Disaggregated Homes

My name is Oliver Parson, and I'm currently employed as a Product Data Science Lead at Octopus. I'm interested in investigating the ways in which machine learning can be used to break down household energy consumption data into individual appliances, also known as Non-intrusive Appliance Load Monitoring (NILM) or energy disaggregation.

Monday, 28 February 2011

Load Signature Study—Part I: Basic Concept, Structure, and Methodology

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Liang J, Ng S, Kendall G, Cheng J. Load Signature Study - Part I: Basic Concept, Structure, and Methodology. Power Delivery, IEEE Transactio...
Friday, 25 February 2011

Using smoothness to detect appliances

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This post follows up on a previous post describing how if we subtract an appliance's signature from the aggregate consumption, we end u...

IEEE Pervasive Computing 10 (1): Special Issue on Smart Energy Systems - part 3

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Marchiori A, Hakkarinen D, Han Q, Earle L. Circuit-Level Load Monitoring for Household Energy Management. Pervasive Computing, IEEE . 2011;1...
Wednesday, 23 February 2011

IEEE Pervasive Computing 10 (1): Special Issue on Smart Energy Systems - part 2

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Froehlich J, Larson E, Gupta S, et al. Disaggregated End-Use Energy Sensing for the Smart Grid. Pervasive Computing, IEEE . 2011;10(1):28-39...

IEEE Pervasive Computing 10 (1): Special Issue on Smart Energy Systems

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I been reading more from the special issue on smart energy systems. Here are my thoughts: Paradiso J, Dutta P, Gellersen H, Schooler E. Gues...
Tuesday, 22 February 2011

Look Back before Leaping Forward: Four Decades of Domestic Energy Inquiry

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I recently read the following article on domestic energy monitoring in the IEEE Pervasive Computing magazine: Hazas M, Friday A, Scott J. Lo...

Microsoft Hohm

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I've just come across Microsoft's Hohm, an energy visualisation web app similar to Google's powermeter. It's only open to US...
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