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If you are installing the sensor along with a new AC unit, then you would want to include it with the Cooling improvement, because it is a necessary additional cost that impacts the SIR of the improvement. If the AC is already installed, then it is sunk cost and the new sensor doesn’t really have an SIR. In that case you would make it a separate line item, since it is more of a safety issue and doesn’t require financial analysis. Does that clarify things?
On the DHW tab (detailed mode in Wizard), there is a Sink/Shower% control that allows you to set the total sink and shower water usage as a percentage of the standard usage for the number of bedrooms in the home. You can view and edit the standard assumptions on the Setup/Usage&Costs tab. You can model an improvement that reduces usage by setting the improved % to be less than the base %. The savings for this measure are listed separately in the improvement tables under the heading Reduce Water Use.
Before I address your examples, I will give you a little more detail on our model. Our model is based on a Lawrence Berkeley study, which found that the average incandescent light bulb was 67 watts and ran for 2.1 hours per day. The leads to an average annual consumption of 51.4 kWh/yr for incandescent bulbs. We assume that the average CFL consumes 25% as much energy (i.e. 16.75 watts). We are looking into adding a detailed lighting survey as an alternative to this model.
For your first scenario, you are replacing 10 incandescent bulbs with LEDs. Here is a simple approach :
- Base: 75 Incandescent, 25 CFL
- Improved: 65 Incandescent , 32 CFL
- I removed 10 incandescent and added 7= 10*9/13 CFL
If you have actually checked the wattage of each bulb in the house, you could convert each bulb count using the ratio of actual wattage to assumed wattage for each bulb. In that case initial counts would be 84=75*75/67 incandescent and 19=25*13/16.75 CFL. The final counts would be 73=65*75/67 incandescent and 24=19+5=19+10*9/16.75 CFL.
Hi Travis – Sorry for the delay. The person who would normally cover this topic has been unavailable.
Pool pump controls are located at the bottom of the Lights&Appl tab (standard mode) or the detailed mode of the Lighting/Appliances page in the Wizard. The controls should be pretty easy to understand. We don’t have detailed costing information, so please review the cost in the control to the right and adjust as appropriate for your situation. If you have further questions, feel free to ask them here.
When you select a Heat Pump option for a heating or cooling system, a button labeled H.P. appears to the right. Click that button to open an advanced interface that drives a detailed hourly heat pump analysis. This analysis generates effective seasonal heating and cooling efficiencies that can be pushed back to the main interface. Press F1 while you mouse is over that popup to open Help.
The geothermal analysis currently relies on a constant, user-set ground loop entry water temperature. Depending on the system design, it is likely that this temperature varies seasonally. If you think that there is significant temperature difference between the heating and cooling seasons, then you may want to change the input between calculations. We are currently investigating how to improve this interface and analysis and welcome any input you may have.
As I suspected, there is an error impacting the savings displayed on the window row. However this error does not impact the total package savings. I will explain why that is below. We will get out a patch later today to correct the problem.
OptiMiser simultaneously runs two very detailed models, one for the base building and one for the building with the proposed improvements in place. This ensures that the total package savings are calculated using our most robust model. Additionally OptiMiser runs a unique, but simpler model for each improvement measure that is represented by a row on the Details table. These models estimate the impact of adding/removing each improvement to/from the selected package. When an improvement is un-checked the savings on the row estimate the change to the total package savings incurred by checking the improvement. However, once an improvement is added to a package, the savings on it’s row are an apportionment of the total package savings. The two numbers will usually be slightly different due to interactions between the improvements in the package.
Running complete models for each measure would be too burdensome for a typical users computer, making OpitMiser unusable. The simple models are designed to incorporate the most significant interactions between the components and generate good individual savings estimates without bogging down your computer. These simple models allow us to give you the dynamically updating measure-by-measure savings information that makes the Details table so interactive and allows us to quickly calculate optimized packages on the Packages tables. Because these models are simpler than the detailed models used to generate the base and selected package models, the savings estimate of an un-selected item will often be slightly different, then the actual change to savings of the selected package to the realized by adding the improvement.
However, in any case where you see a disconcerting discrepancy between either the checked and unchecked savings, or the unchecked savings and the actual change to the package savings, then it is a good idea to submit an error report. This will always help us to improve our estimates.
There are several reasons why the “checked” and “un-checked” numbers will almost never be identical. This is partially by design and partially due to modeling limitations. However, this is an unusually large discrepancy. I would like to review this file, before giving you my full explanation. Please open the file and submit an error report. You can assign it directly to me, by typing “gamaliel” in the Assign To field.
Modeling the solar and backup hot water sources as two separate systems is the correct method.
We do not currently have the means to automatically estimate the percent load met by the backup system. We do have a SolarThermal module in development that would allow you to model the solar collectors and estimate the annual load that they could meet. We are currently looking for beta testers for this module. If you would like to try it out, let us know.
I do not have any resources to help you determine the % backup. It would depend heavily on the size of the collectors and the scale of demand in the home. Your best bet is to use the utility base load as your guide and adjust the ratio to get the best fit between the model and utilities.
The solar screens cause an increase in heat load and a decrease in cooling load. The cooling load decrease is actually larger than the heating load increase. However, the cooling system has a much higher efficiency than the heating system. Heat pumps convert energy into met load at a much higher rate than combustion systems. Thus you end up expending more energy in terms of overall MBtu. However because there are such significant transmission losses for electricity, you probably get a net savings in energy at the point of generation. You also get a net savings in energy cost, due to the higher cost of electricity.
