You can install the package from CRAN:
install.packages("antaresRead")You can also install the last development version from Github:
devtools::install_github("rte-antares-rpackage/antaresRead", ref ="develop")To display the help of the package and see all the functions it provides, type:
help(package="antaresRead")To see a practical example of use of the package, look at the vignette :
vignette("antares")Finally, you can download a cheatsheet that summarize in a single page how to use the package: https://github.com/rte-antares-rpackage/antaresRead/raw/master/cheat_sheet/antares_cheat_sheet_en.pdf .
Load the package
library(antaresRead)Select an Antares simulation interactively.
setSimulationPath()You can also select it programmatically:
setsimulationPath("study_path", simulation)The parameter simulation can be the name of a simulation, the name of the folder containing the simulation results, or the index of the simulation. 1 corresponds to the oldest simulation, -1 to the newest one, 0 to the inputs.
Most data from a simulation can be imported in the R session with function readAntares(). It has many parameters that control what data is imported. Here are a few examples:
# Read synthetic results of all areas of a study with hourly time step.
areaData <- readAntares(areas = "all")
# Same but with a daily time step:
areaData <- readAntares(areas = "all", timeStep = "daily")
# Read all Monte Carlo scenarios for a given area.
myArea <- readAntares(areas = "my_area", mcYears = "all")
# Same but add miscelaneous production time series to the result
myArea <- readAntares(areas = "my_area", mcYears = "all", misc = TRUE)
# Read only columns "LOAD" and "MRG. PRICE"
areaData <- readAntares(areas = "all", select = c("LOAD", "MRG. PRICE"))Functions getAreas and getLinks are helpful to create a selection of areas or links of interest. Here are a few examples:
# select areas containing "fr"
myareas <- getAreas("fr")
# Same but remove areas containing "hvdc"
myareas <- getAreas("fr", exclude = "hvdc")
# Get the links that connect two of the previous areas
mylinks <- getLinks(myareas, internalOnly = FALSE)
# Get the results for these areas and links
mydata <- readAntares(areas = myareas, links = mylinks)When only one type of elements is imported (only areas or only links, etc.) readAntares() read antares returns a data.table with some extra attributes. A data.table is a table with some enhanced capacities offered by package data.table. In particular it provides a special syntax to manipulate its content:
name_of_the_table[filter_rows, select_columns, group_by]Here are some examples:
# Select lines based on some criteria
mydata[area == "fr" & month == "JUL"]
# Select columns, and compute new ones
mydata[, .(area, month, load2 = LOAD^2)]
# Aggregate data by some variables
mydata[, .(total = sum(LOAD)), by = .(month)]
# All three operations can be done with a single line of code
mydata[area == "fr", .(total = sum(LOAD)), by = .(month)]
help(package = "data.table")If you are not familiar with package data.table, you should have a look at the documentation and especially at the vignettes of the package:
help(package="data.table")
vignette("datatable-intro")Contributions to the library are welcome and can be submitted in the form of pull requests to this repository.
The folder test_case contains a test Antares study used to run automatic tests. If you modifies it, you need to run the following command to include the modifications in the tests:
tar(
tarfile = "inst/testdata/antares-test-study.tar.gz",
files = "test_case",
compression = "gzip"
)Antares is a powerful software developed by RTE to simulate and study electric power systems (more information about Antares here : https://antares.rte-france.com).
Copyright 2015-2016 RTE (France)
This Source Code is subject to the terms of the GNU General Public License, version 2 or any higher version. If a copy of the GPL-v2 was not distributed with this file, You can obtain one at https://www.gnu.org/licenses/old-licenses/gpl-2.0.en.html.