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Would appreciate folks' thoughts on how best to use modelling to estimate savings when little is known about the subject building.

Say one wanted to estimate the energy savings from upgrading a building's HVAC system. All you know about this building is its use type (e.g. office), HVAC type (e.g. PVAV w/ elec reheat), location, and monthly EUI by fuel.

Is it worth trying to calibrate a generic prototype model (of same use type and HVAC type) to the monthly energy use data or, (given all the uncertainties inherent to the whole analysis) is it better to just finding a percent savings using the uncalibrated prototype model and applying that percent savings (monthly by fuel type) to the metered data?

In other words:

Option 1.

1. Calibrate generic DOE prototype to metered whole building monthly energy use of a building where you only know the use type, HVAC type and location
2. Update calibrated model's HVAC system
3. use energy impact of HVAC update to estimate savings for the actual building.

Option 2.

1. update the HVAC system of the prototype
2. Calculate the percent savings from the updated HVAC system
3. Apply the percent savings to the know consumption of the actual building

Assume the calibration would be done as well as could be expected given the data availability limitations.

Thanks.

Would appreciate folks' thoughts on how best to use modelling to estimate savings when little is known about the subject building.

Say one wanted to estimate the energy savings from upgrading a building's HVAC system. All you know about this building is its use type (e.g. office), HVAC type (e.g. PVAV w/ elec reheat), location, and monthly EUI by fuel.

Is it worth trying to calibrate a generic prototype model (of same use type and HVAC type) to the monthly energy use data or, (given all the uncertainties inherent to the whole analysis) is it better to just finding a percent savings using the uncalibrated prototype model and applying that percent savings (monthly by fuel type) to the metered data?

In other words:

Option 1.

1. Calibrate generic DOE prototype to metered whole building monthly energy use of a building where you only know the use type, HVAC type and location
2. Update calibrated model's HVAC system
3. use energy impact of HVAC update to estimate savings for the actual building.

Option 2.

1. update the HVAC system of the prototype
2. Calculate the percent savings from the updated HVAC system
3. Apply the percent savings to the know consumption of the actual building

Assume the calibration would be done as well as could be expected given the data availability limitations.

Thanks.

Would appreciate folks' thoughts on how best to use modelling to estimate savings when little is known about the subject building.

Say one wanted to estimate the energy savings from upgrading a building's HVAC system. All you know about this building is its use type (e.g. office), HVAC type (e.g. PVAV w/ elec reheat), location, and monthly EUI by fuel.

Is it worth trying to calibrate a generic prototype model (of same use type and HVAC type) to the monthly energy use data or, (given all the uncertainties inherent to the whole analysis) is it better to just finding find a percent savings using the uncalibrated prototype model and applying that percent savings (monthly by fuel type) to the metered data?

In other words:

Option 1.

1. Calibrate generic DOE prototype to metered whole building monthly energy use of a building where you only know the use type, HVAC type and location
2. Update calibrated model's HVAC system
3. use energy impact of HVAC update to estimate savings for the actual building.

Option 2.

1. update the HVAC system of the prototype
2. Calculate the percent savings from the updated HVAC system
3. Apply the percent savings to the know consumption of the actual building

Assume the calibration would be done as well as could be expected given the data availability limitations.

Thanks.