First it’s necessary to load the package:
library(antaresEditObject)You need to set the path to an Antares study in “input” mode:
antaresRead::setSimulationPath(path = "path/to/study", simulation = "input")Or you can simply create a new study:
createStudy("path/to/study")Before modifying your study, you can save it in an archive:
backupStudy(what = "input")This will create a .tar.gz file in your study folder.
You can create a new area with:
createArea(name = "myarea")
# The new area should appear here:
antaresRead::getAreas()You can specify the localization of the area on the map, and also its color.
There are two helper functions for area parameters:
filteringOptions() for filtering options, like filter-year-by-yearnodalOptimizationOptions() for nodal optimizations options.You can initialize a cluster with some parameters:
createCluster(
area = "myarea",
cluster_name = "myareacluster",
group = "other",
unitcount = 1,
nominalcapacity = 8400,
`min-down-time` = 0,
`marginal-cost` = 0.010000,
`market-bid-cost` = 0.010000
)You can also edit the settings of an existing cluster:
editCluster(
area = "myarea",
cluster_name = "myareacluster",
nominalcapacity = 10600.000
)createLink(
from = "area1",
to = "area2",
propertiesLink = propertiesLinkOptions(
hurdles_cost = FALSE,
transmission_capacities = "enabled"
),
dataLink = NULL
)You can edit the settings of an existing link:
editLink(
from = "area1",
to = "area2",
transmission_capacities = "infinite"
)createBindingConstraint(
name = "myconstraint",
values = matrix(data = c(rep(c(19200, 0, 0), each = 366)), ncol = 3),
enabled = FALSE,
timeStep = "daily",
operator = "both",
coefficients = c("fr%myarea" = 1)
)pspData <- data.frame(
area = c("a", "b"),
installedCapacity = c(800,900)
)
createPSP(
areasAndCapacities = pspData,
efficiency = 0.75
)dsrData <- data.frame(
area = c("a", "b"),
unit = c(10,20),
nominalCapacity = c(100, 120),
marginalCost = c(52, 65),
hour = c(3, 7)
)
createDSR(dsrData)For example, set the output of simulation year by year, and limit the number of Monte-Carlo years to 10:
updateGeneralSettings(year.by.year = TRUE, nbyears = 10)You can remove areas, links, clusters and binding constraints from input folder with remove* functions, e.g.:
removeArea("myarea")First, update general settings to activate time series to generate:
updateGeneralSettings(generate = "thermal")Then run TS-generator:
runTsGenerator(
path_solver = "C:/path/to/antares-solver.exe",
show_output_on_console = TRUE
)Launch an Antares simulation from R:
runSimulation(
name = "myAwesomeSimulation",
mode = "economy",
path_solver = "C:/path/to/antares-solver.exe",
show_output_on_console = TRUE
)