(Unfortunately, Metrix cannot handle this situation. Option C can.)
We treat solar like any other energy savings technology.
Since there is no solar PV system in the base year,
Bill kWh = kWh contributed by grid to building – kWh contributed to grid by solar PV system
Except, no kWh is contributed to the grid by the nonexistent solar PV system, so
Bill kWh = kWh contributed by grid to building = Building kWh = Grid kWh
But we have to still track Grid kWh and Solar to Grid kWh in the post-retrofit period because the utility buys and sells kWh at different rates after the solar is installed. Like in Case 5, we will use two meters in Option C software. One meter will be for the Grid kWh, and the other will be for the Solar to Grid kWh.
Because we are tracking Grid kWh and Solar to Grid kWh, to calculate the total savings, you are going to have to subtract Solar to Grid kWh from Grid kWh. Option C software has a feature that makes a “reverse meter” which is for this situation. Even though you enter in Solar to Grid kWh as positive amounts, it will subtract Solar to Grid kWh from the Grid kWh to determine total kWh.
For Grid kWh, we take the pre-retrofit bills that did not use solar and do a regression on these bills:
Baseline Grid kWh = Fit line of Bill kWh
As there is no solar PV system in the base year, we will use 0 as the baseline for Solar to Grid kWh:
Baseline Solar to Grid kWh = 0
We do not need to add a variable for solar insolation or percentage sunlight, because it was not an issue during the base year. There will likely be no relationship between this variable and energy usage during the base year, so the variable cannot be used.
For Actual data, we will have to track Grid kWh and Solar to Grid kWh.
Actual Grid kWh = Grid kWh
Actual Solar to Grid kWh = Solar to Grid kWh
For Grid kWh, then
Grid kWh Savings = Fit Line of Bill kWh – Actual Grid kWh
Solar to Grid kWh Savings = 0 – Actual Solar to Grid kWh
To do this in Option C
- Use two meters.
- One meter for Grid kWh (which is the same as Bill kWh), and
- One “reverse” meter for Solar to Grid kWh. You do not need to enter any pre-retrofit bills for Solar to Grid kWh, as there was no solar PV system during the base year.
- Do a regression of the base year Grid kWh.
- Manually set the regression of the base year Solar to Grid kWh to 0
- Model the rates separately. One rate for Grid kWh and one rate for Solar to Grid kWh.
- For post retrofit bills, enter the Grid kWh on the Grid meter, and
- Enter Solar to Grid kWh on the Solar to Grid meter. You will enter these numbers as positives, but OC will make them negatives in the reporting, as it should.
- When you make reports, you will make them at the Area or Site Level, and this rolls up the two meters into one.
In this example, we are given 2 days of usage in a month.
|Fit line of Grid
|Fit line of Solar to Grid
|Actual Solar to Grid
|Solar to Grid
|Day 1 kWh
|Day 2 kWh
How to Handle Demand
You would treat demand almost exactly as you treat energy. Solar to Grid kW is not tracked, so:
Grid kW Savings = Fit Line of Bill kW – Actual Grid kW
Another Way to Handle Solar
One problem associated with the method I described above is that your solar savings are going to be subject to changes in weather. If a volcano blows up, or you have an unusually overcast summer, your solar system will not provide the savings you expected. Assuming you only guaranteed 85% or 90% of what you expected the solar to provide, everything should work out. But what if the variation is greater?
In general, over the life of a performance contract, weather fluctuations should even out. So you can make a good argument for not addressing the variation of solar production due to weather.
However, if you want your savings numbers to not be at the mercy of weather, but only subject to how well the project performs, you could introduce a variable for solar.
There was no solar in the base year, but there is in the performance year.
You can do a regression of solar production to solar insolation for the performance year. (You will have to do this again for every year of the performance period.) Then you apply TMY weather data to your regression equation. The result will be, “This is how much solar production we would have had in a typical year with the equipment as it is now running.”
This method is fair. But there is an implicit assumption that TMY data is accurate, and there have been studies that show that TMY data seems to change every decade.
You are measuring the solar system’s production each year. If you do this, then you would have to measure Building kWh at the building, which is Bill kWh during the base year, and it is sub-metered Building kWh during the performance period. You would have to track savings for all ECMs except for solar using this method, and then add in the solar savings using the method we are speaking of now.
If you were to use Option C software, you can model this as follows:
- Add meter with baseline = 0. That is the solar production meter.
- A meter with performance period data for solar production. Enter it positive.
- Enter a variable for solar insolation or solar irradiance
- Do a regression on each performance year solar production using your variable.
- Import TMY data
- And provide a report of savings, Baseline – Actual, where Baseline = 0, and Actual is the solar production as estimated by the regression equation which was created with performance year data.
If you want to measure Solar to Grid kWh, then you probably should just use the method presented above, where
Solar to Grid kWh Savings = 0 – Actual Solar to Grid kWh
I cannot think of any way to use TMY on this that is not too convoluted. Fortunately, Solar to Grid $ will in most cases be very small.
The Option C software will likely not be able to make a report that shows savings using this two-regression method (for solar) and the traditional one-regression method (for the other ECMs) together. You will most likely have to copy and paste and format results from the software in Excel to make a report that handles both the solar and the rest of the facility.