Classify thermosensitivity from daily load data

Estimate thermosensitivity using the residential rule based on the ratio between mean winter load and mean summer load.

Usage

elcf4r_classify_thermosensitivity(
  data,
  id_col = "entity_id",
  date_col = "date",
  value_col = "y",
  threshold = 1.5,
  winter_months = c(12L, 1L, 2L),
  summer_months = c(6L, 7L, 8L)
)

Arguments

data

Data frame containing at least an identifier, a date and a load column. Long-format panels are accepted and are aggregated to mean daily load before classification.

id_col

Name of the entity identifier column.

date_col

Name of the date column.

value_col

Name of the load column.

threshold

Ratio threshold above which the series is classified as thermosensitive. Defaults to 1.5.

winter_months

Integer vector of winter months.

summer_months

Integer vector of summer months.

Value

A data frame with one row per entity and columns winter_mean, summer_mean, ratio, thermosensitive, and status.

Examples

example_ts <- data.frame(
  entity_id = rep("home_1", 4),
  date = as.Date(c("2024-01-10", "2024-01-11", "2024-07-10", "2024-07-11")),
  y = c(12, 11, 6, 5)
)
elcf4r_classify_thermosensitivity(example_ts)
#>   entity_id winter_mean summer_mean    ratio threshold thermosensitive status
#> 1    home_1        11.5         5.5 2.090909       1.5            TRUE     ok
#>   n_winter_days n_summer_days
#> 1             2             2