hub/city_model_structure/monthly_to_hourly_demand.py
2020-10-26 08:26:31 -04:00

63 lines
2.1 KiB
Python

"""
monthly_to_hourly_demand module
SPDX - License - Identifier: LGPL - 3.0 - or -later
Copyright © 2020 Project Author Pilar Monsalvete pilar_monsalvete@yahoo.es
"""
import pandas as pd
import helpers.constants as cte
class MonthlyToHourlyDemand:
"""
MonthlyToHourlyDemand class
"""
def __init__(self, building):
self._hourly_heating = pd.DataFrame()
self._hourly_cooling = pd.DataFrame()
self._building = building
@property
def hourly_heating(self):
"""
hourly distribution of the monthly heating of a building
:return: [hourly_heating]
"""
# todo: this method and the insel model have to be reviewed for more than one thermal zone
external_temp = self._building.hourly_external_temperature
# todo: review index depending on how the schedules are defined, either 8760 or 24 hours
period = 'day'
for usage_zone in self._building.usage_zones:
temp_set = usage_zone.heating_setpoint
temp_back = usage_zone.heating_setback
occupancy = usage_zone.occupancy.occupant_schedule(period)
# todo: heating_schedule is still missing
heating_schedule = usage_zone.heating_schedule_month
self._hourly_heating = pd.DataFrame(columns=['monthly to hourly'])
i = 0
for month in range(0, 12):
temp_grad_month = 0
for day in cte.days_of_month[month]:
external_temp_med = 0
for hour in range(0, 24):
external_temp_med += external_temp[i]/24
for hour in range(0, 24):
if external_temp_med < temp_set[i] & heating_schedule[month] == 1:
if occupancy[hour] == 1:
temp_grad_day = temp_set[i] - external_temp[i]
else:
temp_grad_day = temp_back[i] - external_temp[i]
else:
temp_grad_day = 0
temp_grad_month += temp_grad_day
self._hourly_heating.append(self._building.monthly_heating(month)*temp_grad_day/temp_grad_month)
i += 1
return self._hourly_heating
@property
def hourly_cooling(self) -> NotImplementedError:
raise NotImplementedError