
solar irradiance with a fair degree of accuracy.
