Poster abstract: Is the run-time of domestic appliances predictable?

Patrick Huber1, Paul Schmieder1, Mario Gerber1, Andreas Rumsch1
1Lucerne University of Applied Sciences and Arts, iHomeLab, Horw, Switzerland

Tóm tắt

Từ khóa


Tài liệu tham khảo

Amouroux E, Huraux T, Semp F, Sabouret N, Haradji Y (2013) Simulating human activities to investigate household energy consumption. In: ICAART(2), pp 71–80

Barbato A, Capone A, Rodolfi M, Tagliaferri D (2011) Forecasting the usage of household appliances through power meter sensors for demand management in the smart grid. In: IEEE international conference on smart grid communications (SmartGridComm), pp 404–409

Chrysopoulos A, Diou C, Symeonidis AL, Mitkas PA (2014) Bottom-up modeling of small-scale energy consumers for effective demand response applications. Eng Appl Artif Intell 35:299–315

Fischer D, Hrtl A, Wille-Haussmann B (2015) Model for electric load profiles with high time resolution for German households. Energy Build 92:170–179

Holub O, Sikora M (2013) End user models for residential demand response. In: 2013 4th IEEE/PES Innovative Smart Grid Technologies Europe (ISGT EUROPE), pp 1–4

Hosseini S, Agbossou K, Kelouwani S, Cardenas A (2017) Non-intrusive load monitoring through home energy management systems: a comprehensive review. Renew Sustain Energy Rev 79:1266–1274

Hosseini S, Kelouwani S, Agbossou K, Cardenas A, Henao N (2017) A semi-synthetic dataset development tool for household energy consumption analysis. In: IEEE International Conference on Industrial Technology (ICIT), pp 564–569

Pflugradt ND (2016) Modellierung von Wasser und Energieverbraeuchen in Haushalten, Dissertation, TU Chemnitz

Truong NC, McInerney J, Tran-Thanh L, Costanza E, Ramchurn S (2013) Forecasting multi-appliance usage for smart home energy management. In: 23rd International Joint Conference on Artificial Intelligence (IJCAI 2013), China