Abstract
This paper presents the formulation and practical implementation of a spectral decomposition based, Real-Time Non-Intrusive Load Monitoring (RT-NILM) solution. Many of the NILM techniques reported in the literature have been validated on environments with non-varying supply voltages, while relying on multiple measurements taken at high sampling rates. In contrast, the RT-NILM solution proposed in this paper has addressed the issue of supply voltage variability, which is a common practical problem prevalent in many developing countries and is anticipated to emerge globally with the increased penetration of renewable energy sources. Therefore, the proposed RT-NILM algorithm was implemented to maintain high accuracy levels even under severe supply voltage fluctuations. An iterative implementation of the Karhunen-Loève expansion was introduced to improve the spectrum decomposition resolution. Further, a fast deconvolution based technique was introduced for the disaggregation of individual power levels of active appliances in an computationally efficient manner. The proposed solution has been validated on a real voltage varying environment, at a real house, in real-time, using active power and voltage measurements taken at a low sampling rate of 1 Hz.
| Original language | English |
|---|---|
| Pages (from-to) | 1519-1529 |
| Number of pages | 11 |
| Journal | Applied Energy |
| Volume | 238 |
| DOIs | |
| State | Published - 15 Mar 2019 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 7 Affordable and Clean Energy
Keywords
- Demand side management
- Non-intrusive load monitoring
- Real-time load monitoring
- Smart grid
- Subspace techniques
- Supply voltage variation
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