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Residential Power Traces for Five Houses: The iHomeLab RAPT Dataset

Author

Listed:
  • Patrick Huber

    (Engineering and Architecture, Lucerne University of Sciences and Arts, Technikumstrasse 21, 6048 Horw, Switzerland
    These authors contributed equally to this work.)

  • Melvin Ott

    (Engineering and Architecture, Lucerne University of Sciences and Arts, Technikumstrasse 21, 6048 Horw, Switzerland
    These authors contributed equally to this work.)

  • Martin Friedli

    (Engineering and Architecture, Lucerne University of Sciences and Arts, Technikumstrasse 21, 6048 Horw, Switzerland)

  • Andreas Rumsch

    (Engineering and Architecture, Lucerne University of Sciences and Arts, Technikumstrasse 21, 6048 Horw, Switzerland)

  • Andrew Paice

    (Engineering and Architecture, Lucerne University of Sciences and Arts, Technikumstrasse 21, 6048 Horw, Switzerland)

Abstract

Datasets with measurements of both solar electricity production and domestic electricity consumption separated into the major loads are interesting for research focussing on (i) local optimization of solar energy consumption and (ii) non-intrusive load monitoring. To this end, we publish the iHomeLab RAPT dataset consisting of electrical power traces from five houses in the greater Lucerne region in Switzerland spanning a period from 1.5 up to 3.5 years with a sampling frequency of five minutes. For each house, the electrical energy consumption of the aggregated household and specific appliances such as dishwasher, washing machine, tumble dryer, hot water boiler, or heating pump were metered. Additionally, the data includes electric production data from PV panels for all five houses, and battery power flow measurement data from two houses. Thermal metadata is also provided for the three houses with a heating pump.

Suggested Citation

  • Patrick Huber & Melvin Ott & Martin Friedli & Andreas Rumsch & Andrew Paice, 2020. "Residential Power Traces for Five Houses: The iHomeLab RAPT Dataset," Data, MDPI, vol. 5(1), pages 1-14, February.
    • Handle: RePEc:gam:jdataj:v:5:y:2020:i:1:p:17-:d:316622
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    References listed on IDEAS

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    1. Luthander, Rasmus & Widén, Joakim & Nilsson, Daniel & Palm, Jenny, 2015. "Photovoltaic self-consumption in buildings: A review," Applied Energy, Elsevier, vol. 142(C), pages 80-94.
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    Cited by:

    1. Santiago Bustamante-Mesa & Jorge W. Gonzalez-Sanchez & Sergio D. Saldarriaga-Zuluaga & Jesús M. López-Lezama & Nicolás Muñoz-Galeano, 2024. "Data for Optimal Estimation of Under-Frequency Load Shedding Scheme Parameters by Considering Virtual Inertia Injection," Data, MDPI, vol. 9(6), pages 1-8, June.
    2. Lei Yao & Jinhao Wang & Chen Zhao, 2024. "Non-Intrusive Load Monitoring Based on Multiscale Attention Mechanisms," Energies, MDPI, vol. 17(8), pages 1-23, April.
    3. Margherita Povolato & Alessandro Prada & Sara Verones & Paolo Baggio, 2022. "On the Effect of the Time Interval Base and Home Appliance on the Renewable Quota of a Building in an Alpine Location," Energies, MDPI, vol. 16(1), pages 1-13, December.

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