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SmartMeterAnalytics (version 1.1.1)

Methods for Smart Meter Data Analysis

Description

Methods for analysis of energy consumption data (electricity, gas, water) at different data measurement intervals. The package provides feature extraction methods and algorithms to prepare data for data mining and machine learning applications. Deatiled descriptions of the methods and their application can be found in Hopf (2019, ISBN:978-3-86309-669-4) "Predictive Analytics for Energy Efficiency and Energy Retailing" and Hopf et al. (2016) "Enhancing energy efficiency in the residential sector with smart meter data analytics".

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Version

Install

install.packages('SmartMeterAnalytics')

Monthly Downloads

157

Version

1.1.1

License

MIT + file LICENSE

Maintainer

Konstantin Hopf

Last Published

April 19th, 2025

Functions in SmartMeterAnalytics (1.1.1)

Retrieves the date of the monday in a US week-string (as implemented by R as.Date)

getDay_ISO8601_week

Retrieves the date of the monday in a ISO8601 week-string

calc_features30_consumption

Calculates features from 30-min smart meter data

calc_featureshtnt_consumption2

Calculates consumption features from daily (HT / NT) smart meter data

calc_featuresco_consumption

Calculates consumption features from weekly consumption only

calc_features_daily_multipleTS

Calculates feature from multiple time series data vectors

calc_features60_consumption

Calculates features from 15-min smart meter data

calc_features15_consumption

Calculates features from 15-min smart meter data

calc_featuresda_consumption

Calculates consumption features from daily smart meter data

encode_p_val_stars

Encodes p-values with a star rating according to the Significance code:

calc_featuresnt_consumption

Calculates consumption features from daily (HT / NT) smart meter data

calc_features_weather

Calculates features from one environmental time-series variable and smart meter data

interpolate_missingReadings

Interpolate missing readings

prepareFeatureSet

Compiles a list of features from energy consumption data

replaceNAsFeatures

Replaces NA values with a given ones

Removes the rows with NA or Inf values

occupancy_cluster

Determines two clusters of high and low consumption times (e.g., non-ocupancy during holidays)

features_all_subsets

Creates a set of all combinations of features

remove_empty_features

Removes variables with no necessary information from a data.frame

Synthetic minority oversampling (SMOTE)