feat: simulation models of 2 archetypes with central heating and decentral cooling and dhw are added
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@ -484,7 +484,7 @@ class Building(CityObject):
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monthly_values = PeakLoads().peak_loads_from_hourly(self.domestic_hot_water_heat_demand[cte.HOUR])
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if monthly_values is None:
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return None
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results[cte.MONTH] = [x for x in monthly_values]
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results[cte.MONTH] = [x / cte.WATTS_HOUR_TO_JULES for x in monthly_values]
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results[cte.YEAR] = [max(monthly_values) / cte.WATTS_HOUR_TO_JULES]
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return results
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@ -810,39 +810,16 @@ class Building(CityObject):
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Get total electricity produced onsite in J
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return: dict
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"""
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orientation_losses_factor = {cte.MONTH: {'north': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
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'east': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
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'south': [2.137931, 1.645503, 1.320946, 1.107817, 0.993213, 0.945175,
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0.967949, 1.065534, 1.24183, 1.486486, 1.918033, 2.210526],
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'west': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]},
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cte.YEAR: {'north': [0],
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'east': [0],
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'south': [1.212544],
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'west': [0]}
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}
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# Add other systems whenever new ones appear
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if self.energy_systems is None:
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return self._onsite_electrical_production
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for energy_system in self.energy_systems:
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for generation_system in energy_system.generation_systems:
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if generation_system.system_type == cte.PHOTOVOLTAIC:
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if generation_system.electricity_efficiency is not None:
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_efficiency = float(generation_system.electricity_efficiency)
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else:
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_efficiency = 0
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self._onsite_electrical_production = {}
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for _key in self.roofs[0].global_irradiance.keys():
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_results = [0 for _ in range(0, len(self.roofs[0].global_irradiance[_key]))]
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for surface in self.roofs:
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if _key in orientation_losses_factor:
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_results = [x + y * _efficiency * surface.perimeter_area
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* surface.solar_collectors_area_reduction_factor * z
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for x, y, z in zip(_results, surface.global_irradiance[_key],
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orientation_losses_factor[_key]['south'])]
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self._onsite_electrical_production[_key] = _results
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return self._onsite_electrical_production
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@onsite_electrical_production.setter
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def onsite_electrical_production(self, value):
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"""
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set onsite electrical production from external pv simulations
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:return:
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"""
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self._onsite_electrical_production = value
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@property
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def lower_corner(self):
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"""
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@ -913,10 +890,3 @@ class Building(CityObject):
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self._fuel_consumption_breakdown = fuel_breakdown
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return self._fuel_consumption_breakdown
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@property
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def pv_generation(self) -> dict:
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return self._pv_generation
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@pv_generation.setter
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def pv_generation(self, value):
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self._pv_generation = value
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@ -1559,6 +1559,15 @@
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<system_id>12</system_id>
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</systems>
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</system_archetype>
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<system_archetype id="15">
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<name>Central Heating+Unitary Cooling+Unitary DHW+PV</name>
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<systems>
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<system_id>7</system_id>
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<system_id>10</system_id>
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<system_id>11</system_id>
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<system_id>12</system_id>
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</systems>
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</system_archetype>
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</system_archetypes>
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</EnergySystemCatalog>
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@ -8,6 +8,7 @@ Project Coder Saeed Ranjbar saeed.ranjbar@mail.concordia.ca
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from scripts.system_simulation_models.archetype13 import Archetype13
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from scripts.system_simulation_models.archetype13_stratified_tes import Archetype13Stratified
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from scripts.system_simulation_models.archetype1 import Archetype1
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from scripts.system_simulation_models.archetypes14_15 import Archetype14_15
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class EnergySystemsSimulationFactory:
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@ -36,6 +37,15 @@ class EnergySystemsSimulationFactory:
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self._building.level_of_detail.energy_systems = 2
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self._building.level_of_detail.energy_systems = 2
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def _archetype14_15(self):
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"""
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Enrich the city by using the sizing and simulation model developed for archetype14 and archetype15 of
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montreal_future_systems
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"""
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Archetype14_15(self._building, self._output_path).enrich_buildings()
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self._building.level_of_detail.energy_systems = 2
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self._building.level_of_detail.energy_systems = 2
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def enrich(self):
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"""
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Enrich the city given to the class using the class given handler
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@ -49,18 +49,11 @@ class PVSizingSimulation(RadiationTilted):
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available_roof = self.available_space()
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inter_row_spacing = self.inter_row_spacing()
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self.number_of_panels(available_roof, inter_row_spacing)
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self.building.roofs[0].installed_solar_collector_area = pv_module_area * self.total_number_of_panels
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system_efficiency = 0.2
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pv_hourly_production = [x * system_efficiency * self.total_number_of_panels * pv_module_area for x in radiation]
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pv_hourly_production = [x * system_efficiency * self.total_number_of_panels * pv_module_area *
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cte.WATTS_HOUR_TO_JULES for x in radiation]
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self.building.onsite_electrical_production[cte.HOUR] = pv_hourly_production
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self.building.onsite_electrical_production[cte.MONTH] = (
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MonthlyValues.get_total_month(self.building.onsite_electrical_production[cte.HOUR]))
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self.building.onsite_electrical_production[cte.YEAR] = [sum(self.building.onsite_electrical_production[cte.MONTH])]
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self.building.onsite_electrical_production[cte.YEAR] = [sum(self.building.onsite_electrical_production[cte.MONTH])]
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@ -29,8 +29,9 @@ residential_systems_percentage = {'system 1 gas': 100,
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'system 8 electricity': 0}
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residential_new_systems_percentage = {'PV+ASHP+GasBoiler+TES': 0,
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'PV+4Pipe+DHW': 100,
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'Central Heating+Unitary Cooling+Unitary DHW': 0,
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'PV+4Pipe+DHW': 0,
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'Central Heating+Unitary Cooling+Unitary DHW': 50,
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'Central Heating+Unitary Cooling+Unitary DHW+PV': 50,
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'PV+ASHP+ElectricBoiler+TES': 0,
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'PV+GSHP+GasBoiler+TES': 0,
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'PV+GSHP+ElectricBoiler+TES': 0,
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@ -19,7 +19,8 @@ class Archetype13:
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self._domestic_hot_water_peak_load = building.domestic_hot_water_peak_load[cte.YEAR][0]
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self._hourly_heating_demand = [demand / cte.HOUR_TO_SECONDS for demand in building.heating_demand[cte.HOUR]]
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self._hourly_cooling_demand = [demand / cte.HOUR_TO_SECONDS for demand in building.cooling_demand[cte.HOUR]]
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self._hourly_dhw_demand = building.domestic_hot_water_heat_demand[cte.HOUR]
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self._hourly_dhw_demand = [demand / cte.WATTS_HOUR_TO_JULES for demand in
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building.domestic_hot_water_heat_demand[cte.HOUR]]
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self._output_path = output_path
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self._t_out = building.external_temperature[cte.HOUR]
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self.results = {}
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@ -30,11 +31,12 @@ class Archetype13:
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heat_pump = self._hvac_system.generation_systems[1]
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boiler = self._hvac_system.generation_systems[0]
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thermal_storage = boiler.energy_storage_systems[0]
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heat_pump.nominal_heat_output = round(0.5 * self._heating_peak_load / 3600)
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heat_pump.nominal_cooling_output = round(self._cooling_peak_load / 3600)
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boiler.nominal_heat_output = round(0.5 * self._heating_peak_load / 3600)
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heat_pump.nominal_heat_output = round(0.5 * self._heating_peak_load)
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heat_pump.nominal_cooling_output = round(self._cooling_peak_load)
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boiler.nominal_heat_output = round(0.5 * self._heating_peak_load)
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thermal_storage.volume = round(
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(self._heating_peak_load * storage_factor) / (cte.WATER_HEAT_CAPACITY * cte.WATER_DENSITY * 25))
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(self._heating_peak_load * storage_factor * cte.WATTS_HOUR_TO_JULES) /
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(cte.WATER_HEAT_CAPACITY * cte.WATER_DENSITY * 25))
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return heat_pump, boiler, thermal_storage
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def dhw_sizing(self):
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402
scripts/system_simulation_models/archetypes14_15.py
Normal file
402
scripts/system_simulation_models/archetypes14_15.py
Normal file
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@ -0,0 +1,402 @@
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import math
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import hub.helpers.constants as cte
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import csv
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from hub.helpers.monthly_values import MonthlyValues
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class Archetype14_15:
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def __init__(self, building, output_path):
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self._building = building
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self._name = building.name
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if 'PV' in building.energy_systems_archetype_name:
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i = 1
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self._pv_system = building.energy_systems[0]
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else:
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i = 0
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self._dhw_system = building.energy_systems[i]
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self._heating_system = building.energy_systems[i + 1]
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self._cooling_system = building.energy_systems[i + 2]
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self._dhw_peak_flow_rate = (building.thermal_zones_from_internal_zones[0].total_floor_area *
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building.thermal_zones_from_internal_zones[0].domestic_hot_water.peak_flow *
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cte.WATER_DENSITY)
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self._heating_peak_load = building.heating_peak_load[cte.YEAR][0]
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self._cooling_peak_load = building.cooling_peak_load[cte.YEAR][0]
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self._domestic_hot_water_peak_load = building.domestic_hot_water_peak_load[cte.YEAR][0]
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self._hourly_heating_demand = [demand / cte.WATTS_HOUR_TO_JULES for demand in building.heating_demand[cte.HOUR]]
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self._hourly_cooling_demand = [demand / cte.WATTS_HOUR_TO_JULES for demand in building.cooling_demand[cte.HOUR]]
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self._hourly_dhw_demand = [demand / cte.WATTS_HOUR_TO_JULES for demand in
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building.domestic_hot_water_heat_demand[cte.HOUR]]
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self._output_path = output_path
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self._t_out = building.external_temperature[cte.HOUR]
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self.results = {}
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self.dt = 900
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def heating_system_sizing(self):
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storage_factor = 3
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heat_pump = self._heating_system.generation_systems[1]
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heat_pump.source_temperature = self._t_out
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boiler = self._heating_system.generation_systems[0]
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thermal_storage = boiler.energy_storage_systems[0]
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heat_pump.nominal_heat_output = round(0.5 * self._heating_peak_load)
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boiler.nominal_heat_output = round(0.5 * self._heating_peak_load)
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thermal_storage.volume = round(
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(self._heating_peak_load * storage_factor * cte.WATTS_HOUR_TO_JULES) /
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(cte.WATER_HEAT_CAPACITY * cte.WATER_DENSITY * 25))
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return heat_pump, boiler, thermal_storage
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def cooling_system_sizing(self):
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heat_pump = self._cooling_system.generation_systems[0]
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heat_pump.nominal_cooling_output = heat_pump.nominal_cooling_output = round(self._cooling_peak_load)
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heat_pump.source_temperature = self._t_out
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return heat_pump
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def dhw_system_sizing(self):
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storage_factor = 3
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dhw_hp = self._dhw_system.generation_systems[0]
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dhw_hp.nominal_heat_output = round(0.7 * self._domestic_hot_water_peak_load)
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dhw_hp.source_temperature = self._t_out
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dhw_tes = dhw_hp.energy_storage_systems[0]
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dhw_tes.volume = round(
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(self._domestic_hot_water_peak_load * storage_factor * cte.WATTS_HOUR_TO_JULES) /
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(cte.WATER_HEAT_CAPACITY * cte.WATER_DENSITY * 10))
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return dhw_hp, dhw_tes
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def heating_system_simulation(self):
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hp, boiler, tes = self.heating_system_sizing()
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cop_curve_coefficients = [float(coefficient) for coefficient in hp.heat_efficiency_curve.coefficients]
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number_of_ts = int(cte.HOUR_TO_SECONDS / self.dt)
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demand = [0] + [x for x in self._hourly_heating_demand for _ in range(number_of_ts)]
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t_out = [0] + [x for x in self._t_out for _ in range(number_of_ts)]
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hp.source_temperature = self._t_out
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variable_names = ["t_sup_hp", "t_tank", "t_ret", "m_ch", "m_dis", "q_hp", "q_boiler", "hp_cop",
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"hp_electricity", "boiler_gas_consumption", "t_sup_boiler", "boiler_energy_consumption",
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"heating_consumption"]
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num_hours = len(demand)
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variables = {name: [0] * num_hours for name in variable_names}
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(t_sup_hp, t_tank, t_ret, m_ch, m_dis, q_hp, q_boiler, hp_cop,
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hp_electricity, boiler_gas_consumption, t_sup_boiler, boiler_energy_consumption, heating_consumption) = \
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[variables[name] for name in variable_names]
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t_tank[0] = 55
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hp_heating_cap = hp.nominal_heat_output
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boiler_heating_cap = boiler.nominal_heat_output
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hp_delta_t = 5
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boiler_efficiency = float(boiler.heat_efficiency)
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v, h = float(tes.volume), float(tes.height)
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r_tot = sum(float(layer.thickness) / float(layer.material.conductivity) for layer in
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tes.layers)
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u_tot = 1 / r_tot
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d = math.sqrt((4 * v) / (math.pi * h))
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a_side = math.pi * d * h
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a_top = math.pi * d ** 2 / 4
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ua = u_tot * (2 * a_top + a_side)
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# storage temperature prediction
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for i in range(len(demand) - 1):
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t_tank[i + 1] = (t_tank[i] +
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(m_ch[i] * (t_sup_boiler[i] - t_tank[i]) +
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(ua * (t_out[i] - t_tank[i])) / cte.WATER_HEAT_CAPACITY -
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m_dis[i] * (t_tank[i] - t_ret[i])) * (self.dt / (cte.WATER_DENSITY * v)))
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# hp operation
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if t_tank[i + 1] < 40:
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q_hp[i + 1] = hp_heating_cap
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m_ch[i + 1] = q_hp[i + 1] / (cte.WATER_HEAT_CAPACITY * hp_delta_t)
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t_sup_hp[i + 1] = (q_hp[i + 1] / (m_ch[i + 1] * cte.WATER_HEAT_CAPACITY)) + t_tank[i + 1]
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elif 40 <= t_tank[i + 1] < 55 and q_hp[i] == 0:
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q_hp[i + 1] = 0
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m_ch[i + 1] = 0
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t_sup_hp[i + 1] = t_tank[i + 1]
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elif 40 <= t_tank[i + 1] < 55 and q_hp[i] > 0:
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q_hp[i + 1] = hp_heating_cap
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m_ch[i + 1] = q_hp[i + 1] / (cte.WATER_HEAT_CAPACITY * hp_delta_t)
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t_sup_hp[i + 1] = (q_hp[i + 1] / (m_ch[i + 1] * cte.WATER_HEAT_CAPACITY)) + t_tank[i + 1]
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else:
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q_hp[i + 1], m_ch[i + 1], t_sup_hp[i + 1] = 0, 0, t_tank[i + 1]
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t_sup_hp_fahrenheit = 1.8 * t_sup_hp[i + 1] + 32
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t_out_fahrenheit = 1.8 * t_out[i + 1] + 32
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if q_hp[i + 1] > 0:
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hp_cop[i + 1] = (cop_curve_coefficients[0] +
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cop_curve_coefficients[1] * t_sup_hp_fahrenheit +
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cop_curve_coefficients[2] * t_sup_hp_fahrenheit ** 2 +
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cop_curve_coefficients[3] * t_out_fahrenheit +
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cop_curve_coefficients[4] * t_out_fahrenheit ** 2 +
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cop_curve_coefficients[5] * t_sup_hp_fahrenheit * t_out_fahrenheit)
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hp_electricity[i + 1] = q_hp[i + 1] / hp_cop[i + 1]
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else:
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hp_cop[i + 1] = 0
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hp_electricity[i + 1] = 0
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# boiler operation
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if q_hp[i + 1] > 0:
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if t_sup_hp[i + 1] < 45:
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q_boiler[i + 1] = boiler_heating_cap
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elif demand[i + 1] > 0.5 * self._heating_peak_load / self.dt:
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q_boiler[i + 1] = 0.5 * boiler_heating_cap
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boiler_energy_consumption[i + 1] = q_boiler[i + 1] / boiler_efficiency
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boiler_gas_consumption[i + 1] = (q_boiler[i + 1] * self.dt) / (boiler_efficiency * cte.NATURAL_GAS_LHV)
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t_sup_boiler[i + 1] = t_sup_hp[i + 1] + (q_boiler[i + 1] / (m_ch[i + 1] * cte.WATER_HEAT_CAPACITY))
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# storage discharging
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if demand[i + 1] == 0:
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m_dis[i + 1] = 0
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t_ret[i + 1] = t_tank[i + 1]
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else:
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if demand[i + 1] > 0.5 * self._heating_peak_load / cte.HOUR_TO_SECONDS:
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factor = 8
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else:
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factor = 4
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m_dis[i + 1] = self._heating_peak_load / (cte.WATER_HEAT_CAPACITY * factor * cte.HOUR_TO_SECONDS)
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t_ret[i + 1] = t_tank[i + 1] - demand[i + 1] / (m_dis[i + 1] * cte.WATER_HEAT_CAPACITY)
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tes.temperature = []
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hp_electricity_j = [(x * cte.WATTS_HOUR_TO_JULES) / number_of_ts for x in hp_electricity]
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boiler_consumption_j = [(x * cte.WATTS_HOUR_TO_JULES) / number_of_ts for x in boiler_energy_consumption]
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hp_hourly = []
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boiler_hourly = []
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boiler_sum = 0
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hp_sum = 0
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for i in range(1, len(demand)):
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hp_sum += hp_electricity_j[i]
|
||||
boiler_sum += boiler_consumption_j[i]
|
||||
if (i - 1) % number_of_ts == 0:
|
||||
tes.temperature.append(t_tank[i])
|
||||
hp_hourly.append(hp_sum)
|
||||
boiler_hourly.append(boiler_sum)
|
||||
hp_sum = 0
|
||||
boiler_sum = 0
|
||||
hp.energy_consumption[cte.HEATING] = {}
|
||||
hp.energy_consumption[cte.HEATING][cte.HOUR] = hp_hourly
|
||||
hp.energy_consumption[cte.HEATING][cte.MONTH] = MonthlyValues.get_total_month(
|
||||
hp.energy_consumption[cte.HEATING][cte.HOUR])
|
||||
hp.energy_consumption[cte.HEATING][cte.YEAR] = [
|
||||
sum(hp.energy_consumption[cte.HEATING][cte.MONTH])]
|
||||
boiler.energy_consumption[cte.HEATING] = {}
|
||||
boiler.energy_consumption[cte.HEATING][cte.HOUR] = boiler_hourly
|
||||
boiler.energy_consumption[cte.HEATING][cte.MONTH] = MonthlyValues.get_total_month(
|
||||
boiler.energy_consumption[cte.HEATING][cte.HOUR])
|
||||
boiler.energy_consumption[cte.HEATING][cte.YEAR] = [
|
||||
sum(boiler.energy_consumption[cte.HEATING][cte.MONTH])]
|
||||
|
||||
self.results['Heating Demand (W)'] = demand
|
||||
self.results['HP Heat Output (W)'] = q_hp
|
||||
self.results['HP Source Temperature'] = t_out
|
||||
self.results['HP Supply Temperature'] = t_sup_hp
|
||||
self.results['HP COP'] = hp_cop
|
||||
self.results['HP Electricity Consumption (W)'] = hp_electricity
|
||||
self.results['Boiler Heat Output (W)'] = q_boiler
|
||||
self.results['Boiler Supply Temperature'] = t_sup_boiler
|
||||
self.results['Boiler Gas Consumption'] = boiler_gas_consumption
|
||||
self.results['TES Temperature'] = t_tank
|
||||
self.results['TES Charging Flow Rate (kg/s)'] = m_ch
|
||||
self.results['TES Discharge Flow Rate (kg/s)'] = m_dis
|
||||
self.results['Heating Loop Return Temperature'] = t_ret
|
||||
return hp_hourly, boiler_hourly
|
||||
|
||||
def cooling_system_simulation(self):
|
||||
hp = self.cooling_system_sizing()
|
||||
eer_curve_coefficients = [float(coefficient) for coefficient in hp.cooling_efficiency_curve.coefficients]
|
||||
cooling_efficiency = float(hp.cooling_efficiency)
|
||||
number_of_ts = int(cte.HOUR_TO_SECONDS / self.dt)
|
||||
demand = [0] + [x for x in self._hourly_cooling_demand for _ in range(number_of_ts)]
|
||||
t_out = [0] + [x for x in self._t_out for _ in range(number_of_ts)]
|
||||
hp.source_temperature = self._t_out
|
||||
variable_names = ["t_sup_hp", "t_ret", "m", "q_hp", "hp_electricity", "hp_eer"]
|
||||
num_hours = len(demand)
|
||||
variables = {name: [0] * num_hours for name in variable_names}
|
||||
(t_sup_hp, t_ret, m, q_hp, hp_electricity, hp_eer) = [variables[name] for name in variable_names]
|
||||
t_ret[0] = 13
|
||||
|
||||
for i in range(1, len(demand)):
|
||||
if demand[i] > 0:
|
||||
m[i] = self._cooling_peak_load / (cte.WATER_HEAT_CAPACITY * 5 * cte.HOUR_TO_SECONDS)
|
||||
if t_ret[i - 1] >= 13:
|
||||
if demand[i] < 0.25 * self._cooling_peak_load / cte.HOUR_TO_SECONDS:
|
||||
q_hp[i] = 0.25 * hp.nominal_cooling_output
|
||||
elif demand[i] < 0.5 * self._cooling_peak_load / cte.HOUR_TO_SECONDS:
|
||||
q_hp[i] = 0.5 * hp.nominal_cooling_output
|
||||
else:
|
||||
q_hp[i] = hp.nominal_cooling_output
|
||||
t_sup_hp[i] = t_ret[i - 1] - q_hp[i] / (m[i] * cte.WATER_HEAT_CAPACITY)
|
||||
else:
|
||||
q_hp[i] = 0
|
||||
t_sup_hp[i] = t_ret[i - 1]
|
||||
if m[i] == 0:
|
||||
t_ret[i] = t_sup_hp[i]
|
||||
else:
|
||||
t_ret[i] = t_sup_hp[i] + demand[i] / (m[i] * cte.WATER_HEAT_CAPACITY)
|
||||
else:
|
||||
m[i] = 0
|
||||
q_hp[i] = 0
|
||||
t_sup_hp[i] = t_ret[i -1]
|
||||
t_ret[i] = t_ret[i - 1]
|
||||
t_sup_hp_fahrenheit = 1.8 * t_sup_hp[i] + 32
|
||||
t_out_fahrenheit = 1.8 * t_out[i] + 32
|
||||
if q_hp[i] > 0:
|
||||
hp_eer[i] = (eer_curve_coefficients[0] +
|
||||
eer_curve_coefficients[1] * t_sup_hp_fahrenheit +
|
||||
eer_curve_coefficients[2] * t_sup_hp_fahrenheit ** 2 +
|
||||
eer_curve_coefficients[3] * t_out_fahrenheit +
|
||||
eer_curve_coefficients[4] * t_out_fahrenheit ** 2 +
|
||||
eer_curve_coefficients[5] * t_sup_hp_fahrenheit * t_out_fahrenheit)
|
||||
hp_electricity[i] = q_hp[i] / hp_eer[i]
|
||||
else:
|
||||
hp_eer[i] = 0
|
||||
hp_electricity[i] = 0
|
||||
hp_electricity_j = [(x * cte.WATTS_HOUR_TO_JULES) / number_of_ts for x in hp_electricity]
|
||||
hp_hourly = []
|
||||
hp_sum = 0
|
||||
for i in range(1, len(demand)):
|
||||
hp_sum += hp_electricity_j[i]
|
||||
if (i - 1) % number_of_ts == 0:
|
||||
hp_hourly.append(hp_sum)
|
||||
hp_sum = 0
|
||||
hp.energy_consumption[cte.COOLING] = {}
|
||||
hp.energy_consumption[cte.COOLING][cte.HOUR] = hp_hourly
|
||||
hp.energy_consumption[cte.COOLING][cte.MONTH] = MonthlyValues.get_total_month(
|
||||
hp.energy_consumption[cte.COOLING][cte.HOUR])
|
||||
hp.energy_consumption[cte.COOLING][cte.YEAR] = [
|
||||
sum(hp.energy_consumption[cte.COOLING][cte.MONTH])]
|
||||
self.results['Cooling Demand (W)'] = demand
|
||||
self.results['HP Cooling Output (W)'] = q_hp
|
||||
self.results['HP Cooling Supply Temperature'] = t_sup_hp
|
||||
self.results['HP Cooling COP'] = hp_eer
|
||||
self.results['HP Electricity Consumption'] = hp_electricity
|
||||
self.results['Cooling Loop Flow Rate (kg/s)'] = m
|
||||
self.results['Cooling Loop Return Temperature'] = t_ret
|
||||
return hp_hourly
|
||||
|
||||
def dhw_system_simulation(self):
|
||||
hp, tes = self.dhw_system_sizing()
|
||||
cop_curve_coefficients = [float(coefficient) for coefficient in hp.heat_efficiency_curve.coefficients]
|
||||
number_of_ts = int(cte.HOUR_TO_SECONDS / self.dt)
|
||||
demand = [0] + [x for x in self._hourly_dhw_demand for _ in range(number_of_ts)]
|
||||
t_out = [0] + [x for x in self._t_out for _ in range(number_of_ts)]
|
||||
variable_names = ["t_sup_hp", "t_tank", "m_ch", "m_dis", "q_hp", "q_coil", "hp_cop",
|
||||
"hp_electricity", "available hot water (m3)", "refill flow rate (kg/s)"]
|
||||
num_hours = len(demand)
|
||||
variables = {name: [0] * num_hours for name in variable_names}
|
||||
(t_sup_hp, t_tank, m_ch, m_dis, m_refill, q_hp, q_coil, hp_cop, hp_electricity, v_dhw) = \
|
||||
[variables[name] for name in variable_names]
|
||||
t_tank[0] = 70
|
||||
v_dhw[0] = tes.volume
|
||||
|
||||
hp_heating_cap = hp.nominal_heat_output
|
||||
hp_delta_t = 8
|
||||
v, h = float(tes.volume), float(tes.height)
|
||||
r_tot = sum(float(layer.thickness) / float(layer.material.conductivity) for layer in
|
||||
tes.layers)
|
||||
u_tot = 1 / r_tot
|
||||
d = math.sqrt((4 * v) / (math.pi * h))
|
||||
a_side = math.pi * d * h
|
||||
a_top = math.pi * d ** 2 / 4
|
||||
ua = u_tot * (2 * a_top + a_side)
|
||||
freshwater_temperature = 18
|
||||
for i in range(len(demand) - 1):
|
||||
delta_t_demand = demand[i] * (self.dt / (cte.WATER_DENSITY * cte.WATER_HEAT_CAPACITY * v))
|
||||
if t_tank[i] < 65:
|
||||
q_hp[i] = hp_heating_cap
|
||||
delta_t_hp = q_hp[i] * (self.dt / (cte.WATER_DENSITY * cte.WATER_HEAT_CAPACITY * v))
|
||||
if demand[i] > 0:
|
||||
dhw_needed = (demand[i] * cte.HOUR_TO_SECONDS) / (cte.WATER_HEAT_CAPACITY * t_tank[i] * cte.WATER_DENSITY)
|
||||
m_dis[i] = dhw_needed * cte.WATER_DENSITY / cte.HOUR_TO_SECONDS
|
||||
m_refill[i] = m_dis[i]
|
||||
delta_t_freshwater = m_refill[i] * (t_tank[i] - freshwater_temperature) * (self.dt / (v * cte.WATER_DENSITY))
|
||||
diff = delta_t_freshwater + delta_t_demand - delta_t_hp
|
||||
if diff > 0:
|
||||
if diff > 0:
|
||||
power = diff * (cte.WATER_DENSITY * cte.WATER_HEAT_CAPACITY * v) / self.dt
|
||||
if power <= float(tes.heating_coil_capacity):
|
||||
q_coil[i] = power
|
||||
else:
|
||||
q_coil[i] = float(tes.heating_coil_capacity)
|
||||
delta_t_coil = q_coil[i] * (self.dt / (cte.WATER_DENSITY * cte.WATER_HEAT_CAPACITY * v))
|
||||
|
||||
if q_hp[i] > 0:
|
||||
m_ch[i] = q_hp[i] / (cte.WATER_HEAT_CAPACITY * hp_delta_t)
|
||||
t_sup_hp[i] = (q_hp[i] / (m_ch[i] * cte.WATER_HEAT_CAPACITY)) + t_tank[i]
|
||||
else:
|
||||
m_ch[i] = 0
|
||||
t_sup_hp[i] = t_tank[i]
|
||||
t_sup_hp_fahrenheit = 1.8 * t_sup_hp[i] + 32
|
||||
t_out_fahrenheit = 1.8 * t_out[i] + 32
|
||||
if q_hp[i] > 0:
|
||||
hp_cop[i] = (cop_curve_coefficients[0] +
|
||||
cop_curve_coefficients[1] * t_sup_hp_fahrenheit +
|
||||
cop_curve_coefficients[2] * t_sup_hp_fahrenheit ** 2 +
|
||||
cop_curve_coefficients[3] * t_out_fahrenheit +
|
||||
cop_curve_coefficients[4] * t_out_fahrenheit ** 2 +
|
||||
cop_curve_coefficients[5] * t_sup_hp_fahrenheit * t_out_fahrenheit)
|
||||
hp_electricity[i] = q_hp[i] / hp_cop[i]
|
||||
else:
|
||||
hp_cop[i] = 0
|
||||
hp_electricity[i] = 0
|
||||
|
||||
t_tank[i + 1] = t_tank[i] + (delta_t_hp - delta_t_freshwater - delta_t_demand + delta_t_coil)
|
||||
tes.temperature = []
|
||||
hp_electricity_j = [(x * cte.WATTS_HOUR_TO_JULES) / number_of_ts for x in hp_electricity]
|
||||
heating_coil_j = [(x * cte.WATTS_HOUR_TO_JULES) / number_of_ts for x in q_coil]
|
||||
hp_hourly = []
|
||||
coil_hourly = []
|
||||
coil_sum = 0
|
||||
hp_sum = 0
|
||||
for i in range(1, len(demand)):
|
||||
hp_sum += hp_electricity_j[i]
|
||||
coil_sum += heating_coil_j[i]
|
||||
if (i - 1) % number_of_ts == 0:
|
||||
tes.temperature.append(t_tank[i])
|
||||
hp_hourly.append(hp_sum)
|
||||
coil_hourly.append(coil_sum)
|
||||
hp_sum = 0
|
||||
coil_sum = 0
|
||||
|
||||
hp.energy_consumption[cte.DOMESTIC_HOT_WATER] = {}
|
||||
hp.energy_consumption[cte.DOMESTIC_HOT_WATER][cte.HOUR] = hp_hourly
|
||||
hp.energy_consumption[cte.DOMESTIC_HOT_WATER][cte.MONTH] = MonthlyValues.get_total_month(
|
||||
hp.energy_consumption[cte.DOMESTIC_HOT_WATER][cte.HOUR])
|
||||
hp.energy_consumption[cte.DOMESTIC_HOT_WATER][cte.YEAR] = [
|
||||
sum(hp.energy_consumption[cte.DOMESTIC_HOT_WATER][cte.MONTH])]
|
||||
tes.heating_coil_energy_consumption = {}
|
||||
tes.heating_coil_energy_consumption[cte.HOUR] = coil_hourly
|
||||
tes.heating_coil_energy_consumption[cte.MONTH] = MonthlyValues.get_total_month(
|
||||
tes.heating_coil_energy_consumption[cte.HOUR])
|
||||
tes.heating_coil_energy_consumption[cte.YEAR] = [
|
||||
sum(tes.heating_coil_energy_consumption[cte.MONTH])]
|
||||
tes.temperature = t_tank
|
||||
|
||||
self.results['DHW Demand (W)'] = demand
|
||||
self.results['DHW HP Heat Output (W)'] = q_hp
|
||||
self.results['DHW HP Electricity Consumption (W)'] = hp_electricity
|
||||
self.results['DHW HP Source Temperature'] = t_out
|
||||
self.results['DHW HP Supply Temperature'] = t_sup_hp
|
||||
self.results['DHW HP COP'] = hp_cop
|
||||
self.results['DHW TES Heating Coil Heat Output (W)'] = q_coil
|
||||
self.results['DHW TES Temperature'] = t_tank
|
||||
self.results['DHW TES Charging Flow Rate (kg/s)'] = m_ch
|
||||
self.results['DHW Flow Rate (kg/s)'] = m_dis
|
||||
self.results['DHW TES Refill Flow Rate (kg/s)'] = m_refill
|
||||
self.results['Available Water in Tank (m3)'] = v_dhw
|
||||
return hp_hourly, coil_hourly
|
||||
|
||||
|
||||
def enrich_buildings(self):
|
||||
hp_heating, boiler_consumption = self.heating_system_simulation()
|
||||
hp_cooling = self.cooling_system_simulation()
|
||||
hp_dhw, heating_coil = self.dhw_system_simulation()
|
||||
heating_consumption = [hp_heating[i] + boiler_consumption[i] for i in range(len(hp_heating))]
|
||||
dhw_consumption = [hp_dhw[i] + heating_coil[i] for i in range(len(hp_dhw))]
|
||||
self._building.heating_consumption[cte.HOUR] = heating_consumption
|
||||
self._building.heating_consumption[cte.MONTH] = (
|
||||
MonthlyValues.get_total_month(self._building.heating_consumption[cte.HOUR]))
|
||||
self._building.heating_consumption[cte.YEAR] = [sum(self._building.heating_consumption[cte.MONTH])]
|
||||
self._building.cooling_consumption[cte.HOUR] = hp_cooling
|
||||
self._building.cooling_consumption[cte.MONTH] = (
|
||||
MonthlyValues.get_total_month(self._building.cooling_consumption[cte.HOUR]))
|
||||
self._building.cooling_consumption[cte.YEAR] = [sum(self._building.cooling_consumption[cte.MONTH])]
|
||||
self._building.domestic_hot_water_consumption[cte.HOUR] = dhw_consumption
|
||||
self._building.domestic_hot_water_consumption[cte.MONTH] = (
|
||||
MonthlyValues.get_total_month(self._building.domestic_hot_water_consumption[cte.HOUR]))
|
||||
self._building.domestic_hot_water_consumption[cte.YEAR] = (
|
||||
sum(self._building.domestic_hot_water_consumption[cte.MONTH]))
|
||||
file_name = f'energy_system_simulation_results_{self._name}.csv'
|
||||
with open(self._output_path / file_name, 'w', newline='') as csvfile:
|
||||
output_file = csv.writer(csvfile)
|
||||
# Write header
|
||||
output_file.writerow(self.results.keys())
|
||||
# Write data
|
||||
output_file.writerows(zip(*self.results.values()))
|
||||
|
|
@ -39,7 +39,7 @@ class TestSystemsCatalog(TestCase):
|
|||
|
||||
catalog_categories = catalog.names()
|
||||
archetypes = catalog.names()
|
||||
self.assertEqual(14, len(archetypes['archetypes']))
|
||||
self.assertEqual(15, len(archetypes['archetypes']))
|
||||
systems = catalog.names('systems')
|
||||
self.assertEqual(12, len(systems['systems']))
|
||||
generation_equipments = catalog.names('generation_equipments')
|
||||
|
|
|
|||
Loading…
Reference in New Issue
Block a user