analyze.p2: Apply Period 2 Analysis

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

Description

Conducts period 2 analysis; uses the optimal set of variables obtained in the period 1 analysis to predict the power output of REF and CTR-b turbines in period 2.

Usage

analyze.p2(per1, per2, opt.cov)

Arguments

per1	A dataframe containing the period 1 data.
per2	A dataframe containing the period 2 data.
opt.cov	A character vector indicating the optimal set of variables (obtained from the period 1 analysis).

Value

The function returns a list of the following datasets.

pred.REF

A dataframe including the period 2 prediction for the REF turbine.

pred.CTR

A dataframe including the period 2 prediction for the CTR-b turbine.

References

H. Hwangbo, Y. Ding, and D. Cabezon, 'Machine Learning Based Analysis and Quantification of Potential Power Gain from Passive Device Installation,' arXiv:1906.05776 [stat.AP], Jun. 2019. https://arxiv.org/abs/1906.05776.

Examples

df.ref <- with(wtg, data.frame(time = time, turb.id = 1, wind.dir = D,
 power = y, air.dens = rho))
df.ctrb <- with(wtg, data.frame(time = time, turb.id = 2, wind.spd = V,
 power = y))
df.ctrn <- df.ctrb
df.ctrn$turb.id <- 3

data <- arrange.data(df.ref, df.ctrb, df.ctrn, p1.beg = '2014-10-24',
 p1.end = '2014-10-25', p2.beg = '2014-10-25', p2.end = '2014-10-26',
 k.fold = 2)

p1.res <- analyze.p1(data$train, data$test, ratedPW = 1000)
p2.res <- analyze.p2(data$per1, data$per2, p1.res$opt.cov)

gainML documentation built on June 28, 2019, 5:05 p.m.