Chapter 13 Setting assumptions

An excel control is created to add exogenous variables. Users can add their assumptions. As of August 2023, there are 3 sheets as follows:

  1. The growth rate of electricity generation in 3 utilities (the grw_3u sheet)
  2. The growth rate of electricity generation in the MEA electricity demand (the grw_mea_dmd sheet)
  3. The growth rate of electricity generation in the PEA electricity demand (the grw_pea_dmd sheet)

13.1 The 3 utilities growth rate

The excel control sheet’s logic are given as follows:

  1. Users assumptions is extracted from the excel control sheet. Users must fill in their assumption in terms of the growth rate increase/decrease. Their assumptions are kept in the grw_3u_excel data frame (see the 1st session in the R code chunk below).
  2. The actual percentage growth rate are calculated and are saved in the grw_3u_excel data frame (see the 2nd session code chunk).
  3. The year without a growth rate assumption is extracted as a reference for a base year growth rate calculation. The value is stored in the previous_year_grw data frame (see the 3rd session).
# 1st session
grw_3u_excel <-
  read_excel("process_data/excel_control.xlsx",
             sheet = "grw_3u",
             range = "A1:B83") %>% 
  drop_na()

# 2nd session
grw_3u <- 
  grw_3u_excel %>% 
  select(growth) %>% 
  mutate(growth = 1+growth)

# 3rd session
previous_year_grw <-
grw_3u_excel %>%
  mutate(years = growth<0 | growth > 0) %>% 
  filter(years == first(years)) %>% 
  last() %>% 
  select(year) %>% 
pull(year)

13.2 The MEA electricity demand growth rate

  1. Users assumptions is extracted from the excel control sheet. Users must fill in their assumption in terms of the growth rate increase/decrease. Their assumptions are kept in the grw_mea_dmd_excel data frame (see the 1st session in the R code chunk below).
  2. The actual percentage growth rate are calculated and are saved in the grw_mea_dmd data frame (see the 2nd session code chunk).
  3. The year without a growth rate assumption is extracted as a reference for a base year growth rate calculation. The value is stored in the previous_year_mea_dmd_grw data frame (see the 3rd session).
# 1st session

grw_mea_dmd_excel <-
  read_excel("process_data/excel_control.xlsx",
             sheet = "grw_mea_dmd",
             range = "A1:B83") %>% 
  drop_na()

# 2nd session

grw_mea_dmd <- 
  grw_mea_dmd_excel %>% 
  select(growth)%>% 
  mutate(growth = 1+growth)

# 3rd session
previous_year_mea_dmd_grw <-
  grw_mea_dmd_excel %>%
  mutate(years = growth<0 | growth > 0) %>% 
  filter(years == first(years)) %>% 
  last() %>% 
  select(year) %>% 
  pull(year)

13.3 The PEA electricity demand growth rate

  1. Users assumptions is extracted from the excel control sheet. Users must fill in their assumption in terms of the growth rate increase/decrease. Their assumptions are kept in the grw_pea_dmd_excel data frame (see the 1st session in the R code chunk below).
  2. The actual percentage growth rate are calculated and are saved in the grw_pea_dmd data frame (see the 2nd session code chunk).
  3. The year without a growth rate assumption is extracted as a reference for a base year growth rate calculation. The value is stored in the previous_year_pea_dmd_grw data frame (see the 3rd session).
# 1st session

grw_pea_dmd_excel <-
  read_excel("process_data/excel_control.xlsx",
             sheet = "grw_pea_dmd",
             range = "A1:B83") %>% 
  drop_na()

# 2nd session

grw_pea_dmd <- 
  grw_pea_dmd_excel %>% 
  select(growth)%>% 
  mutate(growth = 1+growth)

# 3nd session

previous_year_pea_dmd_grw <-
  grw_pea_dmd_excel %>%
  mutate(years = growth<0 | growth > 0) %>% 
  filter(years == first(years)) %>% 
  last() %>% 
  select(year) %>% 
  pull(year)