createClusterST: Create a short-term storage cluster

Description

Antares API OK

Create a new ST-storage cluster for >= v8.6.0 Antares studies.

Usage

createClusterST(
  area,
  cluster_name,
  group = "Other1",
  storage_parameters = storage_values_default(),
  PMAX_injection = NULL,
  PMAX_withdrawal = NULL,
  inflows = NULL,
  lower_rule_curve = NULL,
  upper_rule_curve = NULL,
  cost_injection = NULL,
  cost_withdrawal = NULL,
  cost_level = NULL,
  cost_variation_injection = NULL,
  cost_variation_withdrawal = NULL,
  constraints_properties = NULL,
  constraints_ts = NULL,
  add_prefix = TRUE,
  overwrite = FALSE,
  opts = antaresRead::simOptions()
)

Value

An updated list containing various information about the simulation.

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, one of : PSP_open, PSP_closed, Pondage, Battery, Other. It corresponds to the type of stockage (dynamic name for Antares version >= 9.2).
storage_parameters: list Parameters to write in the Ini file (see Note).
PMAX_injection: Modulation of charging capacity on an 8760-hour basis. numeric {0;1} (8760*1).
PMAX_withdrawal: Modulation of discharging capacity on an 8760-hour basis. numeric {0;1} (8760*1).
inflows: Algebraic deviation of the state of charge of the storage, which does not induce any power generation or consumption on the system numeric {<0;>0} (8760*1).
lower_rule_curve: This is the lower limit for filling the stock imposed each hour. numeric {0;1} (8760*1).
upper_rule_curve: This is the upper limit for filling the stock imposed each hour. numeric {0;1} (8760*1).
cost_injection: Penalizes the injection flowrate at each hour (€/MWh) numeric {>0} (8760*1).
cost_withdrawal: Penalizes the withdrawal flowrate at each hour (€/MWh) numeric {>0} (8760*1).
cost_level: Penalizes the volume of stored energy at each hour (€/MWh) numeric {<0;>0} (8760*1).
cost_variation_injection: Penalizes injection flowrate variation every hour (€/MWh) numeric {>0} (8760*1).
cost_variation_withdrawal: Penalizes the withdrawal variation every hour (€/MWh) numeric {>0} (8760*1).
constraints_properties: list Parameters (see example)
constraints_ts: list of time series (see example)
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()

note

To write parameters to the list.ini file. You have function storage_values_default() who is called by default. This function return list containing properties according study version for cluster st-storage.

Study version >= "8.6.0" :

efficiency = 1 (numeric {0;1})
reservoircapacity = 0 (integer >= 0)
initiallevel = 0 (numeric {0;1})
withdrawalnominalcapacity = 0 (integer >= 0)
injectionnominalcapacity = 0 (integer >= 0)
initialleveloptim = FALSE (logical TRUE/FALSE)

Study version >= "8.8.0" (update + new parameter) :

initiallevel = 0.5 (numeric {0;1})
enabled = TRUE (logical TRUE/FALSE)

Study version >= "9.2" (new parameters) :

efficiencywithdrawal = 1 (numeric {0;1})
penalize-variation-injection = FALSE (logical TRUE/FALSE)
penalize-variation-withdrawal = FALSE logical TRUE/FALSE)

By default, these values don't allow you to have an active cluster (See example section.)

Examples

Run this code

if (FALSE) {

# list for cluster parameters : 
storage_values_default()

# create a cluster by default (with default parameters values + default data values):
createClusterST(area = "my_area", 
               "my_cluster") 
  
# Read cluster in study                            
 # by default, cluster name is prefixed 
 # by the area name
levels(readClusterSTDesc()$cluster)
# > "my_area_my_cluster"

# create cluster with custom parameter and data
  # use the function to create your own list of parameters (no Antares optim)
  # if you want optim (my_parameters$initialleveloptim <- TRUE)
my_parameters <- storage_values_default()
my_parameters$efficiency <- 0.5
my_parameters$initiallevel <- 10
my_parameters$withdrawalnominalcapacity <- 100
my_parameters$injectionnominalcapacity <- 1000
my_parameters$reservoircapacity <- 10000

  # time series 
inflow_data <- matrix(3, 8760)
ratio_data <- matrix(0.7, 8760)

createClusterST(area = "my_area", 
                "my_cluster",
                storage_parameters = my_parameters,
                PMAX_withdrawal = ratio_data, 
                inflows = inflow_data, 
                PMAX_injection = ratio_data, 
                lower_rule_curve = ratio_data, 
                upper_rule_curve = ratio_data)
                
# for a study version >= 9.2 (new parameters)
my_parameters <- storage_values_default()
my_parameters$efficiencywithdrawal <- 0.5
my_parameters$`penalize-variation-injection` <- TRUE
my_parameters$`penalize-variation-withdrawal` <- TRUE

createClusterST(area = "my_area", 
                "my_cluster",
                storage_parameters = my_parameters)
               
  # time series                  
ratio_value <- matrix(0.7, 8760)

# default properties with new optional TS
createClusterST(area = "fr", 
                cluster_name = "good_ts_value", 
                cost_injection = ratio_value, 
                cost_withdrawal = ratio_value, 
                cost_level = ratio_value, 
                cost_variation_injection = ratio_value,
                cost_variation_withdrawal = ratio_value)         
                
# Add optional constraints properties 
    
name_no_prefix <- "add_constraints"

constraints_properties <- list(
  "withdrawal-1"=list(
    variable = "withdrawal",
    operator = "equal",
    hours = c("[1,3,5]", 
              "[120,121,122,123,124,125,126,127,128]")
  ),
  "netting-1"=list(
    variable = "netting",
    operator = "less",
    hours = c("[1, 168]")
  ))

# create a cluster with constraint properties (no need to provide TS)
createClusterST(area = area_test_clust, 
                cluster_name = name_no_prefix, 
                constraints_properties = constraints_properties)         

   # Add optional constraints properties + TS 
   
constraints_properties <- list(
  "withdrawal-2"=list(
    variable = "withdrawal",
    operator = "equal",
    hours = c("[1,3,5]", 
              "[120,121,122,123,124,125,126,127,128]")
  ),
  "netting-2"=list(
    variable = "netting",
    operator = "less",
    hours = c("[1, 168]")
  ))    
   
good_ts <- matrix(0.7, 8760)
constraints_ts <- list(
  "withdrawal-2"=good_ts,
  "netting-2"=good_ts)

# create a cluster with constraint properties + TS
createClusterST(area = area_test_clust, 
                cluster_name = name_no_prefix, 
                constraints_properties = constraints_properties, 
                constraints_ts = constraints_ts)
}