Simulate a dataset compliant with AMS-II.E

Generates tidy monitoring data for building portfolios implementing energy efficiency and fuel switching measures under AMS-II.E.

simulate_ams_iie_dataset(
  n_buildings = 6,
  n_periods = 12,
  start_year = 2023,
  start_month = 1,
  baseline_electricity_mean = 140,
  baseline_thermal_mean = 380,
  electricity_savings = 0.25,
  thermal_savings = 0.35,
  fuel_switch_reduction = 0.3
)

Arguments

n_buildings

Number of buildings to simulate.

n_periods

Number of monitoring periods per building (default monthly).

start_year

Calendar year for the first monitoring period.

start_month

Calendar month (1-12) for the first monitoring period.

baseline_electricity_mean

Mean baseline electricity consumption per period (MWh).

baseline_thermal_mean

Mean baseline thermal energy demand per period (GJ).

electricity_savings

Expected fractional reduction in electricity demand under the project (0-1).

thermal_savings

Expected fractional reduction in thermal demand under the project (0-1).

fuel_switch_reduction

Expected fractional reduction in thermal emission factors due to fuel switching (0-1).

Value

A tibble containing building IDs, monitoring metadata, baseline and project energy parameters, service indicators, and leakage placeholders.

Examples

simulate_ams_iie_dataset(n_buildings = 3)
#> # A tibble: 36 × 20
#>    building_id monitoring_period  year month   day monitoring_date
#>    <chr>                   <int> <dbl> <dbl> <int> <date>         
#>  1 building_01                 1  2023     1    13 2023-01-13     
#>  2 building_01                 2  2023     2    23 2023-02-23     
#>  3 building_01                 3  2023     3    12 2023-03-12     
#>  4 building_01                 4  2023     4     5 2023-04-05     
#>  5 building_01                 5  2023     5     6 2023-05-06     
#>  6 building_01                 6  2023     6    15 2023-06-15     
#>  7 building_01                 7  2023     7    15 2023-07-15     
#>  8 building_01                 8  2023     8     4 2023-08-04     
#>  9 building_01                 9  2023     9     6 2023-09-06     
#> 10 building_01                10  2023    10     9 2023-10-09     
#> # ℹ 26 more rows
#> # ℹ 14 more variables: monitoring_label <chr>, baseline_electricity_mwh <dbl>,
#> #   baseline_thermal_energy_gj <dbl>,
#> #   baseline_electricity_emission_factor_tco2_per_mwh <dbl>,
#> #   baseline_thermal_emission_factor_tco2_per_gj <dbl>,
#> #   baseline_total_energy_mwh <dbl>, project_electricity_mwh <dbl>,
#> #   project_thermal_energy_gj <dbl>, …