Existing electricity monitoring solutions often do not provide fine-grained information for the users (e.g., in the case of smart meters) or are too expensive for large-scale deployment (e.g., in the case of smart power plugs and CT-based electric sub-metering systems). Many of them (e.g., smart meters and CT-based electric sub-metering systems) also require professional electricians to install. There is a lack of user-friendly and low-cost system solutions that can help users understand their electricity usage with sufficient accuracy.
Challenges
The central challenge is to achieve high estimation accuracy for fine-grained electricity usage information with low-cost sensing devices while incurring minimum installation / maintainance efforts from the end users. We also need to devise different solutions to suit the needs of different end users. |
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Our approaches
We have invented multiple complementary solutions to provide end users with fine-grained electricity usage information in low-cost and easy-to-install ways (see the table below).
| Approach |
Goal |
Device(s) needed |
Installation |
| Supero |
Estimate the states for home appliances with distinguishable physical signals, like light and sound. |
Multiple indirect sensors and an in-situ smart meter |
Distribute the sensors across the space to be monitored |
| Harmonic-Sense |
Estimate the states for home appliances with distinguishable harmonic patterns in current waveform |
A single battery-powered mote hosting a current transducer and an in-situ smart meter |
Install the sensor mote onto the main feeder of the home / office |
| Noninvasive Sub-metering |
Estimate the current readings of each branch in an electricity distribution panel |
An Anisotropic Magnetoresistive (AMR) sensor array and an in-situ smart meter |
Install the AMR sensor array on the electricity distribution panel |
Our results
While our solution relies on low-cost sensors and allows quick deployment by non-professional users, we can still achieve high estimation accuracy. In particular, when tested extensively in real home environments, both Supero and Harmonic-Sense can estimate the energy consumption of individual appliances with less than 10% of error rate. Our noninvasive sub-metering solution based on AMR sensor arrays can estimate the per-branch current readings with less than 10% of error rate, even for branches carrying small loads (e.g., a 30W fan). See more details in the following two demo videos:
Load Disaggregation Demonstration
presented at BuildSys 2012 |
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AMR Electric Submetering Demo
presented at SenSys 2012 |
Publications
- Dennis E. Phillips, Rui Tan, Mohammad-Mahdi Moazzami, Guoliang Xing, Jinzhu Chen, David K. Y. Yau
Supero: A Sensor System for Unsupervised Residential Power Usage Monitoring
IEEE International Conference on Pervasive Computing and Communications (PerCom’13)
Best paper candidate
San Diego, CA, USA, March 2013
- Deokwoo Jung, Hoang Hai Nguyen, Sreejaya Viswanathan, Binbin Chen and David K.Y. Yau
Demo: Scalable Load Disaggregation System Using Distributed Electrical Signature Detection
In Proceedings of the 4th ACM Workshop On Embedded Systems For Energy-Efficiency In Buildings (BuildSys’12)
Toronto, Canada, November 2012 [pdf]
- Sreejaya Viswanathan, Binbin Chen, Hoang Hai Nguyen, Jerry T. Chiang, Deokwoo Jung, and David K. Y. Yau
Demo: Using Anisotropic Magnetoresistive (AMR) Sensor Arrays for Electric Sub-metering
In Proceedings of the 10th ACM Conference on Embedded Networked Sensor Systems (SenSys’12)
Toronto, Canada, November 2012 [pdf]
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