Solar irradiation shows natural variability in the range of 1 minute or up to 1 second due to cloud cover and especially cloud movement. Nevertheless, in photovoltaic solar power plant simulations only 1 hourly resolved irradiation datasets are typically used. The presentation will investigate the impact of temporally higher resolved natural variability for a private home with a photovoltaic system with battery storage. Self-consumption and the number of needed battery storage cycles are quantified and deviations when using 1 min resolved production and demand time series compared to hourly irradiation and demand time series are derived.
Such 1 min resolved irradiation time series are nowadays neither available operationally from numerical weather models nor from geostationary meteorological satellite observations. Therefore, an automatic method was developed to derive artifical timeseries with the same statistical properties as known from 1 minute resolved ground-based observations at the same location.
Based on a reference database of time series belonging to different variability classes (Schroedter-Homscheidt et al., 2018) and satellite-based structural cloud parameters (Wey and Schroedter-Homscheidt, 2014) a neural network was trained. Such satellite-based structure parameters are available at any location in the satellite field of view in Europa, Middle East, and Africa for 2004 onwards. Based on these satellite observations of clouds, the variability classification can be derived and finally, a stochastic time series generator selects and adapts 1 min time series out of the reference database to generate artifical irradiation time series with correct statistical parameters as the historgram of irradiation values and the ramps of irradiation from minute to minute. This has been tested with various stations of the Baseline Surface Radiation Network (BSRN).
References: Marion Schroedter-Homscheidt, Miriam Kosmale, Sandra Jung, and Jan Kleissl. Classifying ground-measured 1 minute temporal variability within hourly intervals for direct normal irradiances. Meteorologische Zeitschrift, 01 2018.
Etienne Wey and Marion Schroedter-Homscheidt. APOLLO Cloud Product Statistics. In R. Pitchumani, editor, SolarPACES 2013 International Conference, volume 49 of Energy Procedia, pages 2414–2421. Elsevier, 2014.
Sebastian Schreck. Implications of Sub-Hourly Solar Radiation Variability on Decentralized Energy Systems – Generation of Synthetic Time Series and Model-Based Assessment, Masterarbeit, Univ. Stuttgart, 2018