CSIndicators (version 1.1.2)

CST_WindCapacityFactor: Wind capacity factor on s2dv_cube objects

Description

Wind capacity factor computes the wind power generated by a specific wind turbine model under specific wind speed conditions, and expresses it as a fraction of the rated capacity (i.e. maximum power) of the turbine.

It is computed by means of a tabular power curve that relates wind speed to power output. The tabular values are interpolated with a linear piecewise approximating function to obtain a smooth power curve. Five different power curves that span different IEC classes can be selected (see below).

Usage

CST_WindCapacityFactor(
  wind,
  IEC_class = c("I", "I/II", "II", "II/III", "III"),
  start = NULL,
  end = NULL,
  time_dim = "time",
  ncores = NULL
)

Value

An s2dv_cube object containing the Wind Capacity Factor (unitless).

Arguments

wind

An s2dv_cube object with instantaneous wind speeds expressed in m/s.

IEC_class

A string indicating the IEC wind class (see IEC 61400-1) of the turbine to be selected. Classes 'I', 'II' and 'III' are suitable for sites with an annual mean wind speed of 10, 8.5 and 7.5 m/s respectively. Classes 'I/II' and 'II/III' indicate intermediate turbines that fit both classes. More details of the five turbines and a plot of its power curves can be found in Lledó et al. (2019).

start

An optional parameter to defined the initial date of the period to select from the data by providing a list of two elements: the initial date of the period and the initial month of the period. By default it is set to NULL and the indicator is computed using all the data provided in data.

end

An optional parameter to defined the final date of the period to select from the data by providing a list of two elements: the final day of the period and the final month of the period. By default it is set to NULL and the indicator is computed using all the data provided in data.

time_dim

A character string indicating the name of the dimension to compute the indicator. By default, it is set to 'time'. More than one dimension name matching the dimensions provided in the object data$data can be specified.

ncores

An integer indicating the number of cores to use in parallel computation for temporal subsetting.

Author

Llorenç Lledó,

References

Lledó, Ll., Torralba, V., Soret, A., Ramon, J., & Doblas-Reyes, F. J. (2019). Seasonal forecasts of wind power generation. Renewable Energy, 143, 91–100. https://doi.org/10.1016/j.renene.2019.04.135

International Standard IEC 61400-1 (third ed.) (2005)

Examples

wind <- NULL
wind$data <- array(rweibull(n = 100, shape = 2, scale = 6), 
                  c(member = 5, sdate = 3, time = 214, lon = 2, lat = 5))
wind$coords <- list(lat =  c(40, 41), lon = 1:5)
variable <- list(varName = 'sfcWind', 
                metadata = list(sfcWind = list(level = 'Surface')))
wind$attrs <- list(Variable = variable, Datasets = 'synthetic', 
                  when = Sys.time(), Dates = '1990-01-01 00:00:00')
Dates <- c(seq(as.Date("01-05-2000", format = "%d-%m-%Y"), 
                        as.Date("30-11-2000", format = "%d-%m-%Y"), by = 'day'),
                    seq(as.Date("01-05-2001", format = "%d-%m-%Y"), 
                        as.Date("30-11-2001", format = "%d-%m-%Y"), by = 'day'),
                    seq(as.Date("01-05-2002", format = "%d-%m-%Y"), 
                        as.Date("30-11-2002", format = "%d-%m-%Y"), by = 'day'))
dim(Dates) <- c(sdate = 3, time = 214)
wind$attrs$Dates <- Dates
class(wind) <- 's2dv_cube'
WCF <- CST_WindCapacityFactor(wind, IEC_class = "III", 
                             start = list(21, 4), end = list(21, 6))