242 lines
10 KiB
Python
242 lines
10 KiB
Python
"""
|
|
Comnet usage catalog
|
|
SPDX - License - Identifier: LGPL - 3.0 - or -later
|
|
Copyright © 2022 Concordia CERC group
|
|
Project Coder Guille Gutierrez guillermo.gutierrezmorote@concordia.ca
|
|
"""
|
|
from typing import Dict
|
|
|
|
import pandas as pd
|
|
|
|
import helpers.constants as cte
|
|
from catalog_factories.catalog import Catalog
|
|
from catalog_factories.data_models.usages.appliances import Appliances
|
|
from catalog_factories.data_models.usages.content import Content
|
|
from catalog_factories.data_models.usages.lighting import Lighting
|
|
from catalog_factories.data_models.usages.ocupancy import Occupancy
|
|
from catalog_factories.data_models.usages.schedule import Schedule
|
|
from catalog_factories.data_models.usages.thermal_control import ThermalControl
|
|
from catalog_factories.data_models.usages.usage import Usage
|
|
from catalog_factories.usage.usage_helper import UsageHelper
|
|
from helpers.configuration_helper import ConfigurationHelper as ch
|
|
|
|
|
|
class ComnetCatalog(Catalog):
|
|
def __init__(self, path):
|
|
self._comnet_archetypes_path = str(path / 'comnet_archetypes.xlsx')
|
|
self._comnet_schedules_path = str(path / 'comnet_schedules_archetypes.xlsx')
|
|
self._archetypes = self._read_archetype_file()
|
|
self._schedules = self._read_schedules_file()
|
|
|
|
sensible_convective = ch().comnet_occupancy_sensible_convective
|
|
sensible_radiative = ch().comnet_occupancy_sensible_radiant
|
|
lighting_convective = ch().comnet_lighting_convective
|
|
lighting_radiative = ch().comnet_lighting_radiant
|
|
lighting_latent = ch().comnet_lighting_latent
|
|
appliances_convective = ch().comnet_plugs_convective
|
|
appliances_radiative = ch().comnet_plugs_radiant
|
|
appliances_latent = ch().comnet_plugs_latent
|
|
|
|
usages = []
|
|
for schedule_key in self._archetypes['schedules_key']:
|
|
comnet_usage = schedule_key
|
|
schedule_name = self._archetypes['schedules_key'][schedule_key]
|
|
hours_day = self._calculate_hours_day(schedule_name)
|
|
occupancy_archetype = self._archetypes['occupancy'][comnet_usage]
|
|
lighting_archetype = self._archetypes['lighting'][comnet_usage]
|
|
appliances_archetype = self._archetypes['plug loads'][comnet_usage]
|
|
mechanical_air_change = None # comnet provides ventilation rate only
|
|
ventilation_rate = self._archetypes['ventilation rate'][comnet_usage]
|
|
# convert cfm/ft2 to m3/m2.s
|
|
ventilation_rate = ventilation_rate / (cte.METERS_TO_FEET * cte.MINUTES_TO_SECONDS)
|
|
|
|
# get occupancy
|
|
occupancy_density = occupancy_archetype[0] / pow(cte.METERS_TO_FEET, 2)
|
|
sensible_heat_gain = occupancy_archetype[1] * cte.BTU_H_TO_WATTS
|
|
latent_heat_gain = occupancy_archetype[1] * cte.BTU_H_TO_WATTS
|
|
if occupancy_density != 0:
|
|
occupancy_density = 1 / occupancy_density
|
|
sensible_convective_internal_gain = occupancy_density * sensible_heat_gain * sensible_convective
|
|
sensible_radiative_internal_gain = occupancy_density * sensible_heat_gain * sensible_radiative
|
|
latent_internal_gain = occupancy_density * latent_heat_gain
|
|
occupancy = Occupancy(occupancy_density,
|
|
sensible_convective_internal_gain,
|
|
sensible_radiative_internal_gain,
|
|
latent_internal_gain,
|
|
self._schedules[schedule_name]['Occupancy'])
|
|
|
|
# get lighting
|
|
density = lighting_archetype[4] / pow(cte.METERS_TO_FEET,2)
|
|
lighting = Lighting(density,
|
|
lighting_convective,
|
|
lighting_radiative,
|
|
lighting_latent,
|
|
self._schedules[schedule_name]['Lights'])
|
|
|
|
# get appliances
|
|
density = appliances_archetype[0]
|
|
if density == 'n.a.':
|
|
density = 0
|
|
# convert W/ft2 to W/m2
|
|
density = float(density) / pow(cte.METERS_TO_FEET,2)
|
|
appliances = Appliances(density,
|
|
appliances_convective,
|
|
appliances_radiative,
|
|
appliances_latent,
|
|
self._schedules[schedule_name]['Receptacle'])
|
|
|
|
# get thermal control
|
|
max_heating_setpoint = cte.MIN_FLOAT
|
|
min_heating_setpoint = cte.MAX_FLOAT
|
|
|
|
for schedule in self._schedules[schedule_name]['HtgSetPt']:
|
|
if schedule.values is None:
|
|
max_heating_setpoint = None
|
|
min_heating_setpoint = None
|
|
break
|
|
if max(schedule.values) > max_heating_setpoint:
|
|
max_heating_setpoint = max(schedule.values)
|
|
if min(schedule.values) < min_heating_setpoint:
|
|
min_heating_setpoint = min(schedule.values)
|
|
|
|
min_cooling_setpoint = cte.MAX_FLOAT
|
|
for schedule in self._schedules[schedule_name]['ClgSetPt']:
|
|
if schedule.values is None:
|
|
min_cooling_setpoint = None
|
|
break
|
|
if min(schedule.values) < min_cooling_setpoint:
|
|
min_cooling_setpoint = min(schedule.values)
|
|
thermal_control = ThermalControl(max_heating_setpoint,
|
|
min_heating_setpoint,
|
|
min_cooling_setpoint,
|
|
self._schedules[schedule_name]['HVAC Avail'],
|
|
self._schedules[schedule_name]['HtgSetPt'],
|
|
self._schedules[schedule_name]['ClgSetPt']
|
|
)
|
|
|
|
usages.append(Usage(comnet_usage,
|
|
hours_day,
|
|
365,
|
|
mechanical_air_change,
|
|
ventilation_rate,
|
|
occupancy,
|
|
lighting,
|
|
appliances,
|
|
thermal_control))
|
|
|
|
self._content = Content(usages)
|
|
|
|
def _read_schedules_file(self) -> Dict:
|
|
dictionary = {}
|
|
comnet_usages = UsageHelper().comnet_schedules_key_to_comnet_schedules
|
|
comnet_days = UsageHelper().comnet_days
|
|
comnet_data_types = UsageHelper().comnet_data_type_to_hub_data_type
|
|
for usage_name in comnet_usages:
|
|
if usage_name == 'C-13 Data Center':
|
|
continue
|
|
_extracted_data = pd.read_excel(self._comnet_schedules_path, sheet_name=comnet_usages[usage_name],
|
|
skiprows=[0, 1, 2, 3], nrows=39, usecols="A:AA")
|
|
_schedules = {}
|
|
for row in range(0, 39, 3):
|
|
_schedule_values = {}
|
|
schedule_name = _extracted_data.loc[row:row, 'Description'].item()
|
|
schedule_data_type = comnet_data_types[_extracted_data.loc[row:row, 'Type'].item()]
|
|
for day in comnet_days:
|
|
# Monday to Friday
|
|
start = row
|
|
end = row + 1
|
|
if day == cte.SATURDAY:
|
|
start = start + 1
|
|
end = end + 1
|
|
elif day == cte.SUNDAY or day == cte.HOLIDAY:
|
|
start = start + 2
|
|
end = end + 2
|
|
_schedule_values[day] = _extracted_data.iloc[start:end, 3:27].to_numpy().tolist()[0]
|
|
_schedule = []
|
|
for day in _schedule_values:
|
|
if schedule_data_type == 'temperature':
|
|
# to celsius
|
|
if 'n.a.' in _schedule_values[day]:
|
|
_schedule_values[day] = None
|
|
else:
|
|
_schedule_values[day] = [(float(value)-32)*5/9 for value in _schedule_values[day]]
|
|
_schedule.append(Schedule(schedule_name, _schedule_values[day], schedule_data_type, cte.HOUR, cte.DAY, [day]))
|
|
_schedules[schedule_name] = _schedule
|
|
dictionary[usage_name] = _schedules
|
|
return dictionary
|
|
|
|
def _read_archetype_file(self) -> Dict:
|
|
"""
|
|
reads xlsx files containing usage information into a dictionary
|
|
:return : Dict
|
|
"""
|
|
number_usage_types = 33
|
|
xl_file = pd.ExcelFile(self._comnet_archetypes_path)
|
|
file_data = pd.read_excel(xl_file, sheet_name="Modeling Data", skiprows=[0, 1, 2, 24],
|
|
nrows=number_usage_types, usecols="A:AB")
|
|
|
|
lighting_data = {}
|
|
plug_loads_data = {}
|
|
occupancy_data = {}
|
|
ventilation_rate = {}
|
|
water_heating = {}
|
|
process_data = {}
|
|
schedules_key = {}
|
|
for j in range(0, number_usage_types-1):
|
|
usage_parameters = file_data.iloc[j]
|
|
usage_type = usage_parameters[0]
|
|
lighting_data[usage_type] = usage_parameters[1:6].values.tolist()
|
|
plug_loads_data[usage_type] = usage_parameters[8:13].values.tolist()
|
|
occupancy_data[usage_type] = usage_parameters[17:20].values.tolist()
|
|
ventilation_rate[usage_type] = usage_parameters[20:21].item()
|
|
water_heating[usage_type] = usage_parameters[23:24].item()
|
|
process_data[usage_type] = usage_parameters[24:26].values.tolist()
|
|
schedules_key[usage_type] = usage_parameters[27:28].item()
|
|
|
|
|
|
return {'lighting': lighting_data,
|
|
'plug loads': plug_loads_data,
|
|
'occupancy': occupancy_data,
|
|
'ventilation rate': ventilation_rate,
|
|
'water heating': water_heating,
|
|
'process': process_data,
|
|
'schedules_key': schedules_key
|
|
}
|
|
|
|
def _calculate_hours_day(self, function):
|
|
days = [cte.MONDAY, cte.TUESDAY, cte.WEDNESDAY, cte.THURSDAY, cte.FRIDAY, cte.SATURDAY, cte.SUNDAY, cte.HOLIDAY]
|
|
number_of_days_per_type = [51, 50, 50, 50, 50, 52, 52, 10]
|
|
total = 0
|
|
for schedule in self._schedules[function]['HVAC Avail']:
|
|
yearly_days = number_of_days_per_type[days.index(schedule.day_types[0])]
|
|
for value in schedule.values:
|
|
total += value * yearly_days
|
|
return total / 365
|
|
|
|
def names(self, category=None):
|
|
"""
|
|
Get the catalog elements names
|
|
:parm: for usage catalog category filter does nothing as there is only one category (usages)
|
|
"""
|
|
_names = {'usages': []}
|
|
for usage in self._content.usages:
|
|
_names['usages'].append(usage.usage)
|
|
return _names
|
|
|
|
def entries(self, category=None):
|
|
"""
|
|
Get the catalog elements
|
|
:parm: for usage catalog category filter does nothing as there is only one category (usages)
|
|
"""
|
|
return self._content
|
|
|
|
def get_entry(self, name):
|
|
"""
|
|
Get one catalog element by names
|
|
:parm: entry name
|
|
"""
|
|
for usage in self._content.usages:
|
|
if usage.usage.lower() == name.lower():
|
|
return usage
|
|
raise IndexError(f"{name} doesn't exists in the catalog")
|