Hi Nitin,

Sorry for the delay in response. I hope it is timely enough ? this sat in my draft box forgotten after a series of laptop crashing issues. This may yet remain useful or helpful for you and others constructing custom chiller curves:

***

Just getting a preference out of the way: I personally have not used the ?raw data entry? inputs for many years, as I settled on the alternative of deriving curve coefficients in Excel as my preferred approach. I find that allows me to understand and self-commission/visualize the process and results a little more clearly, before introducing into my model. Not suggesting you need to change course here but only recognizing I?m at least a half-step outside of my typical element.

With that said, looking at your raw data entry screenshots I observe a couple issues which may be together playing into your suspect results:
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This screenshot is sufficient to illustrate a few points, in no particular order of priority:

1. The blue box highlights that you have only really established one dependent variable (Y, entering condenser temp). There is no variance in your data to help eQuest solve what happens if and when the supply water temperature (X) varies by even half a degree. To derive coefficients for a curve with two dependent variables, you need to seek/secure performance data showing performance for a range around the expected operating points (i.e. minimally, try to get the same information but for 42 and for 46 degree supply, or better work out first what the reasonable bounds of intended/actual machine operation are and seek those boundaries instead/additionally).
2. The green box highlights redundant points of data that add nothing to the coefficient regression effort. Redundant points are similarly entered for the other two curves.
3. I think I am observing evidence of a data collection issue which I and others have commonly struggled with in trying to specifically build capacity curves. This curve (Cap-fCHWT&ECT) is supposed to answer the prompt ?how is the machine?s maximum capacity affected by varying operating conditions?? It appears the person who ran the performance numbers for you did not totally understand this intent/prompt (a common occurence).
* The first row of data makes sense. At ARI/design conditions, you would anticipate the machine?s maximum capacity to be ?as specified? (1.0).
* The rows following grow concerning. If a chiller at ARI conditions has its peak stable capacity fully halved (0.50) when provided 20 degree cooler water from the tower? something is very wrong indeed.
* What likely happened is the person sourcing this data with typical chiller selection software punched your dependent variable (Z) in as an independent variable (X, Y, etc) in order to resolve on another dependent (like COP). They did not go through the extra effort required to seek out ?how much tonnage can I squeeze out of operating conditions X & Y before my software throws an error/fault on the selected machine??
* Understanding/establishing how peak capacity varies with more and less conducive conditions (relative to the reference ARI/design conditions) is important, because that ?moving target? for peak capacity is used to determine part load ratio (PLR) at every interval.

Earlier in my career, I think it may be reassuring to observe I struggled mightily with both:

1. Personally understanding this technical matter well enough to teach & guide my chiller reps towards sourcing the right information, and
2. Balancing/recognizing egos, on both sides of the table. For whatever experience and knowledge I have scrapped together over the years, the chiller reps sourcing my chiller data (should) receive specialized training in their field making them the subject matter experts for their particular equipment. That typical relationship is not always conducive to asserting ?I understand how you do this part of your job but I need something different.? I maintain building energy simulation is, over the long haul, at least equal parts technical engineering and social engineering for reasons like this.

I hope this may help lead you and others towards working solutions, Nitin!

~Nick C.

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Nick Caton, P.E. (US), BEMP
??? ????, P.E. (US), BEMP
Senior Energy Engineer
Energy Manager, Yokota Airbase
ESS - Energy & Sustainability Services
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Email
+81 . 070 . 3366 . 3317
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nicholas.caton at se.com
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