| calc_featuresnt_consumption {SmartMeterAnalytics} | R Documentation |
Calculates consumption features from daily (HT / NT) smart meter data
Description
The division in HT / NT is done from the input smart meter data
Usage
calc_featuresnt_consumption(
B,
rowname = NULL,
featsCoarserGranularity = FALSE,
replace_NA_with_defaults = TRUE
)
Arguments
B |
a vector with length 2*24*7 = 336 measurements in one day in seven days a week |
rowname |
the row name of the resulting feature vector |
featsCoarserGranularity |
are the features of finer granularity levels also to be calculated (TRUE/FALSE) |
replace_NA_with_defaults |
an optional boolean argument specifying if missing values will be replaced with standard values (i.e., zero values) |
Details
HT consumption is during the time 07:00-22:00
Author(s)
Konstantin Hopf konstantin.hopf@uni-bamberg.de
References
Hopf, K. (2019). Predictive Analytics for Energy Efficiency and Energy Retailing (1st ed.). Bamberg: University of Bamberg. https://doi.org/10.20378/irbo-54833
Hopf, K., Sodenkamp, M., Kozlovskiy, I., & Staake, T. (2014). Feature extraction and filtering for household classification based on smart electricity meter data. Computer Science-Research and Development, (31) 3, 141–148. https://doi.org/10.1007/s00450-014-0294-4
Hopf, K., Sodenkamp, M., & Staake, T. (2018). Enhancing energy efficiency in the residential sector with smart meter data analytics. Electronic Markets, 28(4). https://doi.org/10.1007/s12525-018-0290-9