Electric Vehicle Charging Sessions Profiling and Modelling


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Documentation for package ‘evprof’ version 1.0.0

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choose_k_GMM Visualize BIC indicator to choose the number of clusters
cluster_sessions Cluster sessions with 'mclust' package
convert_time_dt_to_num Convert datetime value to numeric (hour-based)
convert_time_dt_to_plot_dt Modify datetime values according evprof.start.hour
convert_time_dt_to_plot_num Convert datetime values to sorted numeric values considering a start time
convert_time_num_to_chr Convert numeric time value (hour-based) to character hour in %H:%M format
convert_time_num_to_period Convert numeric time value to a datetime period (hour-based)
convert_time_num_to_plot_num Modify numeric time value according to a time sequence start time
cut_sessions Cut outliers based on minimum and maximum limits of ConnectionHours and ConnectionStartDateTime variables
define_clusters Define each cluster with a user profile interpretation
detect_outliers Detect outliers
divide_by_disconnection Divide sessions by disconnection day
divide_by_timecycle Divide sessions by time-cycle
drop_outliers Drop outliers
get_charging_rates_distribution Get charging rates distribution in percentages
get_connection_models Get a tibble of connection GMM for every user profile
get_daily_avg_n_sessions Get the daily average number of sessions given a range of years, months and weekdays
get_daily_n_sessions Get daily number of sessions given a range of years, months and weekdays
get_dbscan_params Get the minPts and eps values for DBSCAN to label only a specific percentage as noise
get_energy_models Get a tibble of energy GMM for every user profile
get_ev_model Get the EV model object of class 'evmodel'
mutate_to_log Logarithmic transformation to ConnectionStartDateTime and ConnectionHours variables
plot_bivarGMM Plot Bivariate Gaussian Mixture Models
plot_density_2D Density plot in 2D, considering Start time and Connection duration as variables
plot_density_3D Density plot in 3D, considering Start time and Connection duration as variables
plot_division_lines Iteration over evprof::plot_division_line function to plot multiple lines
plot_energy_models Compare density of estimated energy with density of real energy vector
plot_histogram Histogram of a variable from sessions data set
plot_histogram_grid Grid of multiple variable histograms
plot_kNNdist Plot kNNdist
plot_model_clusters Plot all bi-variable GMM (clusters) with the colors corresponding to the assigned user profile. This shows which clusters correspond to which user profile, and the proportion of every user profile.
plot_outliers Plot outlying sessions
plot_points Scatter plot of sessions
print_connection_models_table Get LaTeX code for the connection bivariate GMM features (mu and sigma)
print_user_profile_energy_models_table Get LaTeX code for the energy GMM features OF A SINGLE USER PROFILE (mu and sigma)
read_ev_model Read an EV model JSON file and convert it to object of class 'evmodel'
round_to_half Round numeric time value to half hour basis.
round_to_interval Round to nearest interval
save_clustering_iterations Save iteration plots in PDF file
save_ev_model Save the EV model object of class 'evmodel' to a JSON file
set_profiles Classify sessions into user profiles
summarise_sessions Statistic summary of sessions features