A Real-World Energy Management data set from a Smart Company Building for Optimization and Machine Learning

This repository contains the Python code used for validating the real world energy management smart company data set, published under https://doi.org/10.5061/dryad.73n5tb363.

To run the code, we recommend using Python 3.10 and installing the requirements via pip

pip install -r requirements.txt

Furthermore, config.yaml should be configured to contain the respective paths to the data set.

The file issue_template.yml outlines the format of issue files as found in the dataset.

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The src directory contains the following scripts used to create the figures and statistics for the publication accompanying the data set:

• create_reduced_dataset.py: Script for creating the reduced aggregated data set from the full data set.
• downsample_measurements.py: Script for downsampling equidistantly sampled 1min time series to 15min and 1h resolution.
• error_statistics_p_vs_w.py: Script for comparing P measurements vs. W measurements, yielding plots and statistics.
• energy_flow_sankey.py: Script for generating the Sankey diagram illustrating overall electrical energy flows.
• issues_statistics.py: Script for creating statistics table on the automatically detected and manually specified issues of the data set.
• representative_time_series_full.py: Script for creating the time series plot showcasing the most important measurements over the full dataset measurement period.
• representative_time_series_full.py: Script for creasting the time showcasing a representative week from the dataset.
• yearly_energy_statistics.py: Script for creating the figure and tables for yearly energy consumption and production statistics.
• ReadFiles.py: Helper script used for creating reduced data set and the Sankey diagram. Contains a set of useful functions to load meters and elements of the data set effectively.

The meters.yaml in the root directory contains a list of all meters' uniform resource names (URNs) present in the dataset, grouped into categories. This file is used by ReadFiles.py to associate categories with the respective list of URNs for easier data handling. style.mplstyle contains the pyplot style used for creating figures.