Algorithm reveals the electricity consumption of individual appliances
- Date:
- January 26, 2015
- Source:
- Alpen-Adria-Universität Klagenfurt | Graz | Wien
- Summary:
- Opportunities to save energy become apparent once you can determine energy consumption of single appliances without extra measurement effort. A newly developed algorithm provides assistance on the path to greater energy awareness.
- Share:
Opportunities to save energy become apparent once you can determine energy consumption of single appliances without extra measurement effort. A newly developed algorithm provides assistance on the path to greater energy awareness.
"Using the measured performance data from the power supply of a household, the algorithm serves to illustrate the use of individual appliances," according to Wilfried Elmenreich, who is developing the technology at the Institute for Networked and Embedded Systems in collaboration with Dominik Egarter. This saves costs: Firstly, because it is not necessary to use any additional measuring equipment to determine the frequency of appliance use, and secondly, because knowledge of the consumption increases the user's energy awareness. This technology represents an integral part of the concept of the so-called "smart grid," an intelligent electricity network.
Mathematical methods provide the background to this development: The algorithm presented is derived from a model based on Markow chains and a sequential Monte-Carlo method (particle filtering) for the state estimation of the appliances. The researchers were able to illustrate that the algorithm works at an accuracy level of 90 per cent in typical households.
This research was funded by the European Regional Development Fund and the Carinthian Economic Promotion Fund (KWF) as part of the Lakeside Labs Project Smart Microgrid.
Story Source:
Materials provided by Alpen-Adria-Universität Klagenfurt | Graz | Wien. Note: Content may be edited for style and length.
Journal Reference:
- Dominik Egarter, Venkata Pathuri Bhuvana, Wilfried Elmenreich. PALDi: Online Load Disaggregation via Particle Filtering. IEEE Transactions on Instrumentation and Measurement, 2015; 64 (2): 467 DOI: 10.1109/TIM.2014.2344373
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