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001     893851
005     20240712112911.0
024 7 _ |a 10.21014/acta_imeko.v10i2.1054
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024 7 _ |a 2128/34043
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037 _ _ |a FZJ-2021-02875
041 _ _ |a English
082 _ _ |a 620
100 1 _ |a Barbara, Cannas
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245 _ _ |a NILM techniques applied to a real-time monitoring system of the electricity consumption
260 _ _ |a Braunschweig
|c 2021
336 7 _ |a article
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520 _ _ |a Non-Intrusive Load Monitoring (NILM) allows providing appliance-level electricity consumption information and decomposing the overall power consumption by using simple hardware (one sensor) with a suitable software. This paper presents a low-frequency NILM-based monitoring system suitable for a typical house. The proposed solution is a hybrid event-detection approach including an event-detection algorithm for devices with a finite number of states and an auxiliary algorithm for appliances characterized by complex patterns. The system was developed using data collected at households in Italy and tested also with data from BLUED, a widely used dataset of real-world power consumption data. Results show that the proposed approach works well in detecting and classifying what appliance is working and its consumption in complex household load dataset.
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700 1 _ |a Sara, Carcangiu
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700 1 _ |a Carta, Daniele
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|e Corresponding author
700 1 _ |a Alessandra, Fanni
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700 1 _ |a Carlo, Muscas
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700 1 _ |a Giuliana, Sias
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700 1 _ |a Beatrice, Canetto
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700 1 _ |a Luca, Fresi
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700 1 _ |a Paolo, Porcu
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773 _ _ |a 10.21014/acta_imeko.v10i2.1054
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856 4 _ |u https://juser.fz-juelich.de/record/893851/files/1054-7309-1-PB-1.pdf
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910 1 _ |a University of Cagliari
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910 1 _ |a University of Cagliari
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910 1 _ |a University of Cagliari
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910 1 _ |a University of Cagliari
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910 1 _ |a Bithiatech Technologies
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910 1 _ |a Bithiatech Technologies
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910 1 _ |a Bithiatech Technologies
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