Summarise a result variable across technology variants

Aggregates a solved variable over the variants of each base technology and reports the spread across them: total, mean, standard deviation, min and max, plus the number of variants contributing. This is the "analyse by cluster and vintage" view – e.g. the spread of capacity factors across wind resource clusters, or of capacity across vintages.

Usage

variantSummary(object, name, by = character(), weight = NULL, ...)

Arguments

object

a solved scenario.

name

character, name of the variable or parameter (e.g. "vTechCap").

by

character vector, variant dimensions to keep as grouping columns: any of "vintage" and "cluster". Empty (default) summarises across all variants of a base technology.

weight

optional character, name of a variable to use as weights for the mean (e.g. "vTechCap" to capacity-weight a per-unit quantity). When NULL the mean is unweighted.

...

further filters passed to getData() (e.g. year = 2050).

Value

A data.frame with the grouping columns plus n, total, mean, sd, min and max.

See also

Other technology process: getVariants(), newTechnology(), read_technology_xlsx(), write_technology_xlsx()

Examples

if (FALSE) { # \dontrun{
open_project(tempdir())

ek  <- topia$modules$electricity$R3
mod <- newModel("TOPIA", data = ek$repo,
                calendar = topia$modules$calendars$s4_h24,
                region = ek$regions,
                horizon = topia$modules$horizons$base,
                discount = 0.05)
mod <- setGeoscale(mod, ek$geoscale)

# split wind into site grades, solve, then read the result BY GRADE rather
# than by variant name
mod  <- add(mod, ek$EWIN_SITES, overwrite = TRUE)
scen <- solve_model(mod, name = "SITES", solver = solver_options$glpk)

variantSummary(scen, "vTechCap", by = "cluster")
variantSummary(scen, "vTechOut", by = c("cluster", "region"))
} # }