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Detailed performance curve changes #202

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f5c09a9
added detailed performance data and some calculations (not fully func…
kendallbaertlein Dec 9, 2024
ae12e7a
merge dev into the performance curve branch (#195)
jmaguire1 Sep 11, 2025
3ccf356
Merge branch 'dev' of https://github.com/NREL/OCHRE into detailed-per…
jmaguire1 Dec 10, 2025
19ed1b1
find the closest from table instead of exact match
yzhou601 Jan 1, 2026
9c04963
process efficiency, refactor of detailed performance data processing,…
yzhou601 Jan 3, 2026
efe0f91
fix some small issues
yzhou601 Jan 3, 2026
63fe908
store capacity watts instead of btu/hr in detailed performance data, …
yzhou601 Jan 3, 2026
6e96bd0
heating default
yzhou601 Jan 23, 2026
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13 changes: 11 additions & 2 deletions ochre/Equipment/HVAC.py
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Original file line number Diff line number Diff line change
@@ -1,6 +1,8 @@
import datetime as dt
import numpy as np
import psychrolib
import re
import pandas as pd

from ochre.utils import OCHREException, convert, load_csv
from ochre.utils.units import kwh_to_therms
Expand Down Expand Up @@ -700,9 +702,16 @@ def __init__(self, control_type='Time', **kwargs):
rated_efficiency = kwargs.get('Rated Efficiency', '(Unknown Efficiency)')
multispeed_file = kwargs.get('multispeed_file', 'HVAC Multispeed Parameters.csv')
df_speed = load_csv(multispeed_file)
speed_params = df_speed.loc[(df_speed['HVAC Name'] == self.name) &
(df_speed['HVAC Efficiency'] == rated_efficiency) &
# Convert string to efficiency numbers, find the closest match
numeric_pattern = r"([-+]?(?:\d*\.?\d+))"
rated_efficiency_float = float(re.search(numeric_pattern, rated_efficiency).group())
df_speed['Temp_Efficiency_Float'] = pd.to_numeric(
df_speed['HVAC Efficiency'].str.extract(numeric_pattern)[0])
speed_params_subset = df_speed.loc[(df_speed['HVAC Name'] == self.name) &
(df_speed['Number of Speeds'] == self.n_speeds)]
closest_match_index = (speed_params_subset['Temp_Efficiency_Float'] - rated_efficiency_float).abs().idxmin()
df_speed = df_speed.drop(columns=['Temp_Efficiency_Float'])
speed_params = df_speed.loc[[closest_match_index]]
if not len(speed_params):
raise OCHREException(f'Cannot find multispeed parameters for {self.n_speeds}-speed {rated_efficiency} {self.name}')
assert len(speed_params) == 1
Expand Down
77 changes: 47 additions & 30 deletions ochre/utils/equipment.py
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Original file line number Diff line number Diff line change
Expand Up @@ -42,6 +42,12 @@
},
}

AIR_SOURCE_HEAT_RATED_ODB = round(convert(47.0, "degF", "degC"), 1) # Rated outdoor drybulb for air-source systems, heating
AIR_SOURCE_HEAT_RATED_IDB = round(convert(70.0, "degF", "degC"), 1) # Rated indoor drybulb for air-source systems, heating
AIR_SOURCE_COOL_RATED_ODB = round(convert(95.0, "degF", "degC"), 1) # Rated outdoor drybulb for air-source systems, cooling
AIR_SOURCE_COOL_RATED_OWB = round(convert(75.0, "degF", "degC"), 1) # Rated outdoor wetbulb for air-source systems, cooling
AIR_SOURCE_COOL_RATED_IDB = round(convert(80.0, "degF", "degC"), 1) # Rated indoor drybulb for air-source systems, cooling
AIR_SOURCE_COOL_RATED_IWB = round(convert(67.0, "degF", "degC"), 1) # Rated indoor wetbulb for air-source systems, cooling

def get_duct_info(ducts, zones, boundaries, construction, location, **kwargs):
# Get zone type from duct_zone and zone info
Expand Down Expand Up @@ -429,39 +435,50 @@ def calculate_duct_dse(hvac, ducts, climate_file='ASHRAE152_climate_data.csv',
return dse


def calc_c_d(is_heater, name, cop, number_of_speeds):
# Calculate coefficient of degredation (c_d) of equipment based on equipment type and EER/SEER/HSPF
# Should only affect cases with single speed and two speed compressor driven equipment (ASHP/AC)
# Capacity losses based on Jon Winkler's thesis and match what's in E+ with "Advanced Research Features for startup losses"
# https://drum.lib.umd.edu/bitstream/handle/1903/9493/Winkler_umd_0117E_10504.pdf?sequence=1&isAllowed=y page 200

if is_heater:
hspf = convert(cop, "W", "Btu/hour")
if number_of_speeds == 1:
if hspf < 7.0:
c_d = 0.2
else:
c_d = 0.11
elif number_of_speeds == 2:
c_d = 0.11
else:
c_d = 0.0 # Do no capacity degradation at startup, since this isn't on/off equipment
else: #cooling equipment
seer = convert(cop, "W", "Btu/hour")
if name =='Room AC':
c_d = 0.22
elif number_of_speeds == 1:
if seer < 13.0:
c_d = 0.2
else:
c_d = 0.07
elif number_of_speeds == 2:
c_d = 0.11
else:
c_d = 0.0 # Do no capacity degradation at startup, since this isn't on/off equipment
def calc_c_d(name, number_of_speeds):
# Calculate coefficient of degredation (c_d) of equipment based on RESNET HERS Addendum 82
if name == 'Room AC':
c_d = 0.22
elif number_of_speeds in [1, 2]:
c_d = 0.08
elif number_of_speeds == 4:
c_d = 0.4
else:
c_d = 0.0 # Do no capacity degradation at startup, since this isn't on/off equipment
return c_d


def calc_eer2_from_seer2(seer2, number_of_speeds):
# Regressions based on Central ACs & HPs in ENERGY STAR product lists
if number_of_speeds == 1:
return min(0.73 * seer2 + 1.47, seer2)
elif number_of_speeds == 2:
return min(0.63 * seer2 + 2.34, seer2)
elif number_of_speeds == 4:
return min(0.31 * seer2 + 6.45, seer2)


def calc_seer2_from_seer(seer, is_ducted):
if is_ducted:
return seer * 0.95 # ducted, split and packaged system assumption from OS-HPXML
else:
return seer


def calc_eer2_from_eer(eer, is_ducted):
if is_ducted:
return eer * 0.95 # ducted, split and packaged system assumption from OS-HPXML
else:
return eer


def calc_hspf2_from_hspf(hspf, is_ducted):
if is_ducted:
return hspf * 0.85 # ducted, split system assumption from OS-HPXML
else:
return hspf * 0.9


# Psychrometric functions for HVAC
# Originally taken from BEopt python code, author: shorowit
# see: https://cbr.nrel.gov/BEopt2/svn/trunk/Modeling/util.py
Expand Down
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