Review of additional changes to #121 #124
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@wanhanlong1130 - I created this PR just for review purpose.
I left a few comments on the code directly. In general I think that what is in this branch is a bit too specific to two-stage units. Also, I'm not sure if we really need new dedicated functions. I think most of the changes can be done to the current calc_rated_eff function with some modifications:
- As you had started doing, we need to be able sets of curves for each modifier instead of a single curve. For that, I think that in the library we can have
lists of curve definition instead of a singledictfor instance instead of:
"set_of_curves": {
"cap-f-t": {
"out_var": "cap-f-t",
"type": "linear",
"coeff1": 1.304669191,
"coeff2": -0.008704834,
"x_min": 20,
"x_max": 40,
"out_min": 0,
"out_max": 999
}
We would have:
"set_of_curves": [
{
"cap-f-t": {
"out_var": "cap-f-t",
"type": "linear",
"coeff1": 1.304669191,
"coeff2": -0.008704834,
"x_min": 20,
"x_max": 40,
"out_min": 0,
"out_max": 999
}
]
That way, if a unit has the same curves for each stage or if it's a single stage unit the list would only have one item, if not, we would have a dict for each stage. This could be done in the exisiting get_dx_curves() function instead of having a dedicated one.
- Once this has been determined, the only two things that needs to be added in terms of steps in
calc_rated_effis to first determine which stage is going to be used to meet the load (or cycle), or are we cycling between two stages to meet the load and hence we need to perform and interpolation as per AHRI to determine the EER for a particular load percentage. This can be done at the beginning of the iteration through the different sets of rating conditions to calculate the IEER, the load to meet should be iteratively compared with each stage's capacity, for example, first we compare the load against the highest speed capacity, is the load small? If so, is it larger then the second highest speed capacity, if so? An interpolation will be performed as the load could be met by cycling the unit between these two speeds. If it is lower than the second highest speed and if this speed is the last speed, we need to apply the cycling degradation through the part load fraction curve.
| @@ -63,7 +63,7 @@ | |||
| "reducedplr": [1.0, 0.75, 0.5, 0.25], | |||
| "weightingfactor": [0.02, 0.617, 0.238, 0.125] | |||
| }, | |||
| "outdoor_unit_inlet_air_dry_bulb_rated": 35, | |||
| "outdoor_unit_inlet_air_dry_bulb_rated": 35.06, | |||
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Why was this a necessary change? I think that the AHRI standard uses 95 deg. F so 35 deg. C.
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changed back to 35
| set_of_curves=[], | ||
| set_of_curves_1=[], | ||
| set_of_curves_2=[], |
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We should probably use something more modular using a dict like for indoor_fan_speeds_mapping.
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Refer to the overall comments, we can do it like a dict. But this may also need update from the chiller side and Aowabin's work as well.
| @@ -61,6 +63,10 @@ def __init__( | |||
| indoor_fan_speeds=1, | |||
| indoor_fan_curve=False, | |||
| indoor_fan_power_unit="kW", | |||
| control_power = 100, | |||
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I think we add discussed this as also being a dict (or a list) in case the control_power varies for different stages (just like the example G4.3).
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changed to list in test but not here for default input.
| @@ -207,19 +225,19 @@ def __init__( | |||
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| # Cycling degradation | |||
| self.degradation_coefficient = degradation_coefficient | |||
| self.add_cycling_degradation_curve() | |||
| self.add_cycling_degradation_curve(set_of_curves=self.set_of_curves) | |||
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Why do we need set_of_curves as an argument? It's already a class variable.
| """Calculate unitary DX equipment fan power. | ||
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| :param float capacity_fraction: Ratio of actual capacity to net rated capacity | ||
| :param boolean ignore: ignore fan power or not |
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This is a bit confusing. Why would you call a function to calculate a fan power value and then force it to return 0? Might as well not call the function.
| Cd = -0.13*LF + 1.13 | ||
| eer_reduced = LF*net_cooling_cap_reduced/(LF*(Cd*(pc_pcd))+control_power+indoor_fan_power) |
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This is handled by the part load fraction (as a function of the part load ratio) curves.
| degradation = False | ||
| for stage_id, capacity_ratio in enumerate(self.compressor_stages): | ||
| if stage_id + 1 < len(self.compressor_stages): | ||
| if (self.compressor_stages[stage_id + 1] > reduced_plr[red_cap_num]): |
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Part load ratio and compressor stages aren't the same.
part_load_ratio = load / available_capacitywhereavailable_capacity = ref_cap * cap_f_t * cap_f_ff- If you compressor stage is 0.6 that means that at rated conditions (95F ECT, etc.) that your unit is rated to meet a load corresponding to 60% of
ref_cap. You need to compare the load with the compressor capacity at the current rated conditions to see if that stage can be the load or not.
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