From 5f95d2a5fb10fbf9764ceb0b11fd733f0df4fc57 Mon Sep 17 00:00:00 2001 From: s_ranjbar Date: Tue, 25 Jun 2024 18:14:12 -0400 Subject: [PATCH] feat: simulation models of 2 archetypes with central heating and decentral cooling and dhw are added --- hub/city_model_structure/building.py | 48 +-- .../montreal_future_systems.xml | 9 + ...gy_system_sizing_and_simulation_factory.py | 10 + scripts/pv_sizing_and_simulation.py | 15 +- scripts/random_assignation.py | 5 +- .../system_simulation_models/archetype13.py | 12 +- .../archetypes14_15.py | 402 ++++++++++++++++++ tests/test_systems_catalog.py | 2 +- 8 files changed, 445 insertions(+), 58 deletions(-) create mode 100644 scripts/system_simulation_models/archetypes14_15.py diff --git a/hub/city_model_structure/building.py b/hub/city_model_structure/building.py index ac284d29..132e7a5c 100644 --- a/hub/city_model_structure/building.py +++ b/hub/city_model_structure/building.py @@ -484,7 +484,7 @@ class Building(CityObject): monthly_values = PeakLoads().peak_loads_from_hourly(self.domestic_hot_water_heat_demand[cte.HOUR]) if monthly_values is None: return None - results[cte.MONTH] = [x for x in monthly_values] + results[cte.MONTH] = [x / cte.WATTS_HOUR_TO_JULES for x in monthly_values] results[cte.YEAR] = [max(monthly_values) / cte.WATTS_HOUR_TO_JULES] return results @@ -810,39 +810,16 @@ class Building(CityObject): Get total electricity produced onsite in J return: dict """ - orientation_losses_factor = {cte.MONTH: {'north': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], - 'east': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], - 'south': [2.137931, 1.645503, 1.320946, 1.107817, 0.993213, 0.945175, - 0.967949, 1.065534, 1.24183, 1.486486, 1.918033, 2.210526], - 'west': [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]}, - cte.YEAR: {'north': [0], - 'east': [0], - 'south': [1.212544], - 'west': [0]} - } - - # Add other systems whenever new ones appear - if self.energy_systems is None: - return self._onsite_electrical_production - for energy_system in self.energy_systems: - for generation_system in energy_system.generation_systems: - if generation_system.system_type == cte.PHOTOVOLTAIC: - if generation_system.electricity_efficiency is not None: - _efficiency = float(generation_system.electricity_efficiency) - else: - _efficiency = 0 - self._onsite_electrical_production = {} - for _key in self.roofs[0].global_irradiance.keys(): - _results = [0 for _ in range(0, len(self.roofs[0].global_irradiance[_key]))] - for surface in self.roofs: - if _key in orientation_losses_factor: - _results = [x + y * _efficiency * surface.perimeter_area - * surface.solar_collectors_area_reduction_factor * z - for x, y, z in zip(_results, surface.global_irradiance[_key], - orientation_losses_factor[_key]['south'])] - self._onsite_electrical_production[_key] = _results return self._onsite_electrical_production + @onsite_electrical_production.setter + def onsite_electrical_production(self, value): + """ + set onsite electrical production from external pv simulations + :return: + """ + self._onsite_electrical_production = value + @property def lower_corner(self): """ @@ -913,10 +890,3 @@ class Building(CityObject): self._fuel_consumption_breakdown = fuel_breakdown return self._fuel_consumption_breakdown - @property - def pv_generation(self) -> dict: - return self._pv_generation - - @pv_generation.setter - def pv_generation(self, value): - self._pv_generation = value diff --git a/hub/data/energy_systems/montreal_future_systems.xml b/hub/data/energy_systems/montreal_future_systems.xml index f9d43be4..b51c9488 100644 --- a/hub/data/energy_systems/montreal_future_systems.xml +++ b/hub/data/energy_systems/montreal_future_systems.xml @@ -1559,6 +1559,15 @@ 12 + + Central Heating+Unitary Cooling+Unitary DHW+PV + + 7 + 10 + 11 + 12 + + diff --git a/scripts/energy_system_sizing_and_simulation_factory.py b/scripts/energy_system_sizing_and_simulation_factory.py index b0526e2c..9a0e14bb 100644 --- a/scripts/energy_system_sizing_and_simulation_factory.py +++ b/scripts/energy_system_sizing_and_simulation_factory.py @@ -8,6 +8,7 @@ Project Coder Saeed Ranjbar saeed.ranjbar@mail.concordia.ca from scripts.system_simulation_models.archetype13 import Archetype13 from scripts.system_simulation_models.archetype13_stratified_tes import Archetype13Stratified from scripts.system_simulation_models.archetype1 import Archetype1 +from scripts.system_simulation_models.archetypes14_15 import Archetype14_15 class EnergySystemsSimulationFactory: @@ -36,6 +37,15 @@ class EnergySystemsSimulationFactory: self._building.level_of_detail.energy_systems = 2 self._building.level_of_detail.energy_systems = 2 + def _archetype14_15(self): + """ + Enrich the city by using the sizing and simulation model developed for archetype14 and archetype15 of + montreal_future_systems + """ + Archetype14_15(self._building, self._output_path).enrich_buildings() + self._building.level_of_detail.energy_systems = 2 + self._building.level_of_detail.energy_systems = 2 + def enrich(self): """ Enrich the city given to the class using the class given handler diff --git a/scripts/pv_sizing_and_simulation.py b/scripts/pv_sizing_and_simulation.py index 877a1499..6ef1a51d 100644 --- a/scripts/pv_sizing_and_simulation.py +++ b/scripts/pv_sizing_and_simulation.py @@ -49,18 +49,11 @@ class PVSizingSimulation(RadiationTilted): available_roof = self.available_space() inter_row_spacing = self.inter_row_spacing() self.number_of_panels(available_roof, inter_row_spacing) + self.building.roofs[0].installed_solar_collector_area = pv_module_area * self.total_number_of_panels system_efficiency = 0.2 - pv_hourly_production = [x * system_efficiency * self.total_number_of_panels * pv_module_area for x in radiation] + pv_hourly_production = [x * system_efficiency * self.total_number_of_panels * pv_module_area * + cte.WATTS_HOUR_TO_JULES for x in radiation] self.building.onsite_electrical_production[cte.HOUR] = pv_hourly_production self.building.onsite_electrical_production[cte.MONTH] = ( MonthlyValues.get_total_month(self.building.onsite_electrical_production[cte.HOUR])) - self.building.onsite_electrical_production[cte.YEAR] = [sum(self.building.onsite_electrical_production[cte.MONTH])] - - - - - - - - - + self.building.onsite_electrical_production[cte.YEAR] = [sum(self.building.onsite_electrical_production[cte.MONTH])] \ No newline at end of file diff --git a/scripts/random_assignation.py b/scripts/random_assignation.py index 44be581c..ac6eb454 100644 --- a/scripts/random_assignation.py +++ b/scripts/random_assignation.py @@ -29,8 +29,9 @@ residential_systems_percentage = {'system 1 gas': 100, 'system 8 electricity': 0} residential_new_systems_percentage = {'PV+ASHP+GasBoiler+TES': 0, - 'PV+4Pipe+DHW': 100, - 'Central Heating+Unitary Cooling+Unitary DHW': 0, + 'PV+4Pipe+DHW': 0, + 'Central Heating+Unitary Cooling+Unitary DHW': 50, + 'Central Heating+Unitary Cooling+Unitary DHW+PV': 50, 'PV+ASHP+ElectricBoiler+TES': 0, 'PV+GSHP+GasBoiler+TES': 0, 'PV+GSHP+ElectricBoiler+TES': 0, diff --git a/scripts/system_simulation_models/archetype13.py b/scripts/system_simulation_models/archetype13.py index 786115db..5219af2f 100644 --- a/scripts/system_simulation_models/archetype13.py +++ b/scripts/system_simulation_models/archetype13.py @@ -19,7 +19,8 @@ class Archetype13: self._domestic_hot_water_peak_load = building.domestic_hot_water_peak_load[cte.YEAR][0] self._hourly_heating_demand = [demand / cte.HOUR_TO_SECONDS for demand in building.heating_demand[cte.HOUR]] self._hourly_cooling_demand = [demand / cte.HOUR_TO_SECONDS for demand in building.cooling_demand[cte.HOUR]] - self._hourly_dhw_demand = building.domestic_hot_water_heat_demand[cte.HOUR] + self._hourly_dhw_demand = [demand / cte.WATTS_HOUR_TO_JULES for demand in + building.domestic_hot_water_heat_demand[cte.HOUR]] self._output_path = output_path self._t_out = building.external_temperature[cte.HOUR] self.results = {} @@ -30,11 +31,12 @@ class Archetype13: heat_pump = self._hvac_system.generation_systems[1] boiler = self._hvac_system.generation_systems[0] thermal_storage = boiler.energy_storage_systems[0] - heat_pump.nominal_heat_output = round(0.5 * self._heating_peak_load / 3600) - heat_pump.nominal_cooling_output = round(self._cooling_peak_load / 3600) - boiler.nominal_heat_output = round(0.5 * self._heating_peak_load / 3600) + heat_pump.nominal_heat_output = round(0.5 * self._heating_peak_load) + heat_pump.nominal_cooling_output = round(self._cooling_peak_load) + boiler.nominal_heat_output = round(0.5 * self._heating_peak_load) thermal_storage.volume = round( - (self._heating_peak_load * storage_factor) / (cte.WATER_HEAT_CAPACITY * cte.WATER_DENSITY * 25)) + (self._heating_peak_load * storage_factor * cte.WATTS_HOUR_TO_JULES) / + (cte.WATER_HEAT_CAPACITY * cte.WATER_DENSITY * 25)) return heat_pump, boiler, thermal_storage def dhw_sizing(self): diff --git a/scripts/system_simulation_models/archetypes14_15.py b/scripts/system_simulation_models/archetypes14_15.py new file mode 100644 index 00000000..e3cf52d1 --- /dev/null +++ b/scripts/system_simulation_models/archetypes14_15.py @@ -0,0 +1,402 @@ +import math +import hub.helpers.constants as cte +import csv +from hub.helpers.monthly_values import MonthlyValues + + +class Archetype14_15: + def __init__(self, building, output_path): + self._building = building + self._name = building.name + if 'PV' in building.energy_systems_archetype_name: + i = 1 + self._pv_system = building.energy_systems[0] + else: + i = 0 + self._dhw_system = building.energy_systems[i] + self._heating_system = building.energy_systems[i + 1] + self._cooling_system = building.energy_systems[i + 2] + self._dhw_peak_flow_rate = (building.thermal_zones_from_internal_zones[0].total_floor_area * + building.thermal_zones_from_internal_zones[0].domestic_hot_water.peak_flow * + cte.WATER_DENSITY) + self._heating_peak_load = building.heating_peak_load[cte.YEAR][0] + self._cooling_peak_load = building.cooling_peak_load[cte.YEAR][0] + self._domestic_hot_water_peak_load = building.domestic_hot_water_peak_load[cte.YEAR][0] + self._hourly_heating_demand = [demand / cte.WATTS_HOUR_TO_JULES for demand in building.heating_demand[cte.HOUR]] + self._hourly_cooling_demand = [demand / cte.WATTS_HOUR_TO_JULES for demand in building.cooling_demand[cte.HOUR]] + self._hourly_dhw_demand = [demand / cte.WATTS_HOUR_TO_JULES for demand in + building.domestic_hot_water_heat_demand[cte.HOUR]] + self._output_path = output_path + self._t_out = building.external_temperature[cte.HOUR] + self.results = {} + self.dt = 900 + + def heating_system_sizing(self): + storage_factor = 3 + heat_pump = self._heating_system.generation_systems[1] + heat_pump.source_temperature = self._t_out + boiler = self._heating_system.generation_systems[0] + thermal_storage = boiler.energy_storage_systems[0] + heat_pump.nominal_heat_output = round(0.5 * self._heating_peak_load) + boiler.nominal_heat_output = round(0.5 * self._heating_peak_load) + thermal_storage.volume = round( + (self._heating_peak_load * storage_factor * cte.WATTS_HOUR_TO_JULES) / + (cte.WATER_HEAT_CAPACITY * cte.WATER_DENSITY * 25)) + return heat_pump, boiler, thermal_storage + + def cooling_system_sizing(self): + heat_pump = self._cooling_system.generation_systems[0] + heat_pump.nominal_cooling_output = heat_pump.nominal_cooling_output = round(self._cooling_peak_load) + heat_pump.source_temperature = self._t_out + return heat_pump + + + def dhw_system_sizing(self): + storage_factor = 3 + dhw_hp = self._dhw_system.generation_systems[0] + dhw_hp.nominal_heat_output = round(0.7 * self._domestic_hot_water_peak_load) + dhw_hp.source_temperature = self._t_out + dhw_tes = dhw_hp.energy_storage_systems[0] + dhw_tes.volume = round( + (self._domestic_hot_water_peak_load * storage_factor * cte.WATTS_HOUR_TO_JULES) / + (cte.WATER_HEAT_CAPACITY * cte.WATER_DENSITY * 10)) + return dhw_hp, dhw_tes + + def heating_system_simulation(self): + hp, boiler, tes = self.heating_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_heating_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_tank", "t_ret", "m_ch", "m_dis", "q_hp", "q_boiler", "hp_cop", + "hp_electricity", "boiler_gas_consumption", "t_sup_boiler", "boiler_energy_consumption", + "heating_consumption"] + num_hours = len(demand) + variables = {name: [0] * num_hours for name in variable_names} + (t_sup_hp, t_tank, t_ret, m_ch, m_dis, q_hp, q_boiler, hp_cop, + hp_electricity, boiler_gas_consumption, t_sup_boiler, boiler_energy_consumption, heating_consumption) = \ + [variables[name] for name in variable_names] + t_tank[0] = 55 + hp_heating_cap = hp.nominal_heat_output + boiler_heating_cap = boiler.nominal_heat_output + hp_delta_t = 5 + boiler_efficiency = float(boiler.heat_efficiency) + 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) + # storage temperature prediction + for i in range(len(demand) - 1): + t_tank[i + 1] = (t_tank[i] + + (m_ch[i] * (t_sup_boiler[i] - t_tank[i]) + + (ua * (t_out[i] - t_tank[i])) / cte.WATER_HEAT_CAPACITY - + m_dis[i] * (t_tank[i] - t_ret[i])) * (self.dt / (cte.WATER_DENSITY * v))) + # hp operation + if t_tank[i + 1] < 40: + q_hp[i + 1] = hp_heating_cap + m_ch[i + 1] = q_hp[i + 1] / (cte.WATER_HEAT_CAPACITY * hp_delta_t) + t_sup_hp[i + 1] = (q_hp[i + 1] / (m_ch[i + 1] * cte.WATER_HEAT_CAPACITY)) + t_tank[i + 1] + elif 40 <= t_tank[i + 1] < 55 and q_hp[i] == 0: + q_hp[i + 1] = 0 + m_ch[i + 1] = 0 + t_sup_hp[i + 1] = t_tank[i + 1] + elif 40 <= t_tank[i + 1] < 55 and q_hp[i] > 0: + q_hp[i + 1] = hp_heating_cap + m_ch[i + 1] = q_hp[i + 1] / (cte.WATER_HEAT_CAPACITY * hp_delta_t) + t_sup_hp[i + 1] = (q_hp[i + 1] / (m_ch[i + 1] * cte.WATER_HEAT_CAPACITY)) + t_tank[i + 1] + else: + q_hp[i + 1], m_ch[i + 1], t_sup_hp[i + 1] = 0, 0, t_tank[i + 1] + t_sup_hp_fahrenheit = 1.8 * t_sup_hp[i + 1] + 32 + t_out_fahrenheit = 1.8 * t_out[i + 1] + 32 + if q_hp[i + 1] > 0: + hp_cop[i + 1] = (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 + 1] = q_hp[i + 1] / hp_cop[i + 1] + else: + hp_cop[i + 1] = 0 + hp_electricity[i + 1] = 0 + # boiler operation + if q_hp[i + 1] > 0: + if t_sup_hp[i + 1] < 45: + q_boiler[i + 1] = boiler_heating_cap + elif demand[i + 1] > 0.5 * self._heating_peak_load / self.dt: + q_boiler[i + 1] = 0.5 * boiler_heating_cap + boiler_energy_consumption[i + 1] = q_boiler[i + 1] / boiler_efficiency + boiler_gas_consumption[i + 1] = (q_boiler[i + 1] * self.dt) / (boiler_efficiency * cte.NATURAL_GAS_LHV) + t_sup_boiler[i + 1] = t_sup_hp[i + 1] + (q_boiler[i + 1] / (m_ch[i + 1] * cte.WATER_HEAT_CAPACITY)) + # storage discharging + if demand[i + 1] == 0: + m_dis[i + 1] = 0 + t_ret[i + 1] = t_tank[i + 1] + else: + if demand[i + 1] > 0.5 * self._heating_peak_load / cte.HOUR_TO_SECONDS: + factor = 8 + else: + factor = 4 + m_dis[i + 1] = self._heating_peak_load / (cte.WATER_HEAT_CAPACITY * factor * cte.HOUR_TO_SECONDS) + t_ret[i + 1] = t_tank[i + 1] - demand[i + 1] / (m_dis[i + 1] * cte.WATER_HEAT_CAPACITY) + tes.temperature = [] + hp_electricity_j = [(x * cte.WATTS_HOUR_TO_JULES) / number_of_ts for x in hp_electricity] + boiler_consumption_j = [(x * cte.WATTS_HOUR_TO_JULES) / number_of_ts for x in boiler_energy_consumption] + hp_hourly = [] + boiler_hourly = [] + boiler_sum = 0 + hp_sum = 0 + for i in range(1, len(demand)): + 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())) diff --git a/tests/test_systems_catalog.py b/tests/test_systems_catalog.py index 234f54d6..612a8fe6 100644 --- a/tests/test_systems_catalog.py +++ b/tests/test_systems_catalog.py @@ -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')