Electric Vehicle Charging Sessions Profiling and Modelling

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Documentation for package ‘evprof’ version 1.1.2

• DESCRIPTION file.
• User guides, package vignettes and other documentation.
• Package NEWS.

Help Pages

choose_k_GMM	Visualize BIC indicator to choose the number of clusters
cluster_sessions	Cluster sessions with 'mclust' package
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'
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
read_ev_model	Read an EV model JSON file and convert it to object of class 'evmodel'
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