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Improve COL electricity generation in the IEA's WEEB.

fix_COL_WRLD_electricity.Rd

The 2022 release of the IEA's WEEB data is different from the 2021 release of the IEA's WEEB data in terms of Colombia's Electricity generation. For example:

  • 2021 release:

    • Main activity producer electricity plants 34196.4008 TJ

    • Autoproducer electricity plants: 2671.1993 TJ

  • 2022 release:

    • Main activity producer electricity plants 31467.5994 TJ

    • Autoproducer electricity plants: 899.9987 TJ Similar differences appear in all years 1971 - 1977. From 1978 onward, the 2021 and 2022 releases agree. Note that this change leads to overall energy imbalance for Colombia 1971-1977 and World 1971-1977. This function reverts to the values from the 2021 release of the IEA WEEB.

Usage

fix_COL_WRLD_electricity(
  .tidy_iea_df,
  country = IEATools::iea_cols$country,
  year = IEATools::iea_cols$year,
  e_dot = IEATools::iea_cols$e_dot
)

Arguments

.tidy_iea_df

A tidy IEA data frame produced by load_tidy_iea_df().

country, year, e_dot

See IEATools::iea_cols.

Value

.tidy_iea_df with improved Ghana Industry Electricity, if warranted.

Details

Similarly, World Electricity is different 2021 release to 2022 release. The 2022 data are unbalanced for 1971 –> 1977. This function reverts to the value from the 2021 release of the IEA WEEB for World Electricity in 1971–1977.

Examples

library(dplyr)
example_tidy_iea_df <- load_tidy_iea_df() %>% 
  dplyr::filter(Country == "GHA") |> 
  dplyr::mutate(
    # Pretend that GHA is COL.
    Country = "COL"
  )
example_tidy_iea_df
#> # A tibble: 122 × 11
#>    Country Method EnergyType LastStage  Year LedgerSide FlowAggregationPoint    
#>    <chr>   <chr>  <chr>      <chr>     <dbl> <chr>      <chr>                   
#>  1 COL     PCM    E          Final      1971 Supply     Total primary energy su…
#>  2 COL     PCM    E          Final      2000 Supply     Total primary energy su…
#>  3 COL     PCM    E          Final      1971 Supply     Total primary energy su…
#>  4 COL     PCM    E          Final      2000 Supply     Total primary energy su…
#>  5 COL     PCM    E          Final      1971 Supply     Total primary energy su…
#>  6 COL     PCM    E          Final      2000 Supply     Total primary energy su…
#>  7 COL     PCM    E          Final      2000 Supply     Total primary energy su…
#>  8 COL     PCM    E          Final      2000 Supply     Total primary energy su…
#>  9 COL     PCM    E          Final      1971 Supply     Total primary energy su…
#> 10 COL     PCM    E          Final      2000 Supply     Total primary energy su…
#> # ℹ 112 more rows
#> # ℹ 4 more variables: Flow <chr>, Product <chr>, Unit <chr>, Edot <dbl>
fixed <- example_tidy_iea_df %>% 
  fix_COL_WRLD_electricity()
# Compare changed values
example_tidy_iea_df %>% 
  dplyr::filter(Flow %in% c("Main activity producer electricity plants",
                            "Autoproducer electricity plants"), 
         Product == "Electricity") %>% 
  dplyr::select("Year", "Flow", "Edot", "Unit")
#> # A tibble: 2 × 4
#>    Year Flow                                        Edot Unit 
#>   <dbl> <chr>                                      <dbl> <chr>
#> 1  1971 Main activity producer electricity plants 10598. TJ   
#> 2  2000 Main activity producer electricity plants 26003. TJ   
fixed %>% 
  dplyr::filter(Flow %in% c("Main activity producer electricity plants",
                      "Autoproducer electricity plants"), 
                Product == "Electricity") %>% 
  dplyr::select("Year", "Flow", "Edot", "Unit")
#> # A tibble: 3 × 4
#>    Year Flow                                        Edot Unit 
#>   <dbl> <chr>                                      <dbl> <chr>
#> 1  1971 Main activity producer electricity plants 34196. TJ   
#> 2  2000 Main activity producer electricity plants 26003. TJ   
#> 3  1971 Autoproducer electricity plants            2671. TJ