Looking for Residential Energy Usage Data Tracking Alternatives

I'm trying to find a cost-effective solution to track reductions in energy use for residential energy efficiency improvements (the information to be tracked includes property information, historical energy usage, monthly energy usage after improvement, weather-normalized data and carbon offsets).  I have heard that Longjump provided a great tracking tool, but it is now part of a larger solution (AgileApps) that might be more than I need for tracking the energy data.  I've also looked at the EnergyCAP solution.  Are there others I should be considering?

Thank you!

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You can try WegoWise.  If you're just tracking one house it's free.  Added bonus--for many utility companies it can pull in data directly from the homeowner's online utility accounts, both historical data and the monthly data moving forward.  Full disclosure--I work for them.  

Thanks Sean!  Does WegoWise work with Duke Energy yet?  Can you track more than one house?

Yes, we can automatically import from Duke Energy!  We can definitely track more than one house at our Pro level of service, which isn't free but is pretty reasonable at $12/house/year.  I don't want to turn your thread into a sales pitch, so I'll message you with more info. 

Hello Jennifer,

You may be looking for a more automated approach, but here is what I use for identifying energy effieincy improvements that have been made to homes. 

I work for the energy efficiency department of our electric utility and we use a simple spreadsheet to plot the average monthly energy consumed versus the average monthly temperature for each month.  This normalizes the home's energy consumption for weather variations and the number of billing days. The energy used in a typical home will typically line up quite nicely when plotted in this fashion, and any variation can be easily identified. 

Below are two plots of the average energy use versus average monthly temperature.  Average daily temperatures for your specific site can be found at http://www.weatherdatadepot.com/.  I plot electrical usage in terms of average Watts per square foot, and natural gas usage in terms of average BTU per hour.

 

The average temperature plot below was used to see if there were any improvements from installing a high efficiency gas furnace.  This data showed that there does not appear to be any significant reduction in gas usage.

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Thanks James!  We are tracking a few houses in Excel right now and I am looking for a more automated approach for the long term, but I really like your graphs. I may have to see if I can get my Excel data to do that.  Thank you!!

I see these b"blame it on behavior" fallacies all the time. Usually from people who have little home performance or energy efficiency.

Bottom line is dead on. Anyone else find hypocracy of the earlier completely unmeasured 'conclusions' shocking?

+1

It's a little tough to argue with the utility meter (after weather normalizing). 

Hello all,

Back on February 14, Bob Blanchette provoked 7 pages of commentary when he asked for assistance from the collective wisdom of Homeenergypros in an effort to solve the mystery of why he is unable to find a way to quantify savings, following installation of a condensing furnace in his home. Search HDD and you will find Bob's question.

Bob had quite comprehensive records, but seemingly no manipulation of his data allowed him to prove he made a wise choice by replacing the old furnace. Most of his calculations, as well as efforts by many contributors, seemed to indicate he should have saved his money (Someone please correct me if I did not read all 7 pages carefully enough). Frankly, and from a purely subjective perspective, I have a lot of trouble with the conclusion that the new furnace was a mistake.

In an effort to bring additional insight to that discussion, I contacted folks I know in Canada (where, I understand it gets really cold). Here's a reply I received when I shared Bob's conundrum with a gentleman I contacted at the Canadian Centre for Housing Technology. While the response below concentrates on the effect of HDD on heating energy use, I believe Mr. Swinton's observations have implications for other efforts to quantify energy savings, and are appropriate to this discussion. My take away is, we have much to learn...

____________

Hi Steve,

A long time ago, I worked as a housing engineering energy consultant and found out enough about Heating Degree-Days (HDD) to know they are very tricky to use, especially on a monthly basis.

There are so many other factors that affect house consumption in addition to the ones roughly captured by HDD, that you can’t trust that index for a detailed monthly analysis of heat consumption. Some of these other factors include solar gains, internal electrical gains from activity, heat gain from people, wind (though not wind-chill as some of your discussion indicates), and thermal mass as per your discussions with Marianne below. For example, HDD simply truncates data involving temperatures that are hotter than its baseline (for example 65F), so that it will over-predict heating loads on days with warmer daytime temperatures and cold nights. The mass effect carries the house through these periods in reality. The furnace can be shut-off by the owner because they know the heating season is over, but the HDD keeps adding up.

With the large amount of data we collect for our houses, we have never looked at correlations of our house consumption with degrees days. Rather, Marianne has investigated the relationships of the impacts of temperature, solar and wind on the heat loss of the CCHT houses. She also studied the impact of ground temperature on heat loss in the basement, which affects the energy balance of the house. Even with all of this, her correlations always showed scatter, indicating that we don’t yet have the whole story on how weather and surroundings affect heat loss. That is why we went to the trouble of building an identical Reference House to the Test House – the Reference House is like a very expensive weather sensor that integrates all these factors which we use to predict what goes on in the Test house for a given set of technologies and configuration. Even there, we have to benchmark the Reference house ‘weather sensor’ as it changes from season to season.

So the challenge you have taken on is a big one – we have no easy fixes to use HDD as a predictor or adjustment to your consumption data. Others in the business of analyzing customer consumption data in more detail, for example oil and gas utilities or consultants may have had more success.

Best regards,
Mike Swinton
Principal Research Officer
Research Manager
Canadian Centre for Housing Technology

A final note: Response to Bob's post ceased following the reply from the Great White North. I may only speculate...

Best wishes.

It's pretty old school, but I've used this: http://www.marean.mycpanel.princeton.edu/~marean/default.html in the past for looking at energy impacts for several hundred homes at a time.  It's a bit labor intensive, but less expensive if you plan on looking at many homes (100+).

Thanks Dan, I'll look into it!

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