The data is taken from Solar Power Data for Integration Studies | Grid Modernization | NREL[1] which are synthetic solar photovoltaic (PV) power plant data points for the United States representing the year 2006. We also use a US cities database[2].
The pupose of this work is to make data augmentation from this time series power generation profiles dataset in order to generate another simulated time series which has a specified installed peak power and still has the power generation fluctuations due to climate and seasonal weather.
Brief Description of the notebooks:
Here we download and shape all necesary files.
Here we get an idea of the overall dataset and the plant distribution int he US territory.
geographical_plotting.plants_visualization(geo_df_DPV, map_precision = 'states', BBox = (-125.00, -66.00, 24.20, 49.50), tech = 'DPV')
geo_df_UPV_labeled, centers_df_UPV = geographical_analysis.geographical_plant_clustering(geo_df_UPV, N_clusters = 100 ) geographical_plotting.plant_cluster_plotting(geo_df_UPV_labeled, centers_df_UPV, map_precision = 'states', BBox = (-125.00, -66.00, 24.20, 49.50), tech = 'UPV', coords = (-100,40))
Here we perform an analysis to a plant subset set in order to get the gain insight into how the rescaling is performed and how the different parameters are taken into account.
Here we combine and arrange all the necesary calculations in order to achieve the reescalement in a couple of lines of code.
UPV_plant_set.scale_signal(degree=3, data='max', MW_out=7, plot_hist=True)
