WindCurves: A Tool to Fit Wind Turbine Power Curves"

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)

Introduction:

This is a Vignettes of R package, WindCurves. The package WindCurves is a tool used to fit the wind turbine power curves. It can be useful for researchers, data analysts/scientist, practitioners, statistians and students working on wind turbine power curves. The salient features of WindCurves package are:

Instructions to Use:

library(WindCurves)
data(pcurves)
s <- pcurves$Speed
p <- pcurves$`Nordex N90`
da <- data.frame(s,p)
x <- fitcurve(da)
x
validate.curve(x)
plot(x)
random <- function(x)
{
  data_y <- sort(sample(1:1500, size = 25, replace = TRUE))
  d <- data.frame(data_y)
  return(d)
}
dump("random")
rm(random)
library(WindCurves)
data(pcurves)
s <- pcurves$Speed
p <- pcurves$`Nordex N90`
da <- data.frame(s,p)
x <- fitcurve(data = da, MethodPath = "source('dumpdata.R')", MethodName = "Random values")

## The user can specify .R files from other locations as:
# x <- fitcurve(data = da, MethodPath = "source('~/WindCurves/R/random.R')", MethodName = "Random values")
validate.curve(x)
plot(x)

Consider error() is a function which uses two vectors as input and returns a error value with a specific error measure, such as RMSE or MAPE as shown below:

# PCV as an error metric
error <- function(a,b)
{
d <- (var(a) - var(b)) * 100/ var(a)
d <- as.numeric(d)
return(d)
}
dump("error")
rm(error)

The effect of this function can be seen in the results obtained with Validate.curve() function as:

library(WindCurves)
data(pcurves)
s <- pcurves$Speed
p <- pcurves$`Nordex N90`
da <- data.frame(s,p)
x <- fitcurve(da)
validate.curve(x = x, MethodPath = "source('dumpdata.R')", MethodName = "New Error")
plot(x)

Similarly, user can compare various techniques used for wind turbine power curve fitting.

data(pcurves)
pcurves
#img2points("image.jpeg")

where, image.jpeg is the name of power curve image from which discrete points are to extracted. The procedure of extraction is as follows:

References

[1] D. Villanueva and A. E. Feij´oo, “Reformulation of parameters of the logistic function applied to power curves of wind turbines,” Electric Power Systems Research, vol. 137, pp. 51–58, 2016.(via)

[2] Iain Staffell, “Wind turbine power curves, 2012” (via)



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WindCurves documentation built on May 2, 2019, 2:06 a.m.