Add capability to calculate pop-weighted hdcd at electricity intercon…

…nection level (WECC, ERCOT, EI)

DESCRIPTION

@@ -47,4 +47,4 @@ Remotes:
 Config/testthat/edition: 3
 Encoding: UTF-8
 LazyData: true
-RoxygenNote: 7.2.3
+RoxygenNote: 7.3.1

R/data.R

@@ -238,6 +238,20 @@
 #' }
 "mapping_states_gridregion"
 
+#--------------------------------
+# State to Electricity Interconnection Mapping
+#--------------------------------
+#' mapping_states_interconnect
+#'
+#' @source electricity trade update from Matthew Binsted
+#' @format tibble::tribble
+#' @examples
+#' \dontrun{
+#'  library(helios);
+#'  mapping_states_interconnect <- helios::mapping_states_interconnect
+#' }
+"mapping_states_interconnect"
+
 
 #.................................
 # Pre-processed Population Files

R/diagnostics.R

@@ -66,7 +66,7 @@ diagnostics <- function(hdcd_segment = tibble::tibble(),
         # calculate the number of hours in each segment by state
         segment_hours <- helios::segment_map_utc %>%
           dplyr::group_by(subRegion, segment) %>%
-          dplyr::summarise(segment_hours = n()) %>%
+          dplyr::summarise(segment_hours = dplyr::n()) %>%
           dplyr::ungroup()
 
         if(any(grepl('grid', unique(hdcd_segment$subRegion)))) {
@@ -77,11 +77,31 @@ diagnostics <- function(hdcd_segment = tibble::tibble(),
             dplyr::rename(subRegion = grid_region) %>%
             dplyr::distinct()
         }
+
+        if(any(grepl('WECC', unique(hdcd_segment$subRegion)))) {
+          # calculate the number of hours in each segment by electricity interconnection region
+          # if at electricity interconnection level, select Central Northeast grid region (e.g., Montana) as the
+          # Eastern interconnection's segment time
+          # Note: The eastern interconnection is not suppose to be used in GO-CERF-GO (WECC is the one to be used)
+          segment_hours_temp <- segment_hours %>%
+            dplyr::filter(subRegion == 'MO') %>%
+            dplyr::mutate(subRegion = 'EI')
+
+          segment_hours <- segment_hours %>%
+            dplyr::left_join(helios::mapping_states_interconnect, by = 'subRegion') %>%
+            dplyr::select(-subRegion) %>%
+            dplyr::distinct() %>%
+            dplyr::rename(subRegion = grid_region) %>%
+            dplyr::filter(!subRegion == 'EI') %>%
+            dplyr::bind_rows(segment_hours_temp)
+
+        }
+
       } else {
 
         segment_hours <- segment_map %>%
           dplyr::group_by(subRegion, year, segment) %>%
-          dplyr::summarise(segment_hours = n()) %>%
+          dplyr::summarise(segment_hours = dplyr::n()) %>%
           dplyr::ungroup()
 
       }

R/format_temperature.R

@@ -6,7 +6,7 @@
 #' @param ncdf_grid Default = NULL. output from process_temperature.
 #' @param model Default = NULL. String for climate model that generates the ncdf file. Options: 'wrf' or 'cmip'.
 #' @param time_periods Default = NULL. Integer vector for selected time periods to process. If not specified, set to GCAM periods seq(2020, 2100, 5).
-#' @param to_year Default = NULL. Integer for the time step the design year/representative year is for.
+#' @param to_year Default = NULL. Integer for renaming the time step the design year/representative year is for.
 #' @importFrom magrittr %>%
 #' @importFrom data.table :=
 #' @export
@@ -32,7 +32,7 @@ format_temperature <- function(ncdf_grid = NULL,
     ncdf_times_update <- gsub(years, to_year, ncdf_times)
 
     ncdf_grid <- ncdf_grid %>%
-      dplyr::rename_at(vars(ncdf_times), ~ ncdf_times_update)
+      dplyr::rename_at(dplyr::vars(ncdf_times), ~ ncdf_times_update)
 
     ncdf_times <- ncdf_times_update
 

R/hdcd.R

@@ -19,6 +19,7 @@
 #' @param im3_analysis Default = T. Output annual HDCD at grid region scale for trend-representative year analysis
 #' @param elec_share Default = NULL. data frame for the fraction of building heating and cooling energy consumption met by electricity at grid region scale. Column [subRegion, year, HDCD, elec_frac]. If elec_share is provided, helios will recalculate the super peak hours; Otherwise, helios will use the default super peak hours. Note, to get the correct super peak hours, the ncdf argument should include all files that cover full years.
 #' @param to_year Default = NULL. Integer for the time step the design year/representative year is for.
+#' @param use_elec_interconnect Default = F. Set to TRUE to output degree-days and degree-hours at electricity interconnection level (instead of grid region level). IM3 analysis enabled only.
 #' @importFrom magrittr %>%
 #' @importFrom data.table :=
 #' @export
@@ -39,7 +40,8 @@ hdcd <- function(ncdf = NULL,
                  save = T,
                  im3_analysis = T,
                  elec_share = NULL,
-                 to_year = NULL) {
+                 to_year = NULL,
+                 use_elec_interconnect = F) {
 
   print('Starting function process_hdcd...')
 
@@ -177,7 +179,8 @@ hdcd <- function(ncdf = NULL,
                                                time_periods = time_periods,
                                                climate_years = years,
                                                spatial = spatial,
-                                               im3_analysis = im3_analysis)
+                                               im3_analysis = im3_analysis,
+                                               use_elec_interconnect = use_elec_interconnect)
 
         population_j_weighted <- pop_list$population_weighted
         population_j_weighted_gridregion <- pop_list$population_weighted_gridregion
@@ -207,8 +210,15 @@ hdcd <- function(ncdf = NULL,
         # for IM3 grid region analysis
         if(im3_analysis){
 
+          if(use_elec_interconnect){
+            mapping_elec_subregion <- helios::mapping_states_interconnect
+          } else {
+            mapping_elec_subregion <- helios::mapping_states_gridregion
+          }
+
+
           ncdf_pivot_gridregion <- ncdf_pivot %>%
-            dplyr::left_join(helios::mapping_states_gridregion, by = 'subRegion') %>%
+            dplyr::left_join(mapping_elec_subregion, by = 'subRegion') %>%
             dplyr::mutate(subRegion = grid_region,
                           ID = grid_region) %>%
             dplyr::select(-grid_region)
@@ -311,7 +321,7 @@ hdcd <- function(ncdf = NULL,
           dplyr::select(grid_region = subRegion, year, HDCD, elec_frac)
 
         # for state level calculation
-        elec_share_region <- helios::mapping_states_gridregion %>%
+        elec_share_region <- mapping_elec_subregion %>%
           dplyr::left_join(elec_share_region, by = c('grid_region')) %>%
           dplyr::select(subRegion, year, HDCD, elec_frac)
 
@@ -430,11 +440,32 @@ hdcd <- function(ncdf = NULL,
             dplyr::select(subRegion, year, HDCD, elec_frac)
 
           # segment map for grid regions
-          segment_map_utc_no_superpeak_gridregion <- helios::segment_map_utc_no_superpeak %>%
-            dplyr::left_join(helios::mapping_states_gridregion, by = 'subRegion') %>%
-            dplyr::select(-subRegion) %>%
-            dplyr::distinct() %>%
-            dplyr::rename(subRegion = grid_region)
+          if(use_elec_interconnect){
+            # if at electricity interconnection level, select Central Northeast grid region (e.g., Montana) as the
+            # Eastern interconnection's segment time
+            # Note: The eastern interconnection is not suppose to be used in GO-CERF-GO (WECC is the one to be used)
+            segment_map_utc_no_superpeak_gridregion_temp <-  helios::segment_map_utc_no_superpeak %>%
+              dplyr::filter(subRegion == 'MO') %>%
+              dplyr::mutate(subRegion = 'EI')
+
+            segment_map_utc_no_superpeak_gridregion <- helios::segment_map_utc_no_superpeak %>%
+              dplyr::left_join(mapping_elec_subregion, by = 'subRegion') %>%
+              dplyr::select(-subRegion) %>%
+              dplyr::distinct() %>%
+              dplyr::rename(subRegion = grid_region) %>%
+              dplyr::filter(!subRegion == 'EI') %>%
+              dplyr::bind_rows(segment_map_utc_no_superpeak_gridregion_temp)
+
+          } else {
+
+            segment_map_utc_no_superpeak_gridregion <- helios::segment_map_utc_no_superpeak %>%
+              dplyr::left_join(mapping_elec_subregion, by = 'subRegion') %>%
+              dplyr::select(-subRegion) %>%
+              dplyr::distinct() %>%
+              dplyr::rename(subRegion = grid_region)
+
+          }
+
 
           # calculate the HDCD
           hdcd_gridregion_segments <- hdcd_gridregion %>%
@@ -465,7 +496,7 @@ hdcd <- function(ncdf = NULL,
 
           # segment map for grid regions
           segment_map_utc_gridregion <- helios::segment_map_utc %>%
-            dplyr::left_join(helios::mapping_states_gridregion, by = 'subRegion') %>%
+            dplyr::left_join(mapping_elec_subregion, by = 'subRegion') %>%
             dplyr::select(-subRegion) %>%
             dplyr::distinct() %>%
             dplyr::rename(subRegion = grid_region)
@@ -532,7 +563,7 @@ hdcd <- function(ncdf = NULL,
 
             # create building service structure for grid region
             L2441.HDDCDD_Fixed_gcamusa_seg_gridregion <- helios::L2441.HDDCDD_Fixed_gcamusa_seg %>%
-              dplyr::left_join(helios::mapping_states_gridregion, by = 'subRegion') %>%
+              dplyr::left_join(mapping_elec_subregion, by = 'subRegion') %>%
               dplyr::select(-subRegion) %>%
               dplyr::rename(subRegion = grid_region) %>%
               dplyr::distinct()

R/process_population.R

@@ -8,6 +8,7 @@
 #' @param climate_years Default = NULL. Integer vector of years that is covered by the climate data to check if the population years overlap with the climate years. If Null, skip the check.
 #' @param spatial Default = NULL. String for spatial aggregation boundaries. Options: check helios::spatial_options. 'gcam_us49', 'gcam_regions32', 'gcam_regions31_us52', 'gcam_countries', 'gcam_basins'.
 #' @param im3_analysis Default = TRUE. Output annual HDCD at grid region scale for trend-representative year analysis
+#' @param use_elec_interconnect Default = F. Set to TRUE to output degree-days and degree-hours at electricity interconnection level (instead of grid region level). IM3 analysis enabled only.
 #' @importFrom magrittr %>%
 #' @importFrom data.table :=
 #' @export
@@ -17,7 +18,8 @@ process_population <- function(population = NULL,
                                time_periods = NULL,
                                climate_years = NULL,
                                spatial = NULL,
-                               im3_analysis = TRUE){
+                               im3_analysis = TRUE,
+                               use_elec_interconnect = FALSE){
 
   if (im3_analysis) {
 
@@ -96,8 +98,15 @@ process_population <- function(population = NULL,
 
     # for IM3 grid region analysis
     if(im3_analysis){
+
+      if(use_elec_interconnect){
+        mapping_elec_subregion <- helios::mapping_states_interconnect
+      } else {
+        mapping_elec_subregion <- helios::mapping_states_gridregion
+      }
+
       population_weighted_gridregion <- population_grid %>%
-        dplyr::left_join(helios::mapping_states_gridregion, by = 'subRegion') %>%
+        dplyr::left_join(mapping_elec_subregion, by = 'subRegion') %>%
         dplyr::mutate(subRegion = grid_region,
                       ID = grid_region) %>%
         dplyr::select(-grid_region) %>%

inst/extras/dev_tests.R

@@ -39,11 +39,12 @@ ncdf_format <- helios::format_temperature(ncdf_grid = ncdf_grid,
                                           to_year = 2045)$ncdf_pivot
 
 pop_grid <- helios::process_population(population = path_to_population,
-                                       coordinates = ncdf_pivot,
+                                       coordinates = ncdf_format,
                                        time_periods = 2020,
                                        climate_years = NULL,
                                        spatial = 'gcam_us49',
-                                       im3_analysis = TRUE)
+                                       im3_analysis = TRUE,
+                                       use_elec_interconnect = TRUE)
 
 # check mapping grid
 mapping <- helios::find_mapping_grid(data = pop,
@@ -150,10 +151,16 @@ path_to_climate_ncdf <- file.path(data_dir, 'climate', 'wrfout_d01_2020-01-01_01
 path_to_population <- file.path(
   data_dir, 'population', 'population_conus_total_ssp2_2020-2100_wrf_wgs84.csv')
 
+# for grid region
 elec_share <- data.table::fread(
   'C:/WorkSpace/IM3/helios/hddcdd/constance/output/im3_bldg_hdcd_electricity_fraction.csv') %>%
   dplyr::filter(scenario == 'rcp85hotter_ssp5')
 
+# for electricity interconnection
+elec_share <- data.table::fread(
+  'C:/WorkSpace/IM3/helios/hddcdd/constance/output/im3_bldg_hdcd_electricity_intensity_interconnection.csv') %>%
+  dplyr::filter(scenario == 'rcp85hotter_ssp5')
+
 # test file list
 # path_to_climate_ncdf <- c(
 #   helios::pkg_example('wrfout_d01_2020-01-01_01%3A00%3A00_sub.nc'),
@@ -175,19 +182,20 @@ hdcd_wrf_all <- helios::hdcd(
   folder = file.path(getwd(), 'output_im3_test'),
   diagnostics = F,
   xml = F,
-  name_append = '',
+  name_append = 'interconnection',
   save = T,
   im3_analysis = T,
   elec_share = elec_share,
-  to_year = NULL
+  to_year = NULL,
+  use_elec_interconnect = T
 )
 
 helios::diagnostics(
   hdcd_segment = hdcd_wrf_all$hdcd_comb_gcam,
   hdcd_monthly = hdcd_wrf_all$hdcd_comb_monthly,
   min_diagnostic_months = 1,
   folder = file.path(getwd(), 'output_im3_test'),
-  name_append = 'wrf_all'
+  name_append = 'interconnection'
 )
 
 
@@ -208,6 +216,10 @@ ncdf_grid <- helios::read_ncdf(ncdf = path_to_climate_ncdf,
                                time_periods = 2020)
 population_j_grid <- helios::read_population(path_to_population, time_periods = 2020)
 
+ncdf_format <- helios::format_temperature(ncdf_grid = ncdf_grid,
+                                          model = 'cmip',
+                                          to_year = NULL)$ncdf_pivot
+
 hdcd_cmip_all <- helios::hdcd(
   ncdf = path_to_climate_ncdf,
   ncdf_var = 'tas',

inst/extras/saveDataFiles.R

@@ -437,3 +437,19 @@ mapping_states_gridregion <- data.table::fread(
   dplyr::select(subRegion = state, grid_region)
 
 usethis::use_data(mapping_states_gridregion, version = 3, overwrite = T)
+
+
+#--------------------------------
+# State to Grid Region Mapping
+#--------------------------------
+# read state to grid region mapping from gcamdata
+mapping_states_interconnect <- data.table::fread(
+  file.path('C:/WorkSpace/github/helios/inst/extras/GCAM-USA_interconnections.csv')) %>%
+  dplyr::left_join(rmap::mapUS52 %>% tibble::as_tibble() %>% dplyr::select(state_name = subRegionAlt, state = subRegion),
+                   by = 'state_name') %>%
+  dplyr::mutate(interconnect = ifelse(interconnect == 'n/a', NA, interconnect),
+                interconnect = ifelse(interconnect == 'Eastern Interconnection', 'EI', interconnect),
+                interconnect = ifelse(is.na(interconnect), state, interconnect)) %>%
+  dplyr::select(subRegion = state, grid_region = interconnect)
+
+usethis::use_data(mapping_states_interconnect, version = 3, overwrite = T)