OpenStudio EnergyPlus - Create Performance Tables

We discuss how to input performance tables based on manufacturer's data instead of using characterized polynomial curves. These tables can be use in most places where performance curves are used in EnergyPlus such as equipment with evaporators and condensers. You can download the spreadsheet file we used in this episode here:
https://docs.google.com/spreadsheets/...

Transcript:
Today we're going to be talking about performance curves. In a previous episode we talked about how to generate these performance curves using a curve fit.
This time we are going to talk about how to generate these performance curves using a table lookup.
We are working on a variable refrigerant volume (VRF) system. We are looking at the outdoor unit.
We are going to be looking at the cooling capacity ratio modifier function of low temperature curve.
This curve is a function of two different temperatures. Let us look at the EnergyPlus input output reference manual.
You can see that those two temperatures are indoor wet bulb temperature and the outdoor condenser entering air dry bulb temperature.
If we look at the manufacturer data, you will see that those those two performance curves are listed here.
We have this curve here which is the capacity as a function of the indoor unit wet bulb temperature.
And then this curve here is a function of the outdoor dry bulb temperature. We will be using these two curves to generate the cooling capacity as a function of temperature modifier.
If the curve is simple, you can just type in the numbers. If it is a more complex curve, you can use something like this plotdigitizer.com
You can output an image of this chart…we will just search for that image here and drop it in. Cooling capacity function of indoor wet bulb temperature.
This brought in our curve. You need to calibrate the chart. Start with the minimum X and the maximum X…the minimum Y and the maximum Y.
Now we can start adding points to it…and you'll see that…oh sorry, we need to calibrate these points.
X minimum starts at 15…maximum X goes to 24…the minimum Y goes to 0.8 and the maximum Y goes to 1.2.
You can see that first point that we dropped in. It starts giving you these coordinates.
…not sure what I had here before…19.98. The curve is going to go somewhere right here. The next one I had was 20.1.
This should should probably go right here. I think the next one I had right here was 24.
You can see the curve is not quite linear…just for simplification we are going to make it linear in these areas.
So, we have a low temperature curve. A moderate…or rather standard temperature. And we have higher temperatures.
Now we have the data over here. We can just copy and paste this. Copy. Paste it into our spreadsheet. There are the values.
Those values are a function of the indoor wet bulb temperature. We can do the same thing for outdoor dry bulb temperature.
Let us go back to our plotter. Drop those…drop that in there. Outdoor cooling capacity as a function of the outdoor dry bulb temperature. Put it onto the plotter.
Once again we need to calibrate the points. It is handy…you can see that it is magnified up in the top right.
You can get a pretty good placement of the data points on your chart. X1 is at 5. X2 is at…55. Y1 is at 3. Y2 is at 1.3
It is now calibrated. Let us see…I had only three data points on this. First data point is at -5°…place that right there.
It looks like it starts turning the curve right here…it is approximately linear down to here…
Now we have our curve and data. Just select this. Copy. Paste this into here.
We can go over to the spreadsheet…that is this information…it is the same information we input on the previous page.
It gets aggregated onto this page here. One thing you want to keep in mind; these independent variables should be sorted in ascending order.
The smallest number should be at the top. Largest number is at the bottom.
Like wise with these. They should be in ascending order. You could just sort these using Excel or whatever spreadsheet you have. Smallest to largest.
But these are already in smallest to largest…but that is important because when you are using this program…if you start adding in additional data points they get added in randomly.
Now let us go to the next page and start aggregating these. This is your independent variable. This is the dependent variable.
These two get combined into an output. The two dependent variables get multiplied together.
The result is the cooling capacity multiplier as a function of those two temperatures.
Starting from lowest to highest of our independent variables we have the indoor wet bulb modifier multiplied by the outdoor dry bulb modifier.
That give you the cooling capacity modifier as a list of possible outputs.
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Full transcript at:https://www.helix-engineers.net/techn...