R/freq_data.R

In gainML: Machine Learning-Based Analysis of Potential Power Gain from Passive Device Installation on Wind Turbine Generators

#' Long-Term Frequency of Power Output
#'
#' A dataset containing power bins, the proportion of observing each power bin,
#' and the accumulated hours of observing each power bin.
#'
#' @format A data frame with 10 rows and 3 columns: \describe{
#'   \item{\code{PW_bin}}{the right end point of the intervals defining power
#'   bins} \item{\code{freq}}{the proportion of observing each power bin from
#'   historical data} \item{\code{freq_h}}{the accumulated hours of observing
#'   each power bin from historical data} }
#'
#' @note \itemize{ \item This dataset is provided to show how a user is expected
#'   to structure the long-term frequency data, which will be used in
#'   \code{\link{analyze.gain}} or in \code{\link{quantify.gain}}. \item In the
#'   gain analysis performed by \code{\link{analyze.gain}}, power bins will be
#'   defined with 100kW increments. To be consistent, \code{PW_bin} must be
#'   defined with 100kW increments. For example, if rated power is 1,000kW
#'   (1MW), power bins shalle be generated by using the intervals of [0kW,
#'   100kW], [100kW, 200kW], \eqn{ \ldots}, [900kW, 1000kW]. \item The gain
#'   analysis will only need the information specified in \code{freq_h}, so as
#'   long as the elements in this column correponds to each power bin (with
#'   100kW increments) and the number of elements matches the number of power
#'   bins, there should not be any problem. }
#'
"pw.freq"