Reports

Analysis of the model output

An example of a report that can be generated from the model output, using results from the IDEEA electricity model.

library(IDEEA)
library(tidyverse)
library(sf)

Load the model output

Here we use pre-saved results from the IDEEA electricity model, 5 or 32 regions, as described in the vignette("electricity").

ideea_scenarios_list()

# load reference scenario
load_scenario(
  file.path(ideea_scenarios(), 
            "CAP_IDEEA_ELC_reg32_d365_h24_2060"
            # "REF_IDEEA_ELC_reg32_d365_h24_2060"
            )
  )
# load carbon constrained scenario
load_scenario(
  file.path(ideea_scenarios(), 
            "REF_IDEEA_ELC_reg32_d365_h24_Y2050"
            # "CAP_IDEEA_ELC_reg32_d365_h24_2060"
            )
  )

# combine scenarios in one list for comparison
sns <- list(
  # REF_2060 = .scen$REF,
  CAP_2060 = .scen$CAP
  )

# quick check
summary(.scen$REF)
summary(.scen$CAP)

summary(sns) # list with presolved IDEEA scenarios

Compare the results

Objective

Objective value of the model (minimized cost)

getData(sns, "vObjective", merge = TRUE)

Installed capacity

vTechCap <- getData(
  scen = sns, 
  name = c("vTechCap"), # capacity variable of technologies
  tech_ = "^E", # select only electricity generators (start with "E")
  process = TRUE, # use unified set-name for all processes (rename 'tech' -> 'process')
  digits = 1, # round to 2 digits
  drop.zeros = T, # drop zero values
  merge = TRUE # merge tables
  ) |>
  drop_process_cluster() |> # erase cluster from process name
  drop_process_vintage() # erase vintage-year from process name

vTechCap_conv <- vTechCap |>
  filter(grepl("ELC2EDC|EDC2ELC", process)) # converters

vTechCap_gen <- vTechCap |>
  anti_join(vTechCap_conv, by = "process") # keep only generators

vStorageCap <- getData(
  scen = sns, 
  name = c("vStorageCap"), # capacity variables of storage technologies
  # tech_ = "^S", # select only storage technologies (start with "S")
  process = TRUE, # use unified set-name for all processes (rename 'tech' -> 'process')
  digits = 1, # round to 2 digits
  drop.zeros = T, # drop zero values
  merge = TRUE # merge tables
  ) |> 
  drop_process_vintage() # erase vintage-year from process name

# combine technologies and storage
vCap <- bind_rows(vTechCap, vStorageCap)

vCap$process |> unique()

Capacity maps

ideea_sf <- get_ideea_map(nreg = 32) 
vTechCap_gen_sf <- ideea_sf |>
  right_join(vTechCap_gen, by = c("reg32" = "region"), 
            relationship = "many-to-many") 

ggplot() +
  geom_sf(fill = "grey", data = ideea_sf) +
  geom_sf(aes(fill = value), data = vTechCap_sf) +
  scale_fill_viridis_c(option = "H", transform = "sqrt", name = "GW") +
  facet_wrap(~process) +
  theme_ideea_map()

Transmission capacity

vTradeCap <- getData(sns, "vTradeCap", merge = TRUE, process = T,
                     digits = 1, drop.zeros = T)

tra_lines_coord <- ideea_data$transmission[[regN]] |>
  filter(case == "newlines_v01") |>
  select(matches("region|lon|lat|trd_name"))

vTradeCap_coord <- vTradeCap |> 
  left_join(tra_lines_coord, 
            by = c("process" = "trd_name_ac"), 
            relationship = "many-to-many") |> 
  select(-trd_name_dc) |>
  as.data.table() |>
  rows_patch(
    select(
      rename(tra_lines_coord, process = trd_name_dc),
      -trd_name_ac
    ), by = c("process"), unmatched = "ignore") |>
  mutate(
    type = str_extract(process, "HVAC|HVDC"),
  ) |>
  as.data.table()
  

ggplot() +
  geom_sf(data = ideea_sf, fill = "wheat") +
  geom_segment(
    aes(
      x = lon.x, y = lat.x, xend = lon.y, yend = lat.y,
      linewidth = value, color = type
    ),
    # color = "dodgerblue", 
    lineend = "round", alpha = .75,
    data = filter(vTradeCap_coord, value >= 1)
  ) +
  # geom_point(aes(lon, lat), data = points_coord_r32, color = "red") +
  labs(x = "", y = "") +
  facet_grid(year~scenario) +
  theme_ideea_map()

Generation mix

vTechOut_ELC <- getData(sns, "vTechOut", tech_ = "^E", process = T, digits = 2,
                        drop.zeros = TRUE, merge = TRUE) |>
  drop_process_cluster() |>
  drop_process_vintage()

vTechOut_ELC_year <- vTechOut_ELC |>
  group_by(scenario, process, year) |>
  summarise(TWh = sum(value) / 1e3, .groups = "drop") |>
  filter(!process %in% c("ELC2EDC", "EDC2ELC")) # drop converters

ggplot(vTechOut_ELC_year) +
  geom_bar(aes(x = scenario, y = TWh, fill = process), stat = "identity") +
  scale_fill_viridis_d(option = "H", direction = -1) +
  theme_bw()

Intraday generation profile

Emissions

all_emis |>
  group_by(scenario, comm, year) |>
  summarise(Mt = sum(value) / 1e3, .groups = "drop") |>
  pivot_wider(names_from = scenario, values_from = Mt) |>
  kableExtra::kable(
    # caption = "Emissions from fuel combustion and processes, CO2 Mt, kt others", 
    align = "c"
  )