monthly_energy_balance/main.py
2021-03-02 18:58:06 -05:00

175 lines
7.7 KiB
Python

"""
Monthly energy balance main
SPDX - License - Identifier: LGPL - 3.0 - or -later
Copyright © 2020 Project Author Pilar Monsalvete pilar_monsalvete@yahoo.es
"""
import sys
from pathlib import Path
from argparse import ArgumentParser
import ast
import pandas as pd
from helpers import monthly_values as mv
from populate import Populate
from insel.insel import Insel
from insel.templates.monthly_energy_balance import MonthlyEnergyBalance as templates
from simplified_radiosity_algorithm.simplified_radiosity_algorithm import SimplifiedRadiosityAlgorithm
from imports.geometry_factory import GeometryFactory
from imports.weather_factory import WeatherFactory
from city_model_structure.city import City
import datetime
parser = ArgumentParser(description='Monthly energy balance workflow v0.1.')
required = parser.add_argument_group('required arguments')
parser.add_argument('--geometry_type', '-g', help='Geometry type {citygml}', default='citygml')
required.add_argument('--input_geometry_file', '-i', help='Input geometry file', required=True)
parser.add_argument('--use_pickle_file', '-p', help='Use pickle file instead of importing geometry file', default=False,
required=True)
parser.add_argument('--populated_step_in_pickle', '-ps', help='Physics and usage parameters already in pickle file',
default=False, required=True)
parser.add_argument('--weather_step_in_pickle', '-ws', help='Weather parameters already in pickle file',
default=False, required=True)
parser.add_argument('--use_cached_sra_file', '-u', help='Use sra files from cache, instead of freshly calculated sra '
'files', default=False)
required.add_argument('--project_folder', '-f', help='Project folder', required=True)
required.add_argument('--cli_weather_file', '-c', help='weather cli file', required=True)
required.add_argument('--city_name', '-n', help='city name for dat file', required=True)
try:
args = parser.parse_args()
except SystemExit:
sys.exit()
keep_files = True
print('begin_time', datetime.datetime.now())
# Step 1: Initialize the city model
pickle_file = ''
if ast.literal_eval(args.use_pickle_file):
pickle_file = Path(args.input_geometry_file).resolve()
city = City.load(pickle_file)
else:
file = Path(args.input_geometry_file).resolve()
pickle_file = Path(str(file).replace('.gml', '.pickle'))
city = GeometryFactory(args.geometry_type, file).city
city.save(pickle_file)
# Step 2: Populate city adding thermal- and usage-related parameters
populated_step_in_pickle = ast.literal_eval(args.populated_step_in_pickle)
if populated_step_in_pickle:
populated_city = city
for building in populated_city.buildings:
for usage_zone in building.usage_zones:
usage_zone.heating_setpoint = 20
usage_zone.heating_setback = 17
else:
populated_city = Populate(city).populated_city
pickle_file = Path(str(pickle_file).replace('.pickle', '_populated.pickle'))
populated_city.save(pickle_file)
if populated_city.buildings is None:
print('No building to be calculated')
sys.exit()
print('populating_time', datetime.datetime.now())
# Step 3: Populate city adding climate-related parameters
weather_step_in_pickle = ast.literal_eval(args.weather_step_in_pickle)
if not weather_step_in_pickle:
city_name = args.city_name
WeatherFactory('dat', populated_city, city_name)
for building in populated_city.buildings:
if 'hour' not in building.external_temperature:
print('No external temperature found')
sys.exit()
if 'month' not in building.external_temperature:
building.external_temperature['month'] = mv.MonthlyValues().\
get_mean_values(building.external_temperature['hour'][['inseldb']])
max_buildings_handled_by_sra = 500
sra_file_name = 'SRA'
sra = SimplifiedRadiosityAlgorithm(Path(args.project_folder).resolve(), sra_file_name,
Path(args.cli_weather_file).resolve(),
city.city_objects, lower_corner=city.lower_corner)
if ast.literal_eval(args.use_cached_sra_file):
sra.results()
sra.set_irradiance_surfaces(populated_city)
else:
total_number_of_buildings = len(city.buildings)
if total_number_of_buildings > max_buildings_handled_by_sra:
radius = 100
for building in city.buildings:
new_city = city.region(building.location, radius)
sra_file_name = 'SRA'
sra_new = SimplifiedRadiosityAlgorithm(Path(args.project_folder).resolve(), sra_file_name,
Path(args.cli_weather_file).resolve(),
new_city.city_objects, lower_corner=new_city.lower_corner)
sra_new.call_sra(keep_files=True)
sra_new.set_irradiance_surfaces(city, building_name=building.name)
else:
sra.call_sra(keep_files=keep_files)
sra.set_irradiance_surfaces(populated_city)
pickle_file = Path(str(pickle_file).replace('.pickle', '_weather.pickle'))
populated_city.save(pickle_file)
print('begin_insel_time', datetime.datetime.now())
# Step 4: Demand calculation (one model per building)
print_results = None
# todo: city.name needs location and so, internet connection
# file = 'city name: ' + city.name + '\n'
file = 'city name: Kelowna\n'
i = 0
for building in populated_city.buildings:
if building.name != 'BLD122177':
print(building.name)
# todo: default values to be defined at each specific workflow!
building.heated = True
building.cooled = False
building.attic_heated = 2
building.basement_heated = 1
for thermal_boundary in building.thermal_zones[0].bounded:
thermal_boundary.hi = 10
thermal_boundary.he = 25
for thermal_opening in thermal_boundary.thermal_openings:
thermal_opening.hi = 10
thermal_opening.he = 25
building.thermal_zones[0].indirectly_heated_area_ratio = 0.25
building.thermal_zones[0].additional_thermal_bridge_u_value = 0.05
building.usage_zones[0].mechanical_air_change = 0.35
building.thermal_zones[0].infiltration_rate_system_on = 0
full_path_out = Path(args.project_folder + '/outputs/' + building.name + '_insel.out').resolve()
full_path_out.parent.mkdir(parents=True, exist_ok=True)
insel_file_name = building.name + '.insel'
try:
content = templates.generate_meb_template(building, full_path_out)
insel = Insel(Path(args.project_folder).resolve(), insel_file_name, content, mode=2, keep_files=keep_files).run()
building.heating['month'], building.cooling['month'] = templates.demand(full_path_out)
new_building = building.heating['month'].rename(columns={'INSEL': building.name})
if print_results is None:
print_results = new_building
else:
print_results = pd.concat([print_results, new_building], axis='columns')
file += '\n'
file += 'name: ' + building.name + '\n'
file += 'year of construction: ' + building.year_of_construction + '\n'
file += 'function: ' + building.function + '\n'
file += 'floor area: ' + str(building.thermal_zones[0].floor_area) + '\n'
file += 'storeys: ' + str(building.storeys_above_ground) + '\n'
file += 'heated_volume: ' + str(building.heated_volume) + '\n'
file += 'volume: ' + str(building.volume) + '\n'
except ValueError:
print(sys.exc_info()[1])
print('Building ' + building.name + ' could not be processed')
continue
i += 1
full_path_results = Path(args.project_folder + '/outputs/heating_demand.csv').resolve()
print_results.to_csv(full_path_results)
full_path_metadata = Path(args.project_folder + '/outputs/metadata.csv').resolve()
with open(full_path_metadata, 'w') as metadata_file:
metadata_file.write(file)
print('end_time', datetime.datetime.now())