Thanks to everyone who joined for this month's OpenEEmeter working group. We're excited at the huge progress we're making on CalTRACK 2.1, and greatly appreciate all who have taken time out of their schedule to participate in this important discussion.

Tim Guiterman from Sealed led off yesterday's discussion with a follow-up conversation on revising CalTRACK's requirements to permit its usage with delivered fuels such as propane and heating oil. Because these fuels are delivered and manually refilled, data for them are not as consistent nor as abundant as metered energy is. Tim and the Sealed team proposed making an exception to the 70 day data limit for delivered fuels.

The group discussed what the minimum number of data points should be and various factors that could alter this. There was also discussion of relaxing the 365 day baseline period to allow for more data when fitting this period. Most delivered fuel customers can provide data in the form of bills that cover years of time. Adam pointed out that while there might not be a perfect answer to the delivered fuel problem, using the CalTRACK approach is still much better than deemed approaches which are much less accurate.

The conversation concluded with Tim agreeing to analyze Sealed data so that the working group can make a data-driven decision on if rule changes should be made for delivered fuel customers and if so what should the minimum requirements be, with proof that backs up these revisions.

Adam and Travis then summarized CalTRACK 2.0's deficiencies and how the nearly final model of CalTRACK 2.1 rectifies them. The main problem the team was attempting to solve was seasonal bias in the CalTRACK 2.0 model found primarily in gas meters. They showed that CalTRACK 2.1 has significantly reduced seasonal bias. At the same time it has been necessary to revisit how fast the model can be fit in. Travis has implemented several clever means of speeding up the model from worst-case scenarios of 1 minute to fit down to 10 seconds. He also went into detail about how CalTRACK 2.1 differs from CalTRACK 2.0 in order to solve the issues laid out prior. Additionally, Travis briefly mentions that they have implemented a CalTRACK 2.0 mode, a legacy mode, which can replicate CalTRACK 2.0 results with all of the speed improvements developed recently.

Overall, they show that CalTRACK 2.1 reduces seasonal bias by 74% and is between 2 and 100 times faster than CalTRACK 2.0, depending on how it's used (legacy mode or not).

Adam and Travis anticipate that by the next meeting, the final CalTRACK 2.1 model will have completed its R&D phase. Next steps involve code cleanup, polishing, and documentation so that CalTRACK 2.1 can be integrated into the OpenEEmeter.
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Next Meeting Scheduled: Tuesday, June 6th, 1pm PT.

Watch the full presentation below.

Thanks to everyone who joined the most recent OpenEEmeter working group meeting. 

Tim Guiterman from Sealed led off the conversation with a discussion of the need to address delivered fuels such as propane or heating oil in the CalTRACK specifications. CalTRACK's current data sufficiency requirements often limit the ability to model homes that using delivered fuels, which are common in the Northeast. Because these fuels are not necessarily delivered on a consistent cadence, CalTRACK's monthly data requirements are barrier to using it for these kinds of customers. Making CalTRACK more accessible and avoiding unnecessary disqualifications is particularly important given the new funding from the IRA and the opportunities it presents for adopting a measured pathway for incentives. 

Adam Sheer and Travis Sikes then shared updates and results related to the CalTRACK Daily 2.1 model, which is nearing completion. Adam reviewed the issues CalTRACK 2.1 process is attempting to address around model bias, and the tradeoffs between adding parameters to correct bias and the need to avoid overfitting. Preliminary results on the new 2.1 model showed a dramatic improvement, reducing summer, winter and weekend bias. 

Getting these kinds of improvements requires additional computations. CalTRACK 2.0 performance prohibits any additional complexity due to the time it takes to fit a model (20 - 60 seconds). This is particularly prohibitive to the cross-validation that is the lynchpin of our current improvement efforts.

To address this, Travis gave an extended presentation of how he has dramatically improved the computational efficiency of the OpenEEmeter, reducing the per-meter fitting time from 20 to 60 seconds to approximately 0.5 seconds (20-120 times faster) for an equivalent fit. For those that need or want to run the original CalTRACK 2.0, a CalTRACK 2.0 legacy mode will be included that has all of these computational efficiency improvements. 

The team discussed the remaining steps needed to finalize the model formulation and are hopeful that it will be wrapped up in the next one to two months. We are excited about the progress made so far and the potential impact of the updated model.

Watch the full meeting below.
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Next Meeting Scheduled: Tuesday, May 2nd, 1pm PT

Thanks to everyone who joined us for yesterday's OpenEEMeter technical working group meeting.

Adam Scheer led off the meeting by reiterating the high-level goals for the CalTRACK 2.1 Daily model which are to improve specific and known areas of model bias and gain computational efficiency in the process. He explained the need to solve seasonal and weekend/weekday bias by adding parameters and optimization steps without creating an overfitting problem or making the model so complex that it can't be scaled to hundreds of thousands or millions of meters.

For the CalTRACK Hourly model, Adam laid out issues to discuss in future meetings, including remedying known small bugs, specifying demand response baselines, and incorporating solar PV modeling.

Adam then introduced James Fenna from Carbon Co-op to discuss some challenges and modifications needed to implement CalTRACK (specifically eeweather) in the U.K. and internationally. In particular, James discussed the problems of calibrating for metric temperatures and the need for different sources of weather data internationally.

Adam then led a more detailed discussion of the specific tradeoffs of adding parameters to address seasonal bias in the model.

The group discussed how seasonal bias is a problem that has been known for decades, and how much effort should be put into improving the Daily model versus Hourly.

Watch the full meeting below.

Next Meeting Scheduled: Tuesday, April 4th, 10am ET, 1pm PT

Join the working group to get access by clicking this link:

Download the presentation slides below

Thanks to all who attended the most recent CalTRACK working group meeting.

McGee Young opened this meeting with some words for Shuli Goodman of LFEnergy Foundation who recently passed away. McGee made the point that Shuli was instrumental in helping to give the OpenEEmeter credibility and a home. Shuli had a vision that open source/open standards could do for energy what it's done for other industries, like the Internet. Under her leadership LFEnergy has grown as an umbrella to many innovative projects. She will be missed.

The technical discussion explained the current goal of examining sources of bias or error in CalTRACK 2.0 and potential solutions. The group discussed the need to balance adding additional parameters against the risk of overfitting.

Watch the full meeting below.

Next Meeting Scheduled: Tuesday, March 7th, 10am ET, 1pm PT

Join the working group to get access by clicking this link:

Meeting topics will include

Join the working group to get access by clicking this link: 

Watch the 01/17/2023 technical working group meeting on demand or below. If you haven't signed up yet, click here to register for the next meeting. 

Watch the 12/06/2022 technical working group meeting on demand or below. If you haven't signed up yet, click here to register for the next meeting. 

Thank you to everyone who was able to make it to our CalTRACK 2.1 | OpenEEmeter kick off on 11/22. If you were unable to attend check out the recording available on demand or below. We look forward to continuing this work at next week's meeting on Tuesday, 12/6/2022.

Phil Ngo, Director of Engineering at Recurve, provides insights into the OpenEEmeter and EEweather, which is an open source implementation of the CalTRACK Methods that resides in LF Energy.