Build multi-year demand from a base-year profile and growth factors

grow_demand() is the transparent core: it takes a demand object whose @demand table holds a base-year profile (region x timeslice, optionally year-keyed) and a plain growth-factor table, and writes one profile per factor year — demand * factor, keyed by year. Nothing else changes: the shape is the base year's, the factors are whatever table you pass (tyndp_demand filtered to one scenario is one such table, but any (country|region, year, factor) data frame works).

Usage

grow_demand(dem, factors, base_year = 2025)

build_demand(
  name = NULL,
  factors,
  base_year = 2025,
  years = NULL,
  regions = NULL,
  from = reneuro::pypsa_eur_41
)

Arguments

dem

A demand object.

factors

Data frame with columns year, factor, and either region (matched exactly) or country (matched to the first two letters of the region code).

base_year

Year of the base profile in dem@demand. Rows with that year (or with year NA, the year-agnostic form) are the shape that grows; base-year demand is reproduced exactly where factor == 1.

name

Name for the built demand object (default: keep the source object's name).

years

Optional years to keep (subset of factors$year); NULL uses every year in factors.

regions

Optional region codes to keep.

from

Source model holding the base-year demand (default pypsa_eur_41).

Value

The demand object with a year-keyed @demand table.

Details

build_demand() is the convenience wrapper: it pulls a demand object out of a source model, optionally renames it and restricts it to regions, and applies grow_demand() for the requested years.

Examples

if (FALSE) { # \dontrun{
ga <- subset(tyndp_demand, scenario == "GA")
d  <- grow_demand(getObjects(pypsa_eur_41)$DEM_ELC, ga, base_year = 2025)
} # }