prepareFeatureSet {SmartMeterAnalytics}

Compiles a list of features from energy consumption data

Description

Returns a vector of feature names that can be calculated by methods in the *SmartMeterAnalytics* package obtains the feature set according

Usage

prepareFeatureSet(
  features.granularity = NA,
  features.w_adj = FALSE,
  features.anonymized = FALSE,
  features.categorical = FALSE,
  features.geo = "osm-v1",
  features.temperature = TRUE,
  features.weather = TRUE,
  features.neighborhood = FALSE
)

Arguments

features.granularity

Character: The granularity of the input data, either "15-min" (only 15-min features), "30-min" (only 30-minute features), "all_30min_to_week" (all features on daily, weekly, hourly, ..., up to 30-min data), "all_15_week" (all up to 15-min dara), "week" (only the consumption of one week as a single feature).

features.w_adj

Boolean: are the features to be weather adjusted with DiD-Class (NOT IMPLEMENTED YET!)

features.anonymized

Boolean: are anonymized geographic features used (NOT IMPLEMENTED YET!)

features.categorical

Boolean: use categorical features additionally (if only numeric features are used)

features.geo

Character: Version of the geographic feature set (either "none", "osm-v1", "osm-v2")

features.temperature

Boolean, if features for the temperature should be included

features.weather

Boolean, if other weather features should be included

features.neighborhood

Boolean, if features for the neighborhood should be included

Value

Character vector

Author(s)

Konstantin Hopf [e-mail]

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

Beckel, C., Sadamori, L., Staake, T., & Santini, S. (2014). Revealing household characteristics from smart meter data. Energy, 78, 397–410. https://doi.org/10.1016/j.energy.2014.10.025