This morning I learnt that my full co-authored (with co-author William Sung, Ryan Dela Cruz, Brett Yarrow, Bob Gill, Fred Popowich, and Ivan Bajic) paper “Inspiring Energy Conservation Through Open Source Metering Hardware and Embedded Real-Time Load Disaggregation” was accepted at IEEE‘s PES Asia-Pacific Power and Energy Engineering Conference (IEEE PES APPEEC 2013). So I am headed off to Hong Kong at the beginning of December. Here is the paper abstract:
Utility companies around the world are replacing electro-mechanical power meters with new smart meters. These digital power meters have enhanced communication capabilities, but they are not actually smart. We present the cognitive power meter (c-meter), a meter that is actually smart. By using load disaggregation intelligence, c-meter is the realization of demand response and other smart grid energy conservation initiatives. Our c-meter is made of two key components: a prototype open source ammeter and an optimized embedded load disaggregation algorithm (uDisagg).
Additionally, we provide an open source multi-circuit ammeter array that can build probabilistic appliance (or load) consumption models that are used by the c-meter. uDisagg is the first load disaggregation algorithm to be implemented on an inexpensive low-power embedded processor that runs in real-time using a typical/basic smart meter measurement (current, in A). uDisagg can disaggregate loads with complex power states with a high degree of accuracy.
Keywords: embedded software, energy conservation, load modelling, open source hardware, real-time systems
This paper shows the results of our Cognitive Power Meter (c-meter) version 1. One thing to note, we have not released this to open source — we still need to do some code clean up.