calculate_elcc: Calculate effective load carrying capability (ELCC)

In NREL/repra: Renewable Energy Probability Resource Assessment Tool (REPRA)

Description

Given a time data object (with net load data), find the effective load carrying capability (ELCC) to achieve the desired reliability metric. The function automatically applies these calculation for each scenario, level or aggregation and area.

Usage

calculate_elcc(time.data, outage.table, obj.metric = "LOLE",
  obj.value = 0.1, scale.load = FALSE, max.iter = 20, ignore = NULL,
  ...)

Arguments

time.data	Time series data formatted with format_timedata
outage.table	Outage table used in the lookup, created with outage_table
obj.metric	Metric to be used as objective: LOLE, LOLH, PeakLOLP, EUE (see details)
obj.value	Objective value to achieve for the selected metric
scale.load	During the iterations is the load scaled (TRUE) or the same value added to all times (FALSE)
max.iter	Maximum iterations to perform before stopping
ignore	Column names in time.data to ignore in the calculation of total VG data
...	Additional parameters passed to sliding_window

Details

The following metrics can be selected as an objective (through obj.metric):

• Daily loss of load expectation (LOLE): Calculated as the sum of the maximum daily LOLP

• Loss of load hours (LOLH): Sum of all the LOLP

• Maximum daily LOLP (PeakLOLP): Maximum LOLP value observed

• Expected unserved energy (EUE): Sum of EUE for all time steps

ELCC is calculated by modifying the load profile so that the final profile yields a certain reliability level. This can be done in two ways:

• by scaling the entire profile (e.g., by multiplying the entire time series by 1.05)

• by adding a constant number to the entire profiles (e.g., adding 100 MW)

scale.load needs to be set to TRUE or FALSE to achieve either one, respectively.

See Also

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

sliding_window is used internally to extend time.data

calculate_metrics is used internally to evaluate the metrics

Examples

# 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 ELCC with both Wind and Wind2
calculate_elcc(td, out.table)

# Calculate ELCC with only Wind
calculate_elcc(td, out.table, ignore = "Wind2")

NREL/repra documentation built on May 7, 2019, 6:03 p.m.