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http://dx.doi.org/10.7471/ikeee.2020.24.2.632

Data Processing and Analysis of Non-Intrusive Electrical Appliances Load Monitoring in Smart Farm  

Kim, Hong-Su (Soombi Co., Ltd.)
Kim, Ho-Chan (Dept. of Electrical Engineering, Jeju National University)
Kang, Min-Jae (Dept. of Electronics Engineering, Jeju National University)
Jwa, Jeong-Woo (Dept. of Telecommunication Engineering, Jeju National University)
Publication Information
Journal of IKEEE / v.24, no.2, 2020 , pp. 632-637 More about this Journal
Abstract
The non-intrusive load monitoring (NILM) is an important way to cost-effective real-time monitoring the energy consumption and time of use for each appliance in a home or business using aggregated energy from a single recording meter. In this paper, we collect from the smart farm's power consumption data acquisition system to the server via an LTE modem, converted the total power consumption, and the power of individual electric devices into HDF5 format and performed NILM analysis. We perform NILM analysis using open source denoising autoencoder (DAE), long short-term memory (LSTM), gated recurrent unit (GRU), and sequence-to-point (seq2point) learning methods.
Keywords
NILM; Deep learning; power usage pattern; smart farm; data acquisition;
Citations & Related Records
Times Cited By KSCI : 2  (Citation Analysis)
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