Create a cluster

(thermal clusters only)

Create a new thermal or RES (renewable energy source) cluster.

Usage

createCluster(
  area,
  cluster_name,
  group = "Other",
  ...,
  list_pollutants = NULL,
  time_series = NULL,
  prepro_data = NULL,
  prepro_modulation = NULL,
  add_prefix = TRUE,
  overwrite = FALSE,
  opts = antaresRead::simOptions()
)

createClusterRES(
  area,
  cluster_name,
  group = default_group(opts),
  ...,
  time_series = NULL,
  add_prefix = TRUE,
  overwrite = FALSE,
  opts = antaresRead::simOptions()
)

Arguments

area

The area where to create the cluster.

cluster_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:

• thermal cluster, one of: Gas, Hard coal, Lignite, Mixed fuel, Nuclear, Oil, Other, Other 2, Other 3, Other 4(dynamic name for Antares version >= 9.3).

• renewable cluster, one of: Wind Onshore, Wind Offshore, Solar Thermal, Solar PV, Solar Rooftop, Other RES 1, Other RES 2, Other RES 3, Other RES 4(dynamic name for Antares version >= 9.3. Default group by version: Other RES 1 if <930, Other if >=930).

...

Parameters to write in the Ini file. Careful! Some parameters must be set as integers to avoid warnings in Antares, for example, to set unitcount, you'll have to use unitcount = 1L.

list_pollutants

list named with specific pollutants (only for Antares version >= 860)

time_series

the "ready-made" 8760-hour time-series available for simulation purposes.

prepro_data

Pre-process data, a data.frame or matrix, default is a matrix with 365 rows and 6 columns.

prepro_modulation

Pre-process modulation, a data.frame or matrix, if specified, must have 8760 rows and 1 or 4 columns.

add_prefix

If TRUE (the default), cluster_name will be prefixed by area name.

overwrite

Logical, overwrite the cluster or not.

opts

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

Value

An updated list containing various information about the simulation.

Note

Parameter list_pollutants is only available for Antares studies >= v8.6.0.

You must provide named list (numerical values or NULL ) :

list( "nh3"= 0.25, "nox"= 0.45, "pm2_5"= 0.25, "pm5"= 0.25, "pm10"= 0.25, "nmvoc"= 0.25, "so2"= 0.25, "op1"= 0.25, "op2"= 0.25, "op3"= 0.25, "op4"= 0.25, "op5"= NULL, "co2"= NULL)

See also

editCluster() or editClusterRES() to edit existing clusters, removeCluster() or removeClusterRES() to remove clusters.

Examples

if (FALSE) { # \dontrun{

library(antaresRead)
library(antaresEditObject)

# Create a cluster :
createCluster(
  area = "fr", 
  cluster_name = "my_cluster",
  group = "other", 
  unitcount = 1L, # or as.integer(1)
  marginal_cost = 50
)
# by default, cluster name is prefixed 
# by the area name
levels(readClusterDesc()$cluster)
# > "fr_my_cluster"

# To prevent this, use `add_prefix`
createCluster(
  area = "fr", 
  cluster_name = "my_cluster",
  add_prefix = FALSE,
  group = "other", 
  marginal_cost = 50
)
levels(readClusterDesc()$cluster)
# > "my_cluster"


# Create a RES cluster :
createClusterRES(
  area = "fr", 
  cluster_name = "my_cluster_res",
  group = "other", 
  unitcount = 1L, # or as.integer(1)
  nominalcapacity = 50,
  ts_interpretation = "power-generation"
) 

# You can also specify that the Time-Series of the RES cluster are
# production factors :
createClusterRES(
  area = "fr", 
  cluster_name = "my_cluster_res",
  group = "other", 
  unitcount = 1L, # or as.integer(1)
  nominalcapacity = 50,
  ts_interpretation = "production-factor"
)


# Pre-process data : 

# this is the default data :
createCluster(
  area = "fr", 
  cluster_name = "my_cluster",
  prepro_data = matrix(
    data = c(rep(1, times = 365 * 2),
             rep(0, times = 365 * 4)), 
    ncol = 6
  )
)

# with a data.frame
createCluster(
  area = "fr", 
  cluster_name = "my_cluster",
  prepro_data = data.frame(
    v1 = rep(7, 365), # column name does not matter
    v2 = rep(27, 365),
    v3 = rep(0.05, 365),
    v4 = rep(0.12, 365),
    v5 = rep(0, 365),
    v6 = rep(1, 365)
  )
)


# Pre-process modulation : 
# this is the default data
createCluster(
  area = "fr", 
  cluster_name = "my_cluster",
  prepro_modulation = matrix(
    data = c(rep(1, times = 365 * 24 * 3),
             rep(0, times = 365 * 24 * 1)),
    ncol = 4
  )
)

# with a data.frame
createCluster(
  area = "fr", 
  cluster_name = "my_cluster",
  prepro_modulation = data.frame(
    var1 = rep(0, 8760), # column name does not matter
    var2 = rep(1, 8760),
    var3 = rep(0, 8760),
    var4 = rep(1, 8760)
  )
)

} # }