simulate_ams_ib_dataset.RdGenerates a tidy dataset representing mechanical energy services delivered by renewable systems that displace fossil fuel-based equipment.
simulate_ams_ib_dataset(
n_machines = 15,
n_periods = 12,
start_year = 2023,
start_month = 1,
mean_service_mj = 48000,
sd_service_mj = 6000,
emission_factor = 0.00007,
project_fossil_share = 0.05
)Number of mechanical systems to simulate.
Number of monitoring periods per system.
Calendar year of the first monitoring period.
Calendar month (1-12) of the first monitoring period.
Mean annual mechanical energy service per machine in MJ.
Standard deviation of annual mechanical energy service in MJ.
Baseline emission factor in tCO2e/MJ.
Share of mechanical service retained by fossil back-up systems (0-1).
A tibble containing monitoring metadata, baseline fuel characteristics, and emission outcomes.
simulate_ams_ib_dataset(n_machines = 5)
#> # A tibble: 60 × 16
#> machine_id monitoring_period year month day monitoring_date
#> <chr> <int> <dbl> <dbl> <int> <date>
#> 1 machine_1 1 2023 1 21 2023-01-21
#> 2 machine_1 2 2023 2 12 2023-02-12
#> 3 machine_1 3 2023 3 2 2023-03-02
#> 4 machine_1 4 2023 4 6 2023-04-06
#> 5 machine_1 5 2023 5 4 2023-05-04
#> 6 machine_1 6 2023 6 16 2023-06-16
#> 7 machine_1 7 2023 7 2 2023-07-02
#> 8 machine_1 8 2023 8 3 2023-08-03
#> 9 machine_1 9 2023 9 25 2023-09-25
#> 10 machine_1 10 2023 10 22 2023-10-22
#> # ℹ 50 more rows
#> # ℹ 10 more variables: monitoring_label <chr>, service_output_mj <dbl>,
#> # fuel_consumption <dbl>, net_calorific_value <dbl>, emission_factor <dbl>,
#> # project_energy_mj <dbl>, baseline_energy_mj <dbl>,
#> # baseline_emissions_tco2e <dbl>, project_emissions_tco2e <dbl>,
#> # emission_reductions_tco2e <dbl>