specify_elect_heat_markets.Rd
This function specifies electricity and heat markets. See details for more information.
specify_elect_heat_markets(
.tidy_iea_df,
country = IEATools::iea_cols$country,
method = IEATools::iea_cols$method,
energy_type = IEATools::iea_cols$energy_type,
last_stage = IEATools::iea_cols$last_stage,
year = IEATools::iea_cols$year,
ledger_side = IEATools::iea_cols$ledger_side,
flow_aggregation_point = IEATools::iea_cols$flow_aggregation_point,
flow = IEATools::iea_cols$flow,
product = IEATools::iea_cols$product,
e_dot = IEATools::iea_cols$e_dot,
unit = IEATools::iea_cols$unit,
transformation_processes = IEATools::aggregation_flows$transformation_processes,
negzeropos = ".negzeropos"
)
The .tidy_iea_df
for which electricity and heat markets need to be specified.
See IEATools::iea_cols
.
The name of transformation processes in the data frame. Default is IEATools::aggregation_flows$transformation_processes.
Temporary column name. Default is ".netzeropos".
Returns a .tidy_iea_df
with specified electricity and heat markets.
This function specifies electricity and heat markets by selecting production flows (V matrix) of:
"Electricity [
from Oil products]
", "Electricity [
from Coal products]
", "Electricity [
from Natural gas]
",
"Electricity [
from Other products]
", "Electricity [
from Renewables]
", and "Electricity [
from Nuclear]
.
and routing them as inputs to a new industry: "Electricity market". The electricity market industry then produces
"Electricity" in the same amount that it receives as input.
Exactly the same process is conducted for heat.
A_B_path <- system.file("extdata/A_B_data_full_2018_format.csv", package = "ECCTools")
IEATools::load_tidy_iea_df(A_B_path) %>%
IEATools::specify_all() %>%
specify_elect_heat_markets()
#> # A tibble: 102 × 11
#> Country Method Energy.type Last.stage Year Ledger.side
#> <chr> <chr> <chr> <chr> <dbl> <chr>
#> 1 A PCM E Final 2018 Consumption
#> 2 A PCM E Final 2018 Consumption
#> 3 A PCM E Final 2018 Consumption
#> 4 A PCM E Final 2018 Consumption
#> 5 A PCM E Final 2018 Consumption
#> 6 A PCM E Final 2018 Consumption
#> 7 A PCM E Final 2018 Consumption
#> 8 A PCM E Final 2018 Consumption
#> 9 A PCM E Final 2018 Consumption
#> 10 A PCM E Final 2018 Consumption
#> # ℹ 92 more rows
#> # ℹ 5 more variables: Flow.aggregation.point <chr>, Flow <chr>, Product <chr>,
#> # Unit <chr>, E.dot <dbl>