Wednesday, November 22, 2017

Correlation Filters for Load Classification @ IEEE SmartGridComm

We are happy to announce that our paper "On the Applicability of Correlation Filters for Appliance Detection in Smart Meter Readings" was accepted and presented at this year's SmartGridComm conference in Dresden.

With our load classification approach based on correlation filters, we aim to provide a low-cost non-Intrusive Load Monitoring (NILM) method for measurement equipment with limited computational capabilities such as networked sensors or smart plugs. One of these small devices to run such an algorithm on would be our YoMo metering board.

Abstract:

"Communication systems utilise correlation filters to detect waveforms. In a broader sense, these filters examine the amount of resemblance between a template pattern and the input pattern. In the domain of smart grids, many applications require the detection of active electrical appliances, their condition as well as their current state of operation. Furthermore, the identification of power eaters, the recognition of ageing effects, and the forecast of required maintenance represent important challenges in (home) energy management systems.
In this paper, we examine the applicability of correlation filters as a possible solution to meet such challenges. First, we introduce the concept of predictability to power consumption patterns of electrical appliances. Second, we present our concept and the implementation of correlation filters for this kind of application. The correlation filters utilise a particular consumption pattern of an electrical appliance to detect the respective appliance in energy readings from smart meters and smart plugs.
Lastly, we assess the performance of the correlation filters on the real-world energy consumption dataset GREEND, which provides readings from smart meter data as well as appliance-level measurement equipment. As the results approve, the correlation filters show a good performance for appliances with predictable consumption patterns such as refrigerators, dishwashers, or washing machines. Thus, we propose that future work should evaluate the applicability of correlation filters in appliance diagnosis systems."


Christoph Klemenjak presenting at the load classification session


C. Klemenjak and W. Elmenreich. On the Applicability of Correlation Filters for Appliance Detection in Smart Meter Readings. In Proceedings of the 2017 IEEE International Conference on Smart Grid Communications (SmartGridComm), Dresden, Germany, October 2017.


The Correlation Filters were evaluated on real-world energy consumption data provided by the GREEND dataset, which is available at Sourceforge:

A. Monacchi, D. Egarter, W. Elmenreich, S. D'Alessandro, and A. M. Tonello. GREEND: An energy consumption dataset of households in italy and austria. In Proc. IEEE International Conference on Smart Grid Communications (SmartGridComm'14), Venice, Italy, 2014.




Friday, November 10, 2017

Should I drive with my car to turn off forgotten lights?

I forgot to turn off the lights in my office today. True story. And it's Friday, so unless the cleaning personel turns them off, the lights there will burn unnecessarily for 60 hours until Monday morning. This is a bit awkward when you are doing research[1] and teaching[2] in sustainability and energy management.
So the question is, should I go there immediately and turn them off? Normally I would use my bike, but it's dark and cold outside so I consider using the car.

Let's crunch the numbers first. My car consumes about 5,5l Diesel per 100 km, so using it for a single person trip is far from contributing to a sustainable future. But the trip will save the energy that would be consumed by the office lights. The trip there and back is 11km, so this would use 0.6 l of Diesel. 1 liter of diesel contains chemical energy worth 9.85 kWh, weighs 835 g, and contains 86% carbon. This 720 g carbon would be mostly burned to CO2, resulting in 2640 g of CO2 [3].

Burning 0,6 l Diesel would thus generate about 1,5 kg of CO2 and waste 5,9 kWh of energy.

What if I let the lights burn? Unfortunately the office lights are not LED-based, but they are fluorescent tubes. I would guess all together the lighting has a power consumption of 100 W. Letting them burn for 60 h would thus waste 6 kWh, basically the same value that we calculated for the used fuel.

About 3/4 of Austria's "Strom-Mix" come from hydropower, wind, waste and solar sources, the remaining part from fossil fuels like gas, oil and coal. I'm lucky that Austria has no nuclear power, first because it is a dangerous technology and second because the effective CO2 emissions of nuclear power are hard to estimate :-).

Coal is the worst source, it comes with 882 g CO2 per kWh[4]. All together Austria's electric energy comes with emissions of 181 g/kWh[5]. So the 6 kWh of electrical energy from the "let's the lights burn" scenario are a bit more than 1kg - less than the scenario where I drive with the car to turn the lights off.

So I should feel bad about the environment, but at least I have my lazyness supported. I might go there by bike tomorrow :-)