True Analytics™ - Energy Savings, Comfort, and Operational Efficiency
Simple and Elegant Building Energy Modeling for All
A building owner changes the building’s thermostat setting, allowing
the indoor temperature to increase a couple of degrees for an entire
afternoon. But how much energy was actually saved? To know the answer
for sure, the energy actually used must be compared to the energy that
would have been used if they hadn’t made the change…but how does the
building owner find that out?
The answer is provided by a “baseline energy model,” a statistical
formula that, based on the analysis of previous energy use, takes into
account the time of day, the day of the week, and the outdoor air
temperature to predict the building’s energy consumption as a function
of time if the building were operated normally.
When Environmental Energy Technologies Division (EETD) researcher
Phillip Price began working with building energy data a few years ago,
he discovered that the standard baseline energy models are very simple.
“And that makes sense,” says Price, “because usually the only useful
explanatory variable you have is outdoor air temperature. If your only
variables are time and temperature, you may not get much benefit from a
But he also discovered that the standard approaches have some flaws, so
he made improvements. He developed a model that produces more accurate
predictions in most buildings, but isn’t much more complicated than
previous models. He and graduate student Johanna Mathieu published the
model in 2011.
Price has worked with statistical models for 20 years at Berkeley Lab.
In the early 1990s he became one of the foremost authorities on the
spatial and statistical distribution of indoor radon, and co-developed
state-of-the-art algorithms for mapping airborne pollutant
concentrations using optical remote sensing data.
He turned his hand to statistically modeling electric load data several years ago. While researching for his model development, Price noted changes happening in the industry, which dramatically increased the amount of energy use data available.
“Until not too long ago, the only energy use data people had were monthly use data,” Price said. “Now that we have ‘smart meters,’ we’ve started getting more data and that has opened up many possibilities. The idea was to look at what people were doing and see if we could do better—and that effort led to this model.”
Read the rest: http://eetd.lbl.gov/news/article/57523/simple-and-elegant-building-ene
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