Table 7.

Summary of assumptions for using the model to predict net consumption for a year

Assumption	Notes
1. The fitted model sufficiently predicts mean response.	The potential biases noted in Figure 4 and loss of normality in the residuals could weaken this assumption. If there are a large number of days in regions where the potential prediction biases exists the results could be skewed.
2. A calendar year contains a sufficient number of days for mean response to overcome prediction variability.	Aggregating a daily model over a year’s worth of predictions inherently increases uncertainty in the summed value. Confidence intervals on the sum can easily inflate to absurd widths. If assumption 1 and 2 hold, the resulting sum should be somewhat representative of the mean yearly total.
3. The E+ results are sufficiently accurate to serve as a basis for comparison.	EnergyPlus is a simulation model with its own implicit uncertainty and assumptions. Its results cannot be considered a perfect predictor, however its overall acceptance in practice and vetted physics-based models provide some confidence in its accuracy.
4. TMY3 data is used for all locations.	Issues with TMY3 data are noted in the literature review. However, they are currently the best source of estimated weather data.
5. The Perez model was used in converting TMY3 irradiance data to plane of array insolation data.	Albedo was not used in determining insolation, as some weather files did not contain albedo measurements.
6. The NZERTF house operates identically regardless of location.	Occupant behavior, appliance usage, and thermostat set points are unchanged.
7. The NZERTF construction is identical regardless of location	Building orientation, envelope, materials, and plane of array for the solar PV system are unchanged.
8. All locations are within the Mixed-Humid climate zone, the region the NZERTF is located in and designed for.	This assumption reduces the chance of applying the regression model to conditions outside those it was fit to. It is still possible certain the chosen locations may produce ODB or INS values outside the range of the validation set, increasing uncertainty in their reported net consumptions.
9. Reported values are the result of a bootstrap procedure. The 5000 regressions performed to produce Table 6 were used to predict the yearly net consumption, producing 5000 yearly net consumption values.	This assumption simplified the calculation of confidence bounds on the yearly total of net consumption. As noted the partitioned data sets showed strong agreement with the trend in the full data, lending credence to the reduced data set having roughly equivalent predictive power.
10. Snow cover in the TMY3 files is properly accounted for in determining the irradiance values used in calculations.	Irradiance was calculated through NREL’s System Advisory Model with the option of including effects due to snow cover selected [38]. Doing so should provide appropriate irradiances for the calculation of solar PV generation.