select_years: Identify some representative time series of an ANTARES...
In rte-antares-rpackage/antaresXpansion: Antares Expansion Planning Tool

Description Usage Arguments Details Value Examples

Identify some representative time series of an ANTARES project containing a significant amount of Monte-Carlo years. Usually based on France (= mainAreas) load duration curves. Europe can also be imported as extraAreas to take energy imports and exports into account.

select_years(mainAreas = "fr", extraAreas = c("at", "be", "ch", "de", "es",
  "gb", "ie", "it", "nl", "pt"), selection = 5, MCYears = "all",
  weightMain = 0.3, weightPeakMain = 0.3, weightUnspEnrgMain = 0.3,
  weightExtra = 0.1, weightPeakExtra = 0,
  subtractUndispatchableEnergyMain = TRUE,
  subtractUndispatchableEnergyExtra = TRUE,
  subtractNuclearAvailabilityMain = TRUE,
  subtractNuclearAvailabilityExtra = FALSE, displayCurves = TRUE,
  displayTable = TRUE, opts = antaresRead::simOptions())

`mainAreas`	Vector containing the names of the areas on which the clustering algorithm will be based. Usually `mainAreas` = `"fr"`.
`extraAreas`	Vector containing the names of the additional areas on which the clustering algorithm will be based. Usually it contains areas that need to be taken into account in the algorithm but in a smaller scale than the ones in `mainAreas`. If `mainAreas` = `"fr"`, `extraAreas` must not contain `"fr"` again to be relevant enough. By default, the 10 most important areas in Europe (except France) are imported. If `NULL`, no extra area is imported.
`selection`	Numeric representing the amount of Monte-Carlo years to get after the function.
`MCYears`	Index of the Monte-Carlo years to import. If `"all"`, every MC years are read, else the specified Monte-Carlo simulations are imported.
`weightMain`	Numeric giving the weighting of the load duration curve for the main areas into the clustering algorithm choices. If `0`, no importance is given to this criteria. If `1`, the algorithm will be based only on this criteria.
`weightPeakMain`	Numeric giving the weighting of the peak period (for the 20 most crucial hours on the load duration curves) for the main areas into the clustering algorithm choices. If `0`, no importance is given to this criteria. If `1`, the algorithm will be based only on this criteria.
`weightUnspEnrgMain`	Numeric giving the weighting of the total unsupplied energy for the main areas into the clustering algorithm choices. If `0`, no importance is given to this criteria. If `1`, the algorithm will be based only on this criteria.
`weightExtra`	Numeric giving the weighting of the load duration curve for the additional areas into the clustering algorithm choices. It is usually lower than `WeightExtra`. If `0`, no importance is given to this criteria. If `1`, the algorithm will be based only on this criteria.
`weightPeakExtra`	Numeric giving the weighting of the peak period (for the 20 most crucial hours on the load duration curves) for the additional areas into the clustering algorithm choices. It is usually lower than `WeightPeakMain`. If `0`, no importance is given to this criteria. If `1`, the algorithm will be based only on this criteria.
`subtractUndispatchableEnergyMain`	If `TRUE`, undispatchable energy (Solar, Wind, etc.) is subtracted from LOAD of the main areas.
`subtractUndispatchableEnergyExtra`	If `TRUE`, undispatchable energy (Solar, Wind, etc.) is subtracted from LOAD of the additional areas.
`subtractNuclearAvailabilityMain`	If `TRUE`, nuclear availability is subtracted from LOAD of the main areas.
`subtractNuclearAvailabilityExtra`	If `TRUE`, nuclear availability is subtracted from LOAD of the additional areas.
`displayCurves`	If `TRUE`, the function displays a load duration curve analysis
`displayTable`	If `TRUE`, the function displays a cost analysis (LOAD, OP. COST, LOLD, UNSP. ENRG)
`opts`	List of simulation parameters returned by the function `antaresRead::setSimulationPath`

When subtractUndispatchableEnergyMain, subtractUndispatchableEnergyExtra, subtractNuclearAvailabilityMain and subtractNuclearAvailabilityExtra are all TRUE, the function may crash because of insufficient memory. In such a case, it is necessary to reduce the size of the input. Different strategies are available depending on your objective : reduce the number of Monte-Carlo years, do not subtract nuclear availability (especially on extra areas), take fewer areas, increase the memory (with setRam), etc.

If displayCurves and displayTable are both FALSE, only identities and weightings of the selected Monte-Carlo years are displayed. Else, load duration curves for imported areas will be also plotted (for every MC years, clusters and average curves) and a cost analysis will be given (based on ANNUAL LOAD, OP. COST, LOLD and UNSP. ENRG).

# Import simulation
setSimulationPath()

# Find 5 Monte-Carlo year clusters for the simulation
# Study France as the main area and 3 European countries as the secondary area
# Base algorithm on :
# 30% for the load duration curve in France
# 30% for the peak period in France
# 30% for the total unsupplied energy in France
# 10% for the load duration curve in all europe
# 0% for the peak period in all europe
select_years(mainAreas = "fr", extraAreas = c("es", "gb", "it"), weightMain = 0.3, weightPeakMain = 0.3, weightUnspEnrgMain = 0.3, weightExtra = 0.1)