Supervised non-intrusive load monitoring algorithm for identifying different operating states of type-II residential appliances
Author:
Affiliation:
1. University of Sri Jayewardenepura,Dept. of Electrical & Electronic Eng.,Dehiwala-Mount Lavinia,Sri Lanka
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/9906100/9906138/09906271.pdf?arnumber=9906271
Reference30 articles.
1. Non-intrusive load monitoring and its challenges in a NILM system framework
2. A Scalable Real-Time Non-Intrusive Load Monitoring System for the Estimation of Household Appliance Power Consumption
3. Non-Intrusive Load Monitoring Approaches for Disaggregated Energy Sensing: A Survey
4. Residential Appliance Identification Based on Spectral Information of Low Frequency Smart Meter Measurements
5. Load signatures enhancement via odd-order harmonic currents
Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. Real-Time Non-Intrusive Load Monitoring System for Residential Appliance Identification;2024 4th International Conference on Advanced Research in Computing (ICARC);2024-02-21
2. A Review of NILM Applications with Machine Learning Approaches;Computers, Materials & Continua;2024
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