Post on 24-May-2020
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A SNAPSHOT OF NILMBALTIMORE, MDAUGUST 10, 2017JUSTIN ELSZASZ
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Is it ready yet?
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Let’s give it a try.
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We use fresh ingredients.
45 houses w. optical sensors /~ 30 second resolution
23 houses submetered / ~ 60 second resolution
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Training Data
Machine Learning
NILM Algorithm
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Training Data
Machine Learning
NILM Algorithm
?
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While we’re at it, let’s try a few recipes.
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“Secret Recipe”Partnered with NILM software
company to evaluate their algorithm.
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“As Seen on Pinterest®”Open-source algorithm
“SparseNILM” developed by Steven Makonin.
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“Grandma’s Homemade”Implemented an established
econometrics model.
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Central AC Hourly Averages (Sites)
0.0
2.0
Aver
age
kWh
0 2312 0 2312
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𝐶𝐶𝐶𝐶𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑 =𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑�𝑦𝑦𝑙𝑙𝑙𝑙𝑑𝑑𝑑𝑑𝑙𝑙𝑑𝑑
=
∑𝑑𝑑=1𝑛𝑛 𝑦𝑦𝑑𝑑 − �𝑦𝑦𝑑𝑑 2
𝑛𝑛 − 1�𝑦𝑦𝑙𝑙𝑙𝑙𝑑𝑑𝑑𝑑𝑙𝑙𝑑𝑑
𝐶𝐶𝐶𝐶𝑚𝑚𝑙𝑙𝑑𝑑𝑛𝑛 =𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑅𝑚𝑚𝑙𝑙𝑑𝑑𝑛𝑛
�𝑦𝑦𝑙𝑙𝑙𝑙𝑑𝑑𝑑𝑑𝑙𝑙𝑑𝑑=
∑𝑑𝑑=1𝑛𝑛 𝑦𝑦𝑑𝑑 −�𝑦𝑦𝑙𝑙𝑙𝑙𝑑𝑑𝑑𝑑𝑙𝑙𝑑𝑑2
𝑛𝑛 − 1�𝑦𝑦𝑙𝑙𝑙𝑙𝑑𝑑𝑑𝑑𝑙𝑙𝑑𝑑
𝐶𝐶𝐶𝐶 =𝜎𝜎𝜇𝜇
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1. Morning (6AM-10AM)
2. Midday (10AM-2PM)
3. Afternoon (2PM-6PM)
4. Evening (6PM-10PM)
5. Night (10PM-6AM)
CV Comparison for Central AC (Weekend)
0.0
1.0
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1. You need some “ILM” data.
2. Software providers may or may not help you cook.
3. “New” houses are still a challenge.
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JUSTIN ELSZASZjustin.elszasz@navigant.com202.481.8667linkedin.com/in/justinelszasz
THANK YOU