Skip to contents

Plot the occupancy duration curve

Source: R/charging_infrastructure.R
plot_occupancy_duration_curve.Rd

This term is based on the "load duration curve" and is useful to see the behavior of occupancy over the time in your charging installation. The steeper the curve, the shorter the duration that higher number of connections are sustained. Conversely, the flatter the curve, the longer the duration that higher number of connections are sustained. This information is crucial for various purposes, such as infrastructure planning, capacity sizing, and resource allocation.

Usage

plot_occupancy_duration_curve(
  sessions,
  dttm_seq = NULL,
  by = "Profile",
  resolution = 15
)

Arguments

sessions

tibble, sessions data set in standard format marked by {evprof} package

dttm_seq

sequence of datetime values that will be the datetime variable of the returned time-series data frame.

by

character, being 'Profile' or 'Session'. When by='Profile' each column corresponds to an EV user profile.

resolution

integer, time resolution (in minutes) of the sessions datetime variables. If dttm_seq is defined this parameter is ignored.

Value

ggplot

Examples

library(dplyr)

sessions <- head(evsim::california_ev_sessions_profiles, 100)
plot_occupancy_duration_curve(
  sessions,
  by = "Profile",
  resolution = 15
)
#> Warning: charging sessions have been aligned to 15-minute resolution.
#> # A tibble: 3,520 × 20
#>    Session Timeslot            Power PowerNominal EnergyRequired
#>    <chr>   <dttm>              <dbl>        <dbl>          <dbl>
#>  1 S1~1    2018-10-08 06:30:00   0.6          0.6           6.31
#>  2 S1~1    2018-10-08 06:45:00   0.6          0.6           6.31
#>  3 S1~1    2018-10-08 07:00:00   0.6          0.6           6.31
#>  4 S1~1    2018-10-08 07:15:00   0.6          0.6           6.31
#>  5 S1~1    2018-10-08 07:30:00   0.6          0.6           6.31
#>  6 S1~1    2018-10-08 07:45:00   0.6          0.6           6.31
#>  7 S1~1    2018-10-08 08:00:00   0.6          0.6           6.31
#>  8 S1~1    2018-10-08 08:15:00   0.6          0.6           6.31
#>  9 S1~1    2018-10-08 08:30:00   0.6          0.6           6.31
#> 10 S1~1    2018-10-08 08:45:00   0.6          0.6           6.31
#> # ℹ 3,510 more rows
#> # ℹ 15 more variables: ConnectionHoursLeft <dbl>, ID <int>,
#> #   ConnectionStartDateTime <dttm>, ConnectionEndDateTime <dttm>,
#> #   ChargingStartDateTime <dttm>, ChargingEndDateTime <dttm>, Energy <dbl>,
#> #   ConnectionHours <dbl>, ChargingHours <dbl>, ChargingStation <chr>,
#> #   Profile <chr>, FlexibilityHours <dbl>, UserID <chr>, Timecycle <fct>,
#> #   Cluster <chr>