capacity_value: Calculate capacity value for variable generation
In NREL/repra: Renewable Energy Probability Resource Assessment Tool (REPRA)

Description Usage Arguments Details See Also Examples

View source: R/capacity_value.R

Given time data series and an outage table, calculate the capacity value of variable generation (VG) time series. Capacity value is calculated by iteratively removing one type of VG at a time and recalculating effective load carrying capability (ELCC).

1 2	capacity_value(time.data, outage.table, VG.cols = NULL, marginal = FALSE, scale.first = FALSE, ...)

`time.data`	Time series data (or subset) formatted with `format_timedata`
`outage.table`	Outage table used in the lookup, created with `outage_table`
`VG.cols`	Order in which VG capacity value is calculated (see details for more info)
`marginal`	Should the VG capacity value be calculated as the last resource (`TRUE`) or added progressively to the load (`FALSE`)?
`scale.first`	This triggers a special case to calculate capacity value. See details for more information.
`...`	Additional parameters passed to `calculate_elcc` and `sliding_window`

This function calculates ELCC for the system with different combinations of VG. The metric and desired reliability metric can be set; see calculate_elcc for details and a list of parameters. Additionally, a sliding window can be used in the calculation (see calculate_elcc).

When calculating the capacity value of VG, the results depends on the order in which the different technologies are added into the system. The variable VG.cols is used to determine this order manually. If not determined the order will default to the order in which the VG columns appear in time.data.

This marginal parameter determines if the capacity value is calculated by taking each VG profile out of the total mix (when is set to TRUE) or by progressively stacking the VG profiles on top the conventional generators (when is set to FALSE). The latter option is the default and the order is determined by the VG.cols parameter or, if not set, by the order in which the columns appear in the time.data object.

If scale.first is set to TRUE the capacity value a special calculation is triggered. Before perfoming the calculations, the load is scaled so that the total mix (conventional generators and VG) provide the desired adequacy level, which is specified with the parameters passed to calculate_elcc. Once the load is scaled, the capacity value calculations are performed using the flat block method.

format_timedata and outage_table to create time.data and outage.table objects, respectively

sliding_window is used internally to extend time.data

calculate_elcc is used internally to evaluate ELCC

## Not run: 
# Create outage table with 200 5-MW units
gens <- data.frame(Capacity = rep(5, 200),
                   EFOR = rep(0.08, 200))
out.table <- outage_table(gens)

# Create random load and wind data and format
tdata <- data.frame(Time = 1:8760,
                    Load = runif(8760, 450, 850),
                    Wind = runif(8760, 0, 100),
                    Wind2 = runif(8760, 0, 200))
td <- format_timedata(tdata)

# Calculate capacity value (both are equivalent)
capacity_value(td, out.table)
capacity_value(td, out.table, c("Wind", "Wind2"))

# Calculate capacity value of Wind2 first and Wind second
capacity_value(td, out.table, c("Wind", "Wind2"))

# Calculate capacity value with a sliding window that uses adjacent hours
capacity_value(td, out.table, win.h.size = c(-1, 1))

## End(Not run)