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feat: stratified model for tes added, all the demand and consumptions are converted to J, cold water temperature fixed #9

Merged
s_ranjbar merged 1 commits from stratified_tes into main 2024-06-13 15:43:47 -04:00
Conversation 0 Commits 1 Files Changed 9 +563 -80
9 changed files with 563 additions and 80 deletions
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4
hub/city_model_structure/building.py
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@ -896,13 +896,13 @@ class Building(CityObject):
for energy_system in energy_systems:
if cte.COOLING in energy_system.demand_types and cte.COOLING not in fuel_breakdown[key]:
for generation_system in energy_system.generation_systems:
fuel_breakdown[generation_system.fuel_type][cte.COOLING] = self.cooling_consumption[cte.YEAR][0] / 3600
fuel_breakdown[generation_system.fuel_type][cte.COOLING] = self.cooling_consumption[cte.YEAR][0]
for fuel in heating_fuels:
if cte.HEATING not in fuel_breakdown[fuel]:
for energy_system in energy_systems:
if cte.HEATING in energy_system.demand_types:
for generation_system in energy_system.generation_systems:
fuel_breakdown[generation_system.fuel_type][cte.HEATING] = self.heating_consumption[cte.YEAR][0] / 3600
fuel_breakdown[generation_system.fuel_type][cte.HEATING] = self.heating_consumption[cte.YEAR][0]
for fuel in dhw_fuels:
if cte.DOMESTIC_HOT_WATER not in fuel_breakdown[fuel]:
for energy_system in energy_systems:

1
hub/helpers/constants.py
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@ -10,6 +10,7 @@ Project Coder Pilar Monsalvete Alvarez de Uribarri pilar.monsalvete@concordia.ca
KELVIN = 273.15
WATER_DENSITY = 1000 # kg/m3
WATER_HEAT_CAPACITY = 4182 # J/kgK
WATER_THERMAL_CONDUCTIVITY = 0.65 # W/mK
NATURAL_GAS_LHV = 36.6e6 # J/m3
AIR_DENSITY = 1.293 # kg/m3
AIR_HEAT_CAPACITY = 1005.2 # J/kgK

9
hub/imports/results/ep_multiple_buildings.py
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@ -60,9 +60,12 @@ class EnergyPlusMultipleBuildings:
for building in self._city.buildings:
building.heating_demand[cte.HOUR] = building_energy_demands[f'Building {building.name} Heating Demand (J)']
building.cooling_demand[cte.HOUR] = building_energy_demands[f'Building {building.name} Cooling Demand (J)']
building.domestic_hot_water_heat_demand[cte.HOUR] = building_energy_demands[f'Building {building.name} DHW Demand (W)']
building.appliances_electrical_demand[cte.HOUR] = building_energy_demands[f'Building {building.name} Appliances (W)']
building.lighting_electrical_demand[cte.HOUR] = building_energy_demands[f'Building {building.name} Lighting (W)']
building.domestic_hot_water_heat_demand[cte.HOUR] = \
[x * cte.WATTS_HOUR_TO_JULES for x in building_energy_demands[f'Building {building.name} DHW Demand (W)']]
building.appliances_electrical_demand[cte.HOUR] = \
[x * cte.WATTS_HOUR_TO_JULES for x in building_energy_demands[f'Building {building.name} Appliances (W)']]
building.lighting_electrical_demand[cte.HOUR] = \
[x * cte.WATTS_HOUR_TO_JULES for x in building_energy_demands[f'Building {building.name} Lighting (W)']]
building.heating_demand[cte.MONTH] = MonthlyValues.get_total_month(building.heating_demand[cte.HOUR])
building.cooling_demand[cte.MONTH] = MonthlyValues.get_total_month(building.cooling_demand[cte.HOUR])
building.domestic_hot_water_heat_demand[cte.MONTH] = (

4
hub/imports/weather/epw_weather_parameters.py
View File

@ -126,10 +126,10 @@ class EpwWeatherParameters:
for building in self._city.buildings:
building.external_temperature[cte.MONTH] = \
MonthlyValues().get_mean_values(building.external_temperature[cte.HOUR])
building.external_temperature[cte.YEAR] = [sum(building.external_temperature[cte.HOUR]) / 9870]
building.external_temperature[cte.YEAR] = [sum(building.external_temperature[cte.HOUR]) / 8760]
building.cold_water_temperature[cte.MONTH] = \
MonthlyValues().get_mean_values(building.cold_water_temperature[cte.HOUR])
building.cold_water_temperature[cte.YEAR] = [sum(building.cold_water_temperature[cte.HOUR]) / 9870]
building.cold_water_temperature[cte.YEAR] = [sum(building.cold_water_temperature[cte.HOUR]) / 8760]
# If the usage has already being imported, the domestic hot water missing values must be calculated here that
# the cold water temperature is finally known

32
hub/imports/weather/helpers/weather.py
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@ -8,7 +8,7 @@ Project Coder Pilar Monsalvete Alvarez de Uribarri pilar.monsalvete@concordia.ca
import logging
import math
import hub.helpers.constants as cte
from datetime import datetime, timedelta
class Weather:
"""
@ -55,25 +55,19 @@ class Weather:
# and Craig Christensen, National Renewable Energy Laboratory
# ambient temperatures( in °C)
# cold water temperatures( in °C)
ambient_temperature_fahrenheit = []
average_temperature = 0
maximum_temperature = -1000
minimum_temperature = 1000
for temperature in ambient_temperature:
value = temperature * 9 / 5 + 32
ambient_temperature_fahrenheit.append(value)
average_temperature += value / 8760
if value > maximum_temperature:
maximum_temperature = value
if value < minimum_temperature:
minimum_temperature = value
delta_temperature = maximum_temperature - minimum_temperature
ratio = 0.4 + 0.01 * (average_temperature - 44)
lag = 35 - 1 * (average_temperature - 44)
t_out_fahrenheit = [1.8 * t_out + 32 for t_out in ambient_temperature]
t_out_average = sum(t_out_fahrenheit) / len(t_out_fahrenheit)
max_difference = max(t_out_fahrenheit) - min(t_out_fahrenheit)
ratio = 0.4 + 0.01 * (t_out_average - 44)
lag = 35 - (t_out_average - 35)
number_of_day = [a for a in range(1, 366)]
day_of_year = [day for day in number_of_day for _ in range(24)]
cold_temperature_fahrenheit = []
cold_temperature = []
for temperature in ambient_temperature_fahrenheit:
radians = (0.986 * (temperature-15-lag) - 90) * math.pi / 180
cold_temperature.append((average_temperature + 6 + ratio * (delta_temperature/2) * math.sin(radians) - 32) * 5/9)
for i in range(len(ambient_temperature)):
cold_temperature_fahrenheit.append(t_out_average + 6 + ratio * (max_difference / 2) *
math.sin(math.radians(0.986 * (day_of_year[i] - 15 - lag) - 90)))
cold_temperature.append((cold_temperature_fahrenheit[i] - 32) / 1.8)
return cold_temperature
def epw_file(self, region_code):

45
main.py
View File

@ -0,0 +1,45 @@
from scripts.geojson_creator import process_geojson
from pathlib import Path
import subprocess
from scripts.ep_run_enrich import energy_plus_workflow
from hub.imports.geometry_factory import GeometryFactory
from hub.helpers.dictionaries import Dictionaries
from hub.imports.construction_factory import ConstructionFactory
from hub.imports.usage_factory import UsageFactory
from hub.imports.weather_factory import WeatherFactory
from hub.imports.results_factory import ResultFactory
from scripts.energy_system_analysis_report import EnergySystemAnalysisReport
from scripts import random_assignation
from hub.imports.energy_systems_factory import EnergySystemsFactory
from scripts.energy_system_sizing import SystemSizing
from scripts.energy_system_retrofit_results import system_results, new_system_results
from scripts.energy_system_sizing_and_simulation_factory import EnergySystemsSimulationFactory
from scripts.costs.cost import Cost
from scripts.costs.constants import SKIN_RETROFIT_AND_SYSTEM_RETROFIT_AND_PV, SYSTEM_RETROFIT_AND_PV
import hub.helpers.constants as cte
from hub.exports.exports_factory import ExportsFactory
# Specify the GeoJSON file path
geojson_file = process_geojson(x=-73.5681295982132, y=45.49218262677643, diff=0.0001)
file_path = (Path(__file__).parent / 'input_files' / 'output_buildings.geojson')
# Specify the output path for the PDF file
output_path = (Path(__file__).parent / 'out_files').resolve()
# Create city object from GeoJSON file
city = GeometryFactory('geojson',
path=file_path,
height_field='height',
year_of_construction_field='year_of_construction',
function_field='function',
function_to_hub=Dictionaries().montreal_function_to_hub_function).city
# Enrich city data
ConstructionFactory('nrcan', city).enrich()
UsageFactory('nrcan', city).enrich()
WeatherFactory('epw', city).enrich()
energy_plus_workflow(city)
random_assignation.call_random(city.buildings, random_assignation.residential_new_systems_percentage)
EnergySystemsFactory('montreal_future', city).enrich()
for building in city.buildings:
EnergySystemsSimulationFactory('archetype13', building=building, output_path=output_path).enrich()
print('test')

1
scripts/energy_system_sizing_and_simulation_factory.py
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@ -6,6 +6,7 @@ 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

155
scripts/system_simulation_models/archetype13.py
View File

@ -2,6 +2,8 @@ import math
import hub.helpers.constants as cte
import csv
from hub.helpers.monthly_values import MonthlyValues
class Archetype13:
def __init__(self, building, output_path):
self._building = building
@ -15,12 +17,13 @@ class Archetype13:
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 = [0] + [demand / 3600 for demand in building.heating_demand[cte.HOUR]]
self._hourly_cooling_demand = [demand / 3600 for demand in building.cooling_demand[cte.HOUR]]
self._hourly_dhw_demand = [0] + building.domestic_hot_water_heat_demand[cte.HOUR]
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._output_path = output_path
self._t_out = [0] + building.external_temperature[cte.HOUR]
self._t_out = building.external_temperature[cte.HOUR]
self.results = {}
self.dt = 900
def hvac_sizing(self):
storage_factor = 3
@ -47,7 +50,9 @@ class Archetype13:
def heating_system_simulation(self):
hp, boiler, tes = self.hvac_sizing()
cop_curve_coefficients = [float(coefficient) for coefficient in hp.heat_efficiency_curve.coefficients]
demand = self._hourly_heating_demand
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",
@ -56,9 +61,8 @@ class Archetype13:
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]
[variables[name] for name in variable_names]
t_tank[0] = 55
dt = 3600
hp_heating_cap = hp.nominal_heat_output
boiler_heating_cap = boiler.nominal_heat_output
hp_delta_t = 5
@ -75,8 +79,8 @@ class Archetype13:
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 * (self._t_out[i] - t_tank[i])) / cte.WATER_HEAT_CAPACITY -
m_dis[i] * (t_tank[i] - t_ret[i])) * (dt / (cte.WATER_DENSITY * v)))
(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
@ -93,7 +97,7 @@ class Archetype13:
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 * self._t_out[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 +
@ -109,39 +113,54 @@ class Archetype13:
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 / dt:
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] * dt) / (boiler_efficiency * cte.NATURAL_GAS_LHV)
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 / dt:
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 * dt)
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_electricity
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_energy_consumption
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])]
tes.temperature = t_tank
self.results['Heating Demand (W)'] = demand
self.results['HP Heat Output (W)'] = q_hp
self.results['HP Source Temperature'] = self._t_out
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
@ -152,42 +171,47 @@ class Archetype13:
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_electricity, boiler_energy_consumption
return hp_hourly, boiler_hourly
def cooling_system_simulation(self):
hp = self.hvac_sizing()[0]
eer_curve_coefficients = [float(coefficient) for coefficient in hp.cooling_efficiency_curve.coefficients]
cooling_efficiency = float(hp.cooling_efficiency)
demand = self._hourly_cooling_demand
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
dt = 3600
for i in range(len(demand) - 1):
for i in range(1, len(demand)):
if demand[i] > 0:
m[i] = self._cooling_peak_load / (cte.WATER_HEAT_CAPACITY * 5 * dt)
if t_ret[i] > 13:
if demand[i] < 0.25 * self._cooling_peak_load / dt:
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 / dt:
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] - q_hp[i] / (m[i] * cte.WATER_HEAT_CAPACITY)
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]
t_ret[i + 1] = t_sup_hp[i] + demand[i] / (m[i] * cte.WATER_HEAT_CAPACITY)
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]
t_ret[i + 1] = t_ret[i]
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 * self._t_out[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 +
@ -195,12 +219,20 @@ class Archetype13:
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] / cooling_efficiency
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_electricity
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] = [
@ -212,12 +244,14 @@ class Archetype13:
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_electricity
return hp_hourly
def dhw_system_simulation(self):
hp, tes = self.dhw_sizing()
cop_curve_coefficients = [float(coefficient) for coefficient in hp.heat_efficiency_curve.coefficients]
demand = self._hourly_dhw_demand
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)
@ -226,7 +260,7 @@ class Archetype13:
[variables[name] for name in variable_names]
t_tank[0] = 70
v_dhw[0] = tes.volume
dt = 3600
hp_heating_cap = hp.nominal_heat_output
hp_delta_t = 8
v, h = float(tes.volume), float(tes.height)
@ -239,26 +273,24 @@ class Archetype13:
ua = u_tot * (2 * a_top + a_side)
freshwater_temperature = 18
for i in range(len(demand) - 1):
delta_t_demand = demand[i] * (dt / (cte.WATER_DENSITY * cte.WATER_HEAT_CAPACITY * v))
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] * (dt / (cte.WATER_DENSITY * cte.WATER_HEAT_CAPACITY * v))
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) * (dt / (v * cte.WATER_DENSITY))
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) / dt
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)
elif t_tank[i] < 65:
q_coil[i] = float(tes.heating_coil_capacity)
delta_t_coil = q_coil[i] * (dt / (cte.WATER_DENSITY * cte.WATER_HEAT_CAPACITY * v))
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)
@ -267,7 +299,7 @@ class Archetype13:
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 * self._t_out[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 +
@ -275,32 +307,47 @@ class Archetype13:
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] / 3.5
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_electricity
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] = q_coil
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'] = self._t_out
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
@ -309,7 +356,7 @@ class Archetype13:
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_electricity, q_coil
return hp_hourly, coil_hourly
def enrich_buildings(self):
hp_heating, boiler_consumption = self.heating_system_simulation()
@ -320,11 +367,11 @@ class Archetype13:
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.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.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]))

392
scripts/system_simulation_models/archetype13_stratified_tes.py Normal file
View File

@ -0,0 +1,392 @@
import math
import hub.helpers.constants as cte
import csv
from hub.helpers.monthly_values import MonthlyValues
import numpy as np
class Archetype13Stratified:
def __init__(self, building, output_path):
self._building = building
self._name = building.name
self._pv_system = building.energy_systems[0]
self._hvac_system = building.energy_systems[1]
self._dhw_system = building.energy_systems[-1]
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 / 3600 for demand in building.heating_demand[cte.HOUR]]
self._hourly_cooling_demand = [demand / 3600 for demand in building.cooling_demand[cte.HOUR]]
self._hourly_dhw_demand = [0] + building.domestic_hot_water_heat_demand[cte.HOUR]
self._output_path = output_path
self._t_out = building.external_temperature[cte.HOUR]
self.results = {}
def hvac_sizing(self):
storage_factor = 3
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)
thermal_storage.volume = round(
(self._heating_peak_load * storage_factor) / (cte.WATER_HEAT_CAPACITY * cte.WATER_DENSITY * 25))
return heat_pump, boiler, thermal_storage
def dhw_sizing(self):
storage_factor = 3
dhw_hp = self._dhw_system.generation_systems[0]
dhw_hp.nominal_heat_output = 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 * 3600) / (cte.WATER_HEAT_CAPACITY * cte.WATER_DENSITY * 10))
return dhw_hp, dhw_tes
def heating_system_simulation_stratified(self):
hp, boiler, tes = self.hvac_sizing()
cop_curve_coefficients = [float(coefficient) for coefficient in hp.heat_efficiency_curve.coefficients]
demand = [0] + [x for x in self._hourly_heating_demand for _ in range(12)]
hp.source_temperature = self._t_out
t_out = [0] + [x for x in self._t_out for _ in range(12)]
variable_names = ["t_sup_hp", "t1", "t2", "t3", "t4", "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, t1, t2, t3, t4, 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
t1[0] = 55
t2[0] = 55
t3[0] = 55
t4[0] = 55
dt = 300
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) / 4, float(tes.height) / 4
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_side = u_tot * a_side
ua_top_bottom = u_tot * (a_top + a_side)
# storage temperature prediction
for i in range(len(demand) - 1):
t1[i + 1] = t1[i] + ((m_ch[i] * (t_sup_boiler[i] - t1[i])) + (
np.heaviside((m_dis[i] - m_ch[i]), 0) * (m_ch[i] - m_dis[i]) * (t1[i] - t2[i])) + (
ua_top_bottom * (t_out[i] - t1[i])) / cte.WATER_HEAT_CAPACITY - cte.WATER_THERMAL_CONDUCTIVITY * (a_top * (t1[i] - t2[i])) / (
cte.WATER_HEAT_CAPACITY * h)) * (dt / (cte.WATER_DENSITY * v))
t2[i + 1] = t2[i] + ((np.heaviside((m_dis[i] - m_ch[i]), 0) * (m_ch[i] - m_dis[i]) * (t2[i] - t3[i])) + (
ua_side * (t_out[i] - t2[i])) / cte.WATER_HEAT_CAPACITY - (cte.WATER_THERMAL_CONDUCTIVITY * (a_top * (t2[i] - t1[i])) / (cte.WATER_HEAT_CAPACITY * h)) - (
cte.WATER_THERMAL_CONDUCTIVITY * (a_top * (t2[i] - t3[i])) / (cte.WATER_HEAT_CAPACITY * h)) + (
np.heaviside((m_ch[i] - m_dis[i]), 0) * (m_ch[i] - m_dis[i]) * (
t1[i] - t2[i]))) * (dt / (cte.WATER_DENSITY * v))
t3[i + 1] = t3[i] + ((np.heaviside((m_dis[i] - m_ch[i]), 0) * (m_ch[i] - m_dis[i]) * (t3[i] - t4[i])) + (
ua_side * (t_out[i] - t3[i])) / cte.WATER_HEAT_CAPACITY - (cte.WATER_THERMAL_CONDUCTIVITY * (a_top * (t3[i] - t2[i])) / (cte.WATER_HEAT_CAPACITY * h)) - (
cte.WATER_THERMAL_CONDUCTIVITY * (a_top * (t3[i] - t4[i])) / (cte.WATER_HEAT_CAPACITY * h)) + (
np.heaviside((m_ch[i] - m_dis[i]), 0) * (m_ch[i] - m_dis[i]) * (
t2[i] - t3[i]))) * (dt / (cte.WATER_DENSITY * v))
t4[i + 1] = t4[i] + (np.heaviside((m_ch[i] - m_dis[i]), 0) * ((m_ch[i] - m_dis[i]) * (t3[i] - t4[i])) + (
ua_top_bottom * (t_out[i] - t4[-1])) / cte.WATER_HEAT_CAPACITY - m_dis[i] * ((t4[i] - t_ret[i])) - (
cte.WATER_THERMAL_CONDUCTIVITY * (a_top * (t4[i] - t3[i])) / (cte.WATER_HEAT_CAPACITY * h))) * (dt / (cte.WATER_DENSITY * v))
# hp operation
if t1[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)) + t4[i + 1]
elif 40 <= t1[i + 1] < 55 and q_hp[i] == 0:
q_hp[i + 1] = 0
m_ch[i + 1] = 0
t_sup_hp[i + 1] = t4[i + 1]
elif 40 <= t1[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)) + t4[i + 1]
else:
q_hp[i + 1], m_ch[i + 1], t_sup_hp[i + 1] = 0, 0, t4[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 / 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] * 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] = t1[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] = t1[i + 1] - demand[i + 1] / (m_dis[i + 1] * cte.WATER_HEAT_CAPACITY)
hp_electricity_wh = [x / 12 for x in hp_electricity]
boiler_consumption_wh = [x / 12 for x in boiler_energy_consumption]
hp_hourly = []
boiler_hourly = []
tes.temperature = {}
tes.temperature['layer_1'] = []
tes.temperature['layer_2'] = []
tes.temperature['layer_3'] = []
tes.temperature['layer_4'] = []
for i in range(1, len(demand), 12):
tes.temperature['layer_1'].append(t1[i])
tes.temperature['layer_2'].append(t2[i])
tes.temperature['layer_3'].append(t3[i])
tes.temperature['layer_4'].append(t4[i])
demand_modified = demand[1:]
hp_hourly.append(hp_electricity[1])
boiler_hourly.append(boiler_energy_consumption[1])
boiler_sum = 0
hp_sum = 0
for i in range(1, len(demand_modified) + 1):
hp_sum += hp_electricity_wh[i]
boiler_sum += boiler_consumption_wh[i]
if i % 12 == 0:
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 Layer 1 Temperature'] = t1
self.results['TES Layer 2 Temperature'] = t2
self.results['TES Layer 3 Temperature'] = t3
self.results['TES Layer 4 Temperature'] = t4
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_electricity, boiler_energy_consumption
def cooling_system_simulation(self):
hp = self.hvac_sizing()[0]
eer_curve_coefficients = [float(coefficient) for coefficient in hp.cooling_efficiency_curve.coefficients]
cooling_efficiency = float(hp.cooling_efficiency)
demand = self._hourly_cooling_demand
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
dt = 3600
for i in range(len(demand) - 1):
if demand[i] > 0:
m[i] = self._cooling_peak_load / (cte.WATER_HEAT_CAPACITY * 5 * dt)
if t_ret[i] > 13:
if demand[i] < 0.25 * self._cooling_peak_load / dt:
q_hp[i] = 0.25 * hp.nominal_cooling_output
elif demand[i] < 0.5 * self._cooling_peak_load / dt:
q_hp[i] = 0.5 * hp.nominal_cooling_output
else:
q_hp[i] = hp.nominal_cooling_output
t_sup_hp[i] = t_ret[i] - q_hp[i] / (m[i] * cte.WATER_HEAT_CAPACITY)
else:
q_hp[i] = 0
t_sup_hp[i] = t_ret[i]
t_ret[i + 1] = 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]
t_ret[i + 1] = t_ret[i]
t_sup_hp_fahrenheit = 1.8 * t_sup_hp[i] + 32
t_out_fahrenheit = 1.8 * self._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] / cooling_efficiency
else:
hp_eer[i] = 0
hp_electricity[i] = 0
hp.energy_consumption[cte.COOLING] = {}
hp.energy_consumption[cte.COOLING][cte.HOUR] = hp_electricity
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_electricity
def dhw_system_simulation(self):
hp, tes = self.dhw_sizing()
cop_curve_coefficients = [float(coefficient) for coefficient in hp.heat_efficiency_curve.coefficients]
demand = self._hourly_dhw_demand
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
dt = 3600
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] * (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] * (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) * (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) / dt
if power <= float(tes.heating_coil_capacity):
q_coil[i] = power
else:
q_coil[i] = float(tes.heating_coil_capacity)
elif t_tank[i] < 65:
q_coil[i] = float(tes.heating_coil_capacity)
delta_t_coil = q_coil[i] * (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 * self._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] / 3.5
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)
hp.energy_consumption[cte.DOMESTIC_HOT_WATER] = {}
hp.energy_consumption[cte.DOMESTIC_HOT_WATER][cte.HOUR] = hp_electricity
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] = q_coil
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'] = self._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_electricity, q_coil
def enrich_buildings(self):
hp_heating, boiler_consumption = self.heating_system_simulation_stratified()
# 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()))