antaresEditObject (version 0.9.0)

createClusterBulk: Create serial thermal cluster

Description

For each area, the thermal cluster data are generated :

• Writing .ini files

• Writing time_series files

• Writing prepro_data files

• Writing prepro_modulation files

Usage

createClusterBulk(
  cluster_object,
  area_zone,
  add_prefix = TRUE,
  opts = antaresRead::simOptions()
)

Value

An updated list containing various information about the simulation.

list containing meta information about the simulation

Arguments

cluster_object

list mutiple list containing the parameters for writing each cluster

area_zone

character name of area to create cluster

add_prefix

logical prefix cluster name with area name

opts

List of simulation parameters returned by the function antaresRead::setSimulationPath()

Details

see the example to write a cluster object, see the original function createCluster()

Structure of cluster_object :

The list must be structured with named items

• parameter : list of paramaters to write in .ini file

• overwrite : logical to choose to overwrite an existing cluster (if not present, set to FALSE)

• time_series : matrix or data.frame the "ready-made" 8760-hour time-series

• prepro_data : matrix or data.frame Pre-process data

• prepro_modulation : matrix or data.frame Pre-process modulation

Details for sublist cluster_object[["parameter"]] :

• name : Name for the cluster, it will prefixed by area name, unless you set add_prefix = FALSE

• group : Group of the cluster, depends on cluster type

• ... : Parameters to write in the Ini file

Examples

if (FALSE) {

# /!\/!\/!\ use or create a study /!\/!\/!\

# data preparation for sutructures
ts <- matrix(rep(c(0, 8000), each = 24*364), 
             ncol = 2)

df_pd <- matrix(rep(c(1, 1, 1, 0), each = 24*365), 
                ncol = 4)

df_pm <- matrix(data = c(rep(1, times = 365 * 24 * 3), rep(0, times = 365 * 24 * 1)), 
                ncol = 4)


# Example cluster object
zone_test_1 <- list(
  `CCGT old 1`= list(
  parameter= list(
  name= "CCGT old 1",
  group = "Other",
  unitcount= 10L,
  nominalcapacity= 100,
   enabled= "true",
   `min-stable-power`= 80L,
   `min-up-time`= 20L,
   `min-down_time`= 30L),
   overwrite= TRUE,
   time_series = ts_8760,
   prepro_data = df_pd,
   prepro_modulation = df_pm))
 
 # overwrite existing cluster
zone_test_2 <- list(
 `PEAK`= list(parameter= list(
   name= "PEAK",
   group = "Other"),
   overwrite= TRUE,
   time_series = ts,
   prepro_data = df_pd,
   prepro_modulation = df_pm))

# Create multiple areas with multiple clusters
list_areas <- antaresRead::getAreas()[1:5]

lapply(list_areas, createClusterBulk,
cluster_object = c(zone_test_1, zone_test_2),
add_prefix = TRUE)

}