Search Results - "Rumsch, Andreas"

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  1. 1

    Review on Deep Neural Networks Applied to Low-Frequency NILM by Huber, Patrick, Calatroni, Alberto, Rumsch, Andreas, Paice, Andrew

    Published in Energies (Basel) (01-05-2021)
    “…This paper reviews non-intrusive load monitoring (NILM) approaches that employ deep neural networks to disaggregate appliances from low frequency data, i.e.,…”
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    Journal Article
  2. 2

    Effect of Sampling Rate on Photovoltaic Self-Consumption in Load Shifting Simulations by Voinov, Philippe, Huber, Patrick, Calatroni, Alberto, Rumsch, Andreas, Paice, Andrew

    Published in Energies (Basel) (15-10-2020)
    “…Grid-connected photovoltaic (PV) capacity is increasing and is currently estimated to account for 3.0% of worldwide energy generation. One strategy to balance…”
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    Journal Article
  3. 3

    Residential Power Traces for Five Houses: The iHomeLab RAPT Dataset by Huber, Patrick, Ott, Melvin, Friedli, Martin, Rumsch, Andreas, Paice, Andrew

    Published in Data (Basel) (01-03-2020)
    “…Datasets with measurements of both solar electricity production and domestic electricity consumption separated into the major loads are interesting for…”
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    Journal Article
  4. 4

    Prediction of domestic appliances usage based on electrical consumption by Huber, Patrick, Gerber, Mario, Rumsch, Andreas, Paice, Andrew

    Published in Energy Informatics (10-10-2018)
    “…Forecasting or modeling the on-off times of domestic appliances has gained increasing attention in recent years. However, comparing currently published results…”
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    Journal Article
  5. 5

    The ‘SmartNIALMeter’ electrical appliance disaggregation dataset by Vogel, Manuel, Friedli, Martin, Camenzind, Martin, Kniesel, Guido, Klemenjak, Christoph, Gugolz, Gianni, Huber, Patrick, Calatroni, Alberto, Kaufmann, Lukas, Rumsch, Andreas, Paice, Andrew

    Published in Data in brief (01-10-2024)
    “…Electrical disaggregation, also known as non-intrusive load monitoring (NILM) or non-intrusive appliance load monitoring (NIALM), attempts to recognize the…”
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    Journal Article
  6. 6
  7. 7

    Poster abstract: Is the run-time of domestic appliances predictable? by Huber, Patrick, Schmieder, Paul, Gerber, Mario, Rumsch, Andreas

    Published in Computer science (Berlin, Germany) (01-02-2018)
    “…Run-time forecasting or modeling of domestic appliances has gained more attention in recent years. Comparing currently published works though is difficult due…”
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    Journal Article
  8. 8

    Improving the Recognition Performance of NIALM Algorithms through Technical Labeling by Mathis, Marcel, Rumsch, Andreas, Kistler, Rolf, Andrushevich, Aliaksei, Klapproth, Alexander

    “…A myriad of different electrical devices populate a typical household nowadays. Non-intrusive appliance load monitoring (NIALM) is an approach to find out how…”
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    Conference Proceeding
  9. 9

    Spatial services for decentralised smart green energy management by Ben Mahfoudh, Houssem, Di Marzo Serugendo, Giovanna, Abdennadher, Nabil, Rumsch, Andreas, Upegui, Andres

    “…In neighbourhoods, the number of energy generators are growing. A main reason for this being the rise in people's energy needs and the possibility of local…”
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    Conference Proceeding