No abstract

No abstract

No abstract

The short-term characteristics of utility-scale PV variability become increasingly important for power system operation as PV penetrations grow. However, understanding how these characteristics and their aggregated impacts will change with new PV deployments is challenging given the limited and highly site dependent availability of high-resolution PV output data. This study proposes a methodology to generate a synthetic 4 s utility-scale PV output time series for a PV plant anywhere in a power system using hourly satellite-derived irradiance data, which is globally available, to select a set of 4 s output from models created from four PV plants operating within the Australian national electricity market (NEM). The method resamples 4 s clear sky PV output index variability from statistical distributions which are binned according to hourly clear sky index pairs of global horizontal irradiance and direct normal irradiance. The method is cross-validated against the observations from the four utility PV plants located in different climate zones. The monthly Kolmogorov–Smirnov Integral (KSI) tests on the modeled variability distributions show that they are not statistically different from the observed time series with most KSI values remaining under 80%. Finally, the method is applied to all 20 utility PV plants that were registered in the NEM as of 2019. The modeled result shows good agreement with the measured aggregated 4 s variability. Hence, our method can be usefully applied for modeling the short-term variability of future power system scenarios with high PV penetrations if at least some existing utility PV plant generation data are available.

No abstract