This document describes a typical use of the
This package has been designed to read the results of an Antares simulation in an easy and convivial way. It can of course read any output files of a simulation at any desired time step, read synthetic results or detailed Monte Carlo scenarios but it can also add input time series to the results and perform some basic treatments like removing virtual areas.
antaresRead package depends on the packages
lubridate. If you have not already got them you can install them with the following command:
Then you can install the
antaresRead package either with the Rstudio assistant in the “Packages” tab or with the following command:
First, when you start a new R session, you need to load the package:
To display the list of all the functions of the package and access their help pages, type in the R console:
Then you can start using the package. The first function to use is
This function needs to be called at least once during each R session. It stores important informations that are used by most of the functions of the package. While it has not been run, these functions will not work.
Without any argument,
setSimulationPath asks interactively to choose a directory containing an antares study. If the study contains multiple simulation results, it will also asks the user to choose one of them. This function stores the path to the output and reads some useful information about the simulation: type of output available, list of areas, links and clusters in the simulation, variables present in the output files, etc.
setSimulationPath can also be used in a non-interactive way with one of these syntaxes:
# Specify full path setSimulationPath("study_path/output/simulation_name") # Specify the name of the simulation setSimulationPath("study_path", simulation_name) # Select a simulation by order setSimulationPath("study_path", 1) # first simulation # Select a simulation by reverse order setSimulationPath("study_path", -1) # last simulation # It is possible to store in a variable the result of the function opts <- setSimulationPath("study_path", 1)
The function returns an object containing informations about the selected simulation. You can store this object in a variable for later use but this is not necessary because at any moment you can retrieve these informations.
setSimulationPath has been run, you can start reading data. Function
readAntares is there for that !
readAntares is the main function of the package. It is used to read every possible time series and it performs a few treatments on them to make your life easier. The result of the function will have the simplest structure possible: either a simple table or a list of tables if you asks data for differents elements (for instance links and areas)
It has a huge number of parameters to control exactly what you get, but all of them are optional. Without any argument the function will still works and it will read the synthetic results for all the areas. But you can import other kind of output. here are some examples:
You can also choose what elements to import and what level of details you want. For instance, the following command reads the first 10 Monte-Carlo scenarii data at monthly time step for the areas named “area1”, “area2” and “area3”.
Finally many arguments of
readAntares can be used to add input time series to the object returned by the function. For instance,
misc=TRUE will add columns containing miscelaneous productions for the imported areas.
readAntares returns either a single table or a list of tables depending on the query of the user. More precisely the tables are
data.table objects. It is then possible to use the powerful syntax offered by the package
The general syntax is like:
areas[area == "08_fr", .(timeId, LOAD)] will return a table containing columns
LOAD for the area names “08_fr”. In the select statement, it is also possible to calculate new columns. For instance, one can compute the net load like this:
One can also compute aggregated statistics. For instance, the following code will compute the total load of all areas per
Of course, aggregation also works with filters. For instance to compute the total load only for french areas (assuming their names contain “fr”):
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:
readAntares can import almost everything but not everything because some data is not time series. Other functions exist to read this specific data:
readBindingConstraints to read binding constraints,
readClusterDesc to read cluster characteristics and
readLayout to get the coordinates of the areas in the user interface of Antares.
Some parameters in
readAntares and other functions wait for vectors of area names or link names. On large projects with lots of areas. It may be painful to specify by hand a long list of areas or links. Hopefully, the functions
getLinks can be used to select or exclude areas using regular expressions. For instance, let us assume that the name of all areas located in France start with the characters“fr”, then the following command returns the list of all french areas:
To exclude offshore production areas (assuming their name contains the word “offshore”) one can use:
A few other functions are provided by the package. To see a list of them, type in the console: