tests/testthat/test-efficiency.R

In MatthewHeun/Recca: R Energy Conversion Chain Analysis

test_that("industry efficiencies are calculated correctly", {
  result_mats <- UKEnergy2000mats %>%
    tidyr::spread(key = "matrix.name", value = "matrix") %>%
    calc_eta_i()
  result <- result_mats |>
    dplyr::select(Country, Year, EnergyType, LastStage, eta_i) %>%
    tidyr::gather(key = matnames, value = matvals, eta_i) %>%
    matsindf::expand_to_tidy() %>%
    dplyr::rename(
      eta_i = matvals
    ) |>
    dplyr::mutate(
      # Make expected values
      expected = dplyr::case_when(
        startsWith(rownames, "Resources - ") ~ Inf,
        LastStage == "services" & endsWith(rownames, " dist.") ~ NA_real_,
        rownames %in% c("Cars", "Homes", "Rooms", "Trucks") ~ NA_real_,
        TRUE ~ eta_i
      )
    )
  # Check that NAs appear in the right places.
  expect_equal(result[[Recca::efficiency_cols$eta_i]],
               result$expected)

  # Test some specific values
  expect_equal(result %>%
                 dplyr::filter(LastStage == IEATools::last_stages$final, rownames == "Crude dist.") |>
                 magrittr::extract2(Recca::efficiency_cols$eta_i),
               0.98855359)
  expect_equal(result %>%
                 dplyr::filter(LastStage == IEATools::last_stages$useful, rownames == "Power plants") |>
                 magrittr::extract2(Recca::efficiency_cols$eta_i),
               0.39751553)
  expect_equal(result |>
                 dplyr::filter(LastStage == IEATools::last_stages$services, EnergyType == IEATools::energy_types$e, rownames == "Oil fields") |>
                 magrittr::extract2(Recca::efficiency_cols$eta_i),
               0.94857713)
  expect_equal(result |>
                 dplyr::filter(LastStage == IEATools::last_stages$services, EnergyType == IEATools::energy_types$x, rownames == "Oil fields") |>
                 magrittr::extract2(Recca::efficiency_cols$eta_i),
               0.94860812)
  # Check row and column types
  expect_equal(result_mats |>
                 dplyr::filter(LastStage == IEATools::last_stages$useful) |>
                 magrittr::extract2(Recca::efficiency_cols$eta_i) |>
                 magrittr::extract2(1) |>
                 matsbyname::rowtype(),
               "Industry")
  expect_equal(result_mats |>
                 dplyr::filter(LastStage == IEATools::last_stages$useful) |>
                 magrittr::extract2(Recca::efficiency_cols$eta_i) |>
                 magrittr::extract2(1) |>
                 matsbyname::coltype(),
               "eta_i")
})


test_that("efficiency vectors are named correctly", {
  result <- UKEnergy2000mats %>%
    tidyr::spread(key = "matrix.name", value = "matrix") %>%
    calc_eta_i()

  # Ensure that efficiency column is named correctly.
  for (i in 1:nrow(result)) {
    etai <- result[[Recca::efficiency_cols$eta_i]][[i]]
    expect_equal(colnames(etai)[1], Recca::efficiency_cols$eta_i)
  }
})


test_that("calc_eta_pfu() works correctly", {
  wide <- UKEnergy2000mats %>%
    tidyr::pivot_wider(names_from = matrix.name, values_from = matrix)

  # Define primary industries
  p_industries <- c("Resources [of Crude]", "Resources [of NG]")

  primary_total_aggregates_sut <- wide %>%
    Recca::primary_aggregates(p_industries = p_industries, by = "Total") %>%
    # Get rid of unneeded matrix columns.
    dplyr::mutate(
      "{Recca::psut_cols$R}" := NULL,
      "{Recca::psut_cols$U}" := NULL,
      "{Recca::psut_cols$U_feed}" := NULL,
      "{Recca::psut_cols$U_eiou}" := NULL,
      "{Recca::psut_cols$r_eiou}" := NULL,
      "{Recca::psut_cols$V}" := NULL,
      "{Recca::psut_cols$Y}" := NULL,
      "{Recca::psut_cols$S_units}" := NULL,
      p_industries = NULL
    )

  # Define final demand sectors
  fd_sectors <- c("Residential", "Transport", "Oil fields")

  finaldemand_total_aggregates_sut <- wide %>%
    Recca::finaldemand_aggregates(fd_sectors = fd_sectors, by = "Total") %>%
    # Get rid of unneeded matrix columns.
    dplyr::mutate(
      "{Recca::psut_cols$R}" := NULL,
      "{Recca::psut_cols$U}" := NULL,
      "{Recca::psut_cols$U_feed}" := NULL,
      "{Recca::psut_cols$U_eiou}" := NULL,
      "{Recca::psut_cols$r_eiou}" := NULL,
      "{Recca::psut_cols$V}" := NULL,
      "{Recca::psut_cols$Y}" := NULL,
      "{Recca::psut_cols$S_units}" := NULL,
      fd_sectors = NULL
    )

  etas <- dplyr::full_join(primary_total_aggregates_sut,
                           finaldemand_total_aggregates_sut,
                           by = c(IEATools::iea_cols$country,
                                  IEATools::iea_cols$year,
                                  IEATools::iea_cols$energy_type,
                                  IEATools::iea_cols$last_stage)) %>%
    calc_eta_pfd()

  expect_equal(etas$etapfdgross, c(0.799193548387097, 5384063619.67424, 0.279466456989247, 5097922181.12103))
  expect_equal(etas$etapfdnet, c(0.771505376344086, 5384063619.67343, 0.278660005376344, 5097922181.12023))
})


test_that("calc_eta_pfd() works with the output from chop_Y()", {
  psut_mats <- UKEnergy2000mats %>%
    tidyr::pivot_wider(names_from = matrix.name, values_from = matrix)
  p_industries <- c("Resources - Crude", "Resources - NG")
  fd_sectors <- c("Residential", "Transport", "Oil fields")
  chop_Y_aggs <- psut_mats %>%
    Recca::chop_Y(p_industries = p_industries, fd_sectors = fd_sectors, unnest = TRUE)
  etas <- chop_Y_aggs %>%
    calc_eta_pfd()
  # Make sure expected efficiency columns are present
  expect_true(Recca::efficiency_cols$eta_pfd_gross %in% names(etas))
  expect_true(Recca::efficiency_cols$eta_pfd_net %in% names(etas))
})


test_that("calc_eta_fu_Y_eiou() works as expected", {
  # This example comes from the file named "Example f-u matrix efficiency calcs.xlsx"
  # Build example matrices
  C_Y <- matrix(c(0.7, 0.3, 0, 0, 0,
                  0,   0, 0.2, 0.5, 0.3), byrow = TRUE, nrow = 2, ncol = 5,
                dimnames = list(c("Electricity -> Non-ferrous metals", "PSB -> Residential"),
                                c("Electric arc furnaces -> HTH.600.C", "Electric lights -> L",
                                  "Wood stoves -> LTH.20.C", "Wood stoves -> LTH.50.C", "Wood stoves -> MTH.100.C"))) |>
    matsbyname::setrowtype("Product -> Industry") |> matsbyname::setcoltype("Industry -> Product")
  eta_i <- matrix(c(0.9, 0.2, 0.4, 0.4, 0.3), nrow = 5, ncol = 1,
                  dimnames = list(c("Electric arc furnaces -> HTH.600.C", "Electric lights -> L",
                                    "Wood stoves -> LTH.20.C", "Wood stoves -> LTH.50.C", "Wood stoves -> MTH.100.C"),
                                  "eta_i")) |>
    matsbyname::setrowtype("Industry -> Product") |> matsbyname::setcoltype("eta.i")
  phi <- matrix(c(1, 1.1, 1 - 298.15/(600+273.15), 0.95, 1 - (20 + 273.15)/298.15, 1 - 298.15/(50+273.15), 1 - 298.15/(100+273.15)),
                nrow = 7, ncol = 1,
                dimnames = list(c("Electricity", "PSB", "HTH.600.C", "L", "LTH.20.C", "LTH.50.C", "MTH.100.C"), "phi")) |>
    matsbyname::setrowtype("Product") |> matsbyname::setcolnames_byname("phi")

  res <- calc_eta_fu_Y_eiou(C_Y = C_Y, C_eiou = C_Y, eta_i = eta_i, phi = phi, matricize = FALSE)

  # Check the energy results
  expect_equal(res$etafu_Y_E,
               matrix(c(0.69, 0.37), ncol = 1, dimnames = list(c("Electricity -> Non-ferrous metals", "PSB -> Residential"),
                                                               "etafu_Y_E")) |>
                 matsbyname::setrowtype("Product -> Industry") |> matsbyname::setcoltype("etafu_Y_E"))
  expect_equal(res$etafu_EIOU_E,
               matrix(c(0.69, 0.37), ncol = 1, dimnames = list(c("Electricity -> Non-ferrous metals", "PSB -> Residential"),
                                                               "etafu_EIOU_E")) |>
                 matsbyname::setrowtype("Product -> Industry") |> matsbyname::setcoltype("etafu_EIOU_E"))

  # Check the exergy results
  expect_equal(res$etafu_Y_X,
               matrix(c(0.471877169, 0.031730489), ncol = 1, dimnames = list(c("Electricity -> Non-ferrous metals", "PSB -> Residential"),
                                                                             "etafu_Y_X")) |>
                 matsbyname::setrowtype("Product -> Industry") |> matsbyname::setcoltype("etafu_Y_X"))
  expect_equal(res$etafu_EIOU_X,
               matrix(c(0.471877169, 0.031730489), ncol = 1, dimnames = list(c("Electricity -> Non-ferrous metals", "PSB -> Residential"),
                                                                             "etafu_EIOU_X")) |>
                 matsbyname::setrowtype("Product -> Industry") |> matsbyname::setcoltype("etafu_EIOU_X"))

  # Try with matrix output
  resm <- calc_eta_fu_Y_eiou(C_Y = C_Y, C_eiou = C_Y, eta_i = eta_i, phi = phi)

  # Check the energy results
  expect_equal(resm$etafu_Y_E,
               matrix(c(0.69, 0,
                        0, 0.37), nrow = 2, ncol = 2, dimnames = list(c("Electricity", "PSB"), c("Non-ferrous metals", "Residential"))) |>
                 matsbyname::setrowtype("Product") |> matsbyname::setcoltype("Industry"))
  expect_equal(resm$etafu_EIOU_E,
               matrix(c(0.69, 0,
                        0, 0.37), nrow = 2, ncol = 2, dimnames = list(c("Electricity", "PSB"), c("Non-ferrous metals", "Residential"))) |>
                 matsbyname::setrowtype("Product") |> matsbyname::setcoltype("Industry"))

  # Check the exergy results
  expect_equal(resm$etafu_Y_X,
               matrix(c(0.471877169, 0,
                        0, 0.031730489), nrow = 2, ncol = 2, dimnames = list(c("Electricity", "PSB"), c("Non-ferrous metals", "Residential"))) |>
                 matsbyname::setrowtype("Product") |> matsbyname::setcoltype("Industry"))
  expect_equal(resm$etafu_EIOU_X,
               matrix(c(0.471877169, 0,
                        0, 0.031730489), nrow = 2, ncol = 2, dimnames = list(c("Electricity", "PSB"), c("Non-ferrous metals", "Residential"))) |>
                 matsbyname::setrowtype("Product") |> matsbyname::setcoltype("Industry"))
})


test_that("calc_eta_pfus() works correctly", {
  psut_df <- UKEnergy2000mats |>
    tidyr::pivot_wider(names_from = matrix.name, values_from = matrix)
  p_industries <- "Resources"
  fd_sectors <- c("Residential", "Transport", "Oil fields")
  res <- psut_df |>
    calc_agg_eta_pfus(p_industries = p_industries, fd_sectors = fd_sectors)
  expect_equal(nrow(res), 8)
  # Test a few values
  res |>
    dplyr::filter(EnergyType == "E", LastStage == "Final", GrossNet == "Gross") |>
    magrittr::extract2(Recca::efficiency_cols$eta_pf) |>
    expect_equal(0.7991935, tolerance = 1e-7)
  res |>
    dplyr::filter(EnergyType == "E", LastStage == "Services", GrossNet == "Net") |>
    magrittr::extract2(Recca::efficiency_cols$eta_ps) |>
    expect_equal(5384063620)
  res |>
    dplyr::filter(EnergyType == "X", LastStage == "Services", GrossNet == "Net") |>
    magrittr::extract2(Recca::aggregate_cols$aggregate_final) |>
    is.na() |>
    expect_true()
})


test_that("calc_eta_pfus() works correctly when services are not present", {
  psut_df <- UKEnergy2000mats |>
    tidyr::pivot_wider(names_from = matrix.name, values_from = matrix) |>
    dplyr::filter(LastStage != "Services")
  p_industries <- "Resources"
  fd_sectors <- c("Residential", "Transport", "Oil fields")
  res <- psut_df |>
    calc_agg_eta_pfus(p_industries = p_industries, fd_sectors = fd_sectors)
  expect_equal(nrow(res), 4)
  # Test a few values
  res |>
    dplyr::filter(EnergyType == "E", LastStage == "Final", GrossNet == "Gross") |>
    magrittr::extract2(Recca::efficiency_cols$eta_pf) |>
    expect_equal(0.7991935, tolerance = 1e-7)
  res |>
    dplyr::filter(EnergyType == "E", LastStage == "Useful", GrossNet == "Net") |>
    magrittr::extract2(Recca::efficiency_cols$eta_fu) |>
    expect_equal(0.36119, tolerance = 1e-7)
  res |>
    dplyr::filter(EnergyType == "E", LastStage == "Useful", GrossNet == "Gross") |>
    magrittr::extract2(Recca::aggregate_cols$aggregate_useful) |>
    expect_equal(25990.3805)
})