Calculates features from one environmental time-series variable and smart meter data
calc_features_weather(SMD, WEATHER, rowname = NULL)
the load trace for one week (vector with 672 or 336 elements)
weather observations (e.g. temperature) in 30-minute readings (vector with 336 elements)
the row name of the current data point
Konstantin Hopf konstantin.hopf@uni-bamberg.de, Ilya Kozlovslkiy
Hopf, K. (2019). Predictive Analytics for Energy Efficiency and Energy Retailing (1st ed.). Bamberg: University of Bamberg. tools:::Rd_expr_doi("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. tools:::Rd_expr_doi("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). tools:::Rd_expr_doi("10.1007/s12525-018-0290-9")