Skip to contents

Calculate industry efficiencies

Source: R/efficiency.R
calc_eta_i.Rd

Calculates industry efficiencies for all energy conversion industries in the ECC. Calculations are performed as shown in Equation 11 in Heun, Owen, and Brockway. 2018. A physical supply-use table framework for energy analysis on the energy conversion chain. Applied Energy, vol 226, pp. 1134-1162.

Usage

calc_eta_i(
  .sutmats,
  U = Recca::psut_cols$U,
  V = Recca::psut_cols$V,
  S_units = Recca::psut_cols$S_units,
  eta_i = Recca::efficiency_cols$eta_i
)

Arguments

.sutmats

A data frame containing columns for U, V, and S_units matrices.

U

A string for the name of a column of U matrices in .sutmats. Default is Recca::psut_cols$U.

V

A string for the name of a column of V matrices in .sutmats. Default is Recca::psut_cols$V.

S_units

A string for the name of a column of S_units matrices in .sutmats. Default is Recca::psut_cols$S_units.)

eta_i

The name of the industry efficiency column in output. Default is Recca::efficiency_cols$eta_i.

Value

.sutmats with an additional column eta_i

Details

The efficiency for a given industry is calculated iff the units for inputs and outputs for that industry are unit-homogeneous. If units for inputs and outputs are heterogeneous for an industry, NA is the result.

Note that these efficiencies (eta) are different from final demand sector and product efficiencies (eta_s and eta_p, respectively). Both final demand sector and product efficiencies (eta_s and eta_p) are based on embodied energy, whereas industry efficiencies (eta) is based on direct inputs consumed and outputs produced by the energy conversion industry.

To calculate energy conversion final demand sector and product efficiencies, use the calc_embodied_etas() function.

Examples

library(tidyr)
UKEnergy2000mats %>%
  tidyr::spread(key = "matrix.name", value = "matrix") %>%
  calc_eta_i()
#> # A tibble: 4 × 13
#>   Country  Year EnergyType LastStage R             S_units  U        U_EIOU  
#>   <chr>   <dbl> <chr>      <chr>     <list>        <list>   <list>   <list>  
#> 1 GBR      2000 E          Final     <dbl [2 × 2]> <dbl[…]> <dbl[…]> <dbl[…]>
#> 2 GBR      2000 E          Services  <dbl [2 × 2]> <dbl[…]> <dbl[…]> <dbl[…]>
#> 3 GBR      2000 E          Useful    <dbl [2 × 2]> <dbl[…]> <dbl[…]> <dbl[…]>
#> 4 GBR      2000 X          Services  <dbl [2 × 2]> <dbl[…]> <dbl[…]> <dbl[…]>
#> # ℹ 5 more variables: U_feed <list>, V <list>, Y <list>, r_EIOU <list>,
#> #   eta_i <list>