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Generating two-parameter models with EEmeter
Phil Ngo
Hi Ethan!
I'll point you to the code here - unfortunately this is baked in. It wouldn't be too tricky to add, though- happy to review a pull request.
This line shows the candidate model selection - you'd need to make sure the candidates included your two-parameter models:
https://github.com/openeemeter/eemeter/blob/2f99fdada349f2f5090089e534d8137ee6a82431/eemeter/caltrack/usage_per_day.py#L1844
This line shows how you might add a two-parameter model candidate - you'd have to tweak this formula and add another function to generate the model candidate:I'll point you to the code here - unfortunately this is baked in. It wouldn't be too tricky to add, though- happy to review a pull request.
This line shows the candidate model selection - you'd need to make sure the candidates included your two-parameter models:
https://github.com/openeemeter/eemeter/blob/2f99fdada349f2f5090089e534d8137ee6a82431/eemeter/caltrack/usage_per_day.py#L1844
https://github.com/openeemeter/eemeter/blob/2f99fdada349f2f5090089e534d8137ee6a82431/eemeter/caltrack/usage_per_day.py#L1460
On Tue, Jul 5, 2022 at 2:11 PM Ethan Goldman <ethan.goldman@...> wrote:
Here's a question (or perhaps a feature request) for others who might be using EEmeter for gas meter modeling: there is a flag to force EEmeter to ignore cooling energy (fit_hdd_only), but can you force it to generate a "two-parameter" model with just slope and intercept?
Here I mean a more traditional X-intercept, not a base load. For background, I'm modeling run-time data from a gas furnace (metering the gas solenoid valve), so I'm quite sure there is no non-heating "base" load represented in my data! (I'm using eemeter v.3.1.0, FWIW)
Currently, EEmeter is giving me a model that adds about 20% more energy in the annual base load to a typical heating season for this area. It's also likely picking the wrong balance point, might be skewing the slope a bit, and (most importantly) doesn't actually produce a model that matches the physical reality of the data.
I realize this is a bit of an edge case since I'm technically modeling sub-meter data, but it's pure HVAC and definitely weather-dependent, so it seemed like a reasonably good fit for EEmeter. Does anyone have an easy fix, or would I need to add some new functionality to the code to get this behavior to work?
Thanks,
Ethan
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Here's a question (or perhaps a feature request) for others who might be using EEmeter for gas meter modeling: there is a flag to force EEmeter to ignore cooling energy (fit_hdd_only), but can you force it to generate a "two-parameter" model with just slope and intercept?
Here I mean a more traditional X-intercept, not a base load. For background, I'm modeling run-time data from a gas furnace (metering the gas solenoid valve), so I'm quite sure there is no non-heating "base" load represented in my data! (I'm using eemeter v.3.1.0, FWIW)
Currently, EEmeter is giving me a model that adds about 20% more energy in the annual base load to a typical heating season for this area. It's also likely picking the wrong balance point, might be skewing the slope a bit, and (most importantly) doesn't actually produce a model that matches the physical reality of the data.
I realize this is a bit of an edge case since I'm technically modeling sub-meter data, but it's pure HVAC and definitely weather-dependent, so it seemed like a reasonably good fit for EEmeter. Does anyone have an easy fix, or would I need to add some new functionality to the code to get this behavior to work?
Thanks,
Ethan
Here I mean a more traditional X-intercept, not a base load. For background, I'm modeling run-time data from a gas furnace (metering the gas solenoid valve), so I'm quite sure there is no non-heating "base" load represented in my data! (I'm using eemeter v.3.1.0, FWIW)
Currently, EEmeter is giving me a model that adds about 20% more energy in the annual base load to a typical heating season for this area. It's also likely picking the wrong balance point, might be skewing the slope a bit, and (most importantly) doesn't actually produce a model that matches the physical reality of the data.
I realize this is a bit of an edge case since I'm technically modeling sub-meter data, but it's pure HVAC and definitely weather-dependent, so it seemed like a reasonably good fit for EEmeter. Does anyone have an easy fix, or would I need to add some new functionality to the code to get this behavior to work?
Thanks,
Ethan