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#'Wind capacity factor on s2dv_cube objects
#'
#'@author Llorenç Lledó, \email{llledo@bsc.es}
#'@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.
#'@description 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).
#'@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
#'@references International Standard IEC 61400-1 (third ed.) (2005)
#'
#'@param wind An s2dv_cube object with instantaneous wind speeds expressed in m/s.
#'@param IEC_class A string indicating the IEC wind class (see IEC 61400-1) of
#' the turbine to be selected. Classes \code{'I'}, \code{'II'} and \code{'III'}
#' are suitable for sites with an annual mean wind speed of 10, 8.5 and 7.5 m/s
#' respectively. Classes \code{'I/II'} and \code{'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).
#'@param 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
#' \code{data}.
#'@param 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 \code{data}.
#'@param 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
#' \code{data$data} can be specified.
#'@param ncores An integer indicating the number of cores to use in parallel
#' computation for temporal subsetting.
#'@return An s2dv_cube object containing the Wind Capacity Factor (unitless).
#'
#'@examples
#'wind <- NULL
#'wind$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))
#'
#'@export
CST_WindCapacityFactor <- function(wind, IEC_class = c("I", "I/II", "II", "II/III", "III"),
start = NULL, end = NULL, time_dim = 'time',
ncores = NULL) {
# Check 's2dv_cube'
if (!inherits(wind, 's2dv_cube')) {
stop("Parameter 'wind' must be of the class 's2dv_cube'.")
}
# Dates subset
if (!is.null(start) && !is.null(end)) {
if (is.null(dim(wind$attrs$Dates))) {
warning("Dimensions in 'wind' element 'attrs$Dates' are missed and ",
"all data would be used.")
start <- NULL
end <- NULL
}
}
WindCapacity <- WindCapacityFactor(wind = wind$data, IEC_class = IEC_class,
dates = wind$attrs$Dates, start = start,
end = end, time_dim = time_dim,
ncores = ncores)
wind$data <- WindCapacity
wind$dims <- dim(WindCapacity)
if ('Variable' %in% names(wind$attrs)) {
if ('varName' %in% names(wind$attrs$Variable)) {
wind$attrs$Variable$varName <- 'WindCapacityFactor'
}
}
if (!is.null(start) && !is.null(end)) {
wind$attrs$Dates <- SelectPeriodOnDates(dates = wind$attrs$Dates,
start = start, end = end,
time_dim = time_dim,
ncores = ncores)
}
return(wind)
}
#'Wind capacity factor
#'
#'@author Llorenç Lledó, \email{llledo@bsc.es}
#'@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.
#'@description 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).
#'@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
#'@references International Standard IEC 61400-1 (third ed.) (2005)
#'
#'@param wind A multidimensional array, vector or scalar with instantaneous wind
#' speeds expressed in m/s.
#'@param IEC_class A string indicating the IEC wind class (see IEC 61400-1) of
#' the turbine to be selected. Classes \code{'I'}, \code{'II'} and \code{'III'}
#' are suitable for sites with an annual mean wind speed of 10, 8.5 and 7.5 m/s
#' respectively. Classes \code{'I/II'} and \code{'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).
#'@param dates A multidimensional array of dates with named dimensions matching
#' the temporal dimensions on parameter 'data'. By default it is NULL, to
#' select aperiod this parameter must be provided.
#'@param 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
#' \code{data}.
#'@param 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 \code{data}.
#'@param 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
#' \code{data$data} can be specified.
#'@param ncores An integer indicating the number of cores to use in parallel
#' computation for temporal subsetting.
#'
#'@return An array with the same dimensions as wind, containing the Wind
#' Capacity Factor (unitless).
#'
#'@examples
#'wind <- array(rweibull(n = 32100, shape = 2, scale = 6),
#' c(member = 5, sdate = 3, time = 214, lon = 2, lat = 5))
#'
#'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)
#'
#'WCF <- WindCapacityFactor(wind, IEC_class = "III", dates = Dates,
#' start = list(21, 4), end = list(21, 6))
#'
#'@importFrom stats approxfun
#'@importFrom utils read.delim
#'@export
WindCapacityFactor <- function(wind, IEC_class = c("I", "I/II", "II", "II/III", "III"),
dates = NULL, start = NULL, end = NULL,
time_dim = 'time', ncores = NULL) {
IEC_class <- match.arg(IEC_class)
pc_files <- c(
"I" = "Enercon_E70_2.3MW.txt",
"I/II" = "Gamesa_G80_2.0MW.txt",
"II" = "Gamesa_G87_2.0MW.txt",
"II/III" = "Vestas_V100_2.0MW.txt",
"III" = "Vestas_V110_2.0MW.txt"
)
pc_file <- system.file("power_curves", pc_files[IEC_class], package = "CSIndicators", mustWork = T)
pc <- read_pc(pc_file)
if (!is.null(start) && !is.null(end)) {
if (is.null(dates)) {
warning("Parameter 'dates' is NULL and the average of the ",
"full data provided in 'data' is computed.")
} else {
if (!any(c(is.list(start), is.list(end)))) {
stop("Parameter 'start' and 'end' must be lists indicating the ",
"day and the month of the period start and end.")
}
if (!is.null(dim(dates))) {
wind <- SelectPeriodOnData(data = wind, dates = dates, start = start,
end = end, time_dim = time_dim,
ncores = ncores)
} else {
warning("Parameter 'wind' must have named dimensions if 'start' and ",
"'end' are not NULL. All data will be used.")
}
}
}
cf <- wind2CF(wind, pc)
dim(cf) <- dim(wind)
return(cf)
}
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