Model Soiling

simulate_PV_time_series: Model for generating PV soiling time series described in Deceglie et. al. ‘Numerical Validation of an Algorithm for Combined Soiling and Degradation Analysis of Photovoltaic Systems’, Proceedings of the 2019 IEEE PVSC. simulate_PV_time_series_gaussian_soiling: Model for generating PV soiling time series with soiling rates that vary from day to day according to a Gaussian distribution (Åsmund) generate_my_soiling_signals: A function that generates 6 different time series based on the previous two functions. This was used to generate the datasets used in A. Skomedal, M. G. Deceglie, 2020, ‘Combined Estimation of Degradation and Soiling Losses in PV Systems’ Authors: Michael Deceglie and Åsmund Skomedal (Sep 2019)

solardatatools.model_soiling.generate_my_soiling_signals(high=0.02, low=0.01, num_years=10, index_form='Datetime')

solardatatools.model_soiling.half_one_matrix(size)

solardatatools.model_soiling.simulate_PV_time_series(first_date, last_date, freq='1D', degradation_rate=-0.005, noise_scale=0.01, seasonality_scale=0.01, nr_of_cleaning_events=120, soiling_rate_low=0.0001, soiling_rate_high=0.003, smooth_rates=False, random_seed=False)

solardatatools.model_soiling.simulate_PV_time_series_seasonal_soiling(first_date, last_date, freq='1D', degradation_rate=-0.005, noise_scale=0.01, seasonality_scale=0.01, nr_of_cleaning_events=120, soiling_rate_center=0.002, soiling_rate_std=0.001, soiling_seasonality_scale=0.9, random_seed=False, smooth_rates=False, seasonal_rates=False)

As the name implies, this function models soiling rates that vary from day to day according to a Gaussian distribution