workflow v1.0
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Pilar
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README.md
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README.md
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@ -1,12 +1,16 @@
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# MonthlyEnergyBalance
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This tool calculates the monthly energy balance for a given region.
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This tool calculates the monthly energy balance for each building in a given region.
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The current version can only use NYC CityGml at LOD1, but we will increase the regions and the level of detail in future releases.
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The following assumptions are taken:
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- No building in the region have attics
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- All buildings have basement but those are not heated
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- The construction details come from nrel
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- The usage details come from comnet
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#### Dependencies
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#### dependencies
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You will need to install the following dependencies in your computer order to run the software; please take a look at the [install process](#installation) for your system-specific details
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You will need to install the following dependencies in your computer in order to run the software; please take a look at the [install process](#installation) for your system-specific details
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##### External software
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+ INSEL 8 (https://insel4d.ca/en/download.html)
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@ -14,29 +18,6 @@ You will need to install the following dependencies in your computer order to ru
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After installing these tools you should include their paths in Path.
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##### Python libraries
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+ Shapely (1.7.0)
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+ cycler (0.10.0)
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+ geographiclib (1.50)
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+ geopy (1.21.0)
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+ kiwisolver (1.2.0)
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+ matplotlib (3.2.1)
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+ numpy (1.18.3)
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+ numpy-stl (2.11.2)
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+ pandas (1.0.3)
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+ pip (20.0.2)
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+ pyny3d (0.2)
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+ pyparsing (2.4.7)
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+ pyproj (2.6.0)
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+ python-dateutil (2.8.1)
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+ python-utils (2.4.0)
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+ pytz (2019.3)
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+ scipy (1.4.1)
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+ setuptools (46.1.3)
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+ six (1.14.0)
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+ stl (0.0.3)
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+ xmltodict (0.12.0)
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## installation
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##### Linux / Mac
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@ -81,5 +62,3 @@ $ python main.py
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```
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c:\> python.exe main.py
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```
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@ -1,60 +1,18 @@
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import os
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from pathlib import Path
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from abc import ABC
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class Insel:
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def __init__(self, path, name, new_content="", mode=1, keep_files=False):
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class Insel(ABC):
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def __init__(self, path):
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self._path = path
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self._name = name
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self._full_path = None
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self._content = None
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self._results = None
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self._keep_files = keep_files
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self.add_content(new_content, mode)
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self.save()
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def save(self):
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with open(self.full_path, 'w') as insel_file:
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insel_file.write(self.content)
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return
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@property
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def full_path(self):
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if self._full_path is None:
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self._full_path = (Path(self._path) / 'tmp' / self._name).resolve()
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return self._full_path
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@property
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def content(self):
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if self._content is None:
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if os.path.exists(self.full_path):
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with open(self.full_path, 'r') as insel_file:
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self._content = insel_file.read()
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else:
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self._content = ''
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return self._content
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# todo: create method
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def add_block(self):
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raise Exception('Not implemented')
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def add_content(self, new_content, mode):
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# mode = 1: keep old content
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if mode == 1:
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self._content = self.content + '\r\n' + new_content
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# mode = 2: over-write
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elif mode == 2:
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self._content = new_content
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else:
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raise Exception('Add content mode not supported')
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return
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def run(self):
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output = os.system('insel ' + str(self.full_path))
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# todo: catch errors from INSEL
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if not self._keep_files:
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os.remove(self.full_path)
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paths = sorted(Path(self._path).glob('*.insel'))
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for file in paths:
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os.system('insel ' + str(file))
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@property
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def results(self):
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raise Exception('Not implemented')
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raise NotImplementedError
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@ -7,26 +7,23 @@ Copyright © 2020 Project Author Pilar Monsalvete Alvarez de Uribarri pilar.mons
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from pathlib import Path
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import pandas as pd
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import sys
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from insel.templates.monthly_energy_balance import MonthlyEnergyBalance as templates
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import csv
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from insel.insel import Insel
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class MonthlyDemandCalculation:
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class MonthlyDemandCalculation(Insel):
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def __init__(self, city, main_path, weather_format):
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super().__init__(main_path)
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self._city = city
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self._main_path = main_path
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self._weather_format = weather_format
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def monthly_demand(self):
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def results(self):
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for building in self._city.buildings:
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full_path_out = Path(self._main_path + '/outputs/' + building.name + '_insel.out').resolve()
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file_name = building.name + '.out'
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full_path_out = Path(self._path / file_name).resolve()
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full_path_out.parent.mkdir(parents=True, exist_ok=True)
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insel_file_name = building.name + '.insel'
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try:
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content = templates.generate_meb_template(building, full_path_out, self._weather_format)
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insel = Insel(Path(self._main_path).resolve(), insel_file_name, content, mode=2, keep_files=True).run()
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building.heating['month'], building.cooling['month'] = templates.demand(full_path_out)
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building.heating['month'], building.cooling['month'] = self._demand(full_path_out)
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heating_year = 0
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for value in building.heating['month']['INSEL']:
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if value == 'NaN':
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@ -47,3 +44,21 @@ class MonthlyDemandCalculation:
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print(sys.exc_info()[1])
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print('Building ' + building.name + ' could not be processed')
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continue
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@staticmethod
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def _demand(insel_outputs_path):
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heating = []
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cooling = []
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with open(Path(insel_outputs_path).resolve()) as csv_file:
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csv_reader = csv.reader(csv_file)
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for line in csv_reader:
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demand = str(line).replace("['", '').replace("']", '').split()
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for i in range(0, 2):
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if demand[i] != 'NaN':
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aux = float(demand[i])*1000 # kWh to Wh
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demand[i] = str(aux)
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heating.append(demand[0])
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cooling.append(demand[1])
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monthly_heating = pd.DataFrame(heating, columns=['INSEL'])
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monthly_cooling = pd.DataFrame(cooling, columns=['INSEL'])
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return monthly_heating, monthly_cooling
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@ -1,177 +0,0 @@
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import helpers.library_codes
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import numpy as np
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from pathlib import Path
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import pandas as pd
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import csv
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from imports.weather.helpers.weather import Weather as wt
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import helpers.constants as cte
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class MonthlyEnergyBalance:
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@staticmethod
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def generate_meb_template(building, insel_outputs_path, key):
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lc = helpers.library_codes.LibraryCodes()
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file = ""
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file += "s 1 do\r\n"
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file += "p 1 1 12 1\r\n"
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file += "\r\n"
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file += "s 4 d18599 1.1 20.1 21.1\r\n"
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surfaces = building.surfaces
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for i in range(1, len(surfaces) + 1):
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file += str(100 + i) + '.1 % Radiation surface ' + str(i) + '\n'
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file += 'p 4' + '\n'
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# BUILDING PARAMETERS
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file += str(0.85*building.volume) + ' % BP(1) Heated Volume (vBrutto)\n'
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file += str(building.average_storey_height) + ' % BP(2) Average storey height / m\n'
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file += str(building.storeys_above_ground) + ' % BP(3) Number of storeys above ground\n'
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file += str(building.attic_heated) + ' % BP(4) Attic heating type (0=no room, 1=unheated, 2=heated)\n'
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file += str(building.basement_heated) + ' % BP(5) Cellar heating type (0=no room, 1=unheated, ' \
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'2=heated, 99=invalid)\n'
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# todo: this method and the insel model have to be reviewed for more than one thermal zone
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thermal_zone = building.thermal_zones[0]
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file += str(thermal_zone.indirectly_heated_area_ratio) + ' % BP(6) Indirectly heated area ratio\n'
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file += str(thermal_zone.effective_thermal_capacity) + ' % BP(7) Effective heat capacity\n'
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file += str(thermal_zone.additional_thermal_bridge_u_value) + ' % BP(8) Additional U-value for heat bridge\n'
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file += '0 % BP(9) Usage type (0=standard, 1=IWU)\n'
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# ZONES AND SURFACES
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# todo: is this actually number of thermal zones or of usage zones?
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file += str(len(building.thermal_zones)) + ' % BP(10) Number $z$ of zones\n'
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i = 0
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for usage_zone in building.usage_zones:
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percentage_usage = 1
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file += str(float(building.floor_area) * percentage_usage) + ' % BP(11) #1 Area of zone ' + \
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str(i + 1) + ' (sqm)' + '\n'
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total_internal_gains = 0
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for ig in usage_zone.internal_gains:
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total_internal_gains += float(ig.average_internal_gain) * \
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(float(ig.convective_fraction) + float(ig.radiative_fraction))
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file += str(total_internal_gains) + ' % BP(12) #2 Internal gains of zone ' + str(i + 1) + '\n'
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file += str(usage_zone.heating_setpoint) + ' % BP(13) #3 Heating setpoint temperature zone ' + \
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str(i + 1) + ' (tSetHeat)' + '\n'
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file += str(usage_zone.heating_setback) + ' % BP(14) #4 Heating setback temperature zone ' + \
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str(i + 1) + ' (tSetbackHeat)' + '\n'
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# file += str(usage_zone.cooling_setpoint) + ' % BP(15) #5 Cooling setpoint temperature zone ' + \
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# str(i + 1) + ' (tSetCool)' + '\n'
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file += '21 % BP(15) #5 Cooling setpoint temperature zone ' + \
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str(i + 1) + ' (tSetCool)' + '\n'
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file += str(usage_zone.hours_day) + ' % BP(16) #6 Usage hours per day zone ' + str(i + 1) + '\n'
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file += str(usage_zone.days_year) + ' % BP(17) #7 Usage days per year zone ' + str(i + 1) + '\n'
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if usage_zone.mechanical_air_change is None:
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if thermal_zone.infiltration_rate_system_off is None:
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raise Exception('Ventilation air rate is not initialized')
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else:
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file += str(thermal_zone.infiltration_rate_system_off) + ' % BP(18) #8 Minimum air change rate zone ' + \
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str(i + 1) + ' (h^-1)' + '\n'
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else:
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file += str(usage_zone.mechanical_air_change) + ' % BP(18) #8 Minimum air change rate zone ' + \
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str(i + 1) + ' (h^-1)' + '\n'
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i += 1
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file += str(len(surfaces)) + ' % Number of surfaces = BP(11+8z)\n'
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file += '% 1. Surface type (1=wall, 2=ground 3=roof, 4=flat roof)' + '\n'
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file += '% 2. Areas above ground' + '\n'
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file += '% 3. Areas below ground' + '\n'
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file += '% 4. U-value' + '\n'
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file += '% 5. Window area' + '\n'
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file += '% 6. Window frame fraction' + '\n'
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file += '% 7. Window U-value' + '\n'
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file += '% 8. Window g-value' + '\n'
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file += '% 9. Short-wave reflectance' + '\n'
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file += '% #1 #2 #3 #4 #5 #6 #7 #8 #9' + '\n'
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# todo: this method has to be reviewed for more than one thermal opening per thermal boundary
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for thermal_boundary in building.thermal_zones[0].bounded:
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type_code = lc.construction_types_to_code(thermal_boundary.type)
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if thermal_boundary.surface.holes_polygons is None:
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window_area = float(thermal_boundary.surface.perimeter_polygon.area) * float(thermal_boundary.window_ratio)
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else:
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window_area = 0
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for hole_polygon in thermal_boundary.surface.holes_polygons:
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window_area += hole_polygon.area
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string = type_code + ' ' + str(0.85*thermal_boundary.surface.area_above_ground) + ' ' + \
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str(thermal_boundary.surface.area_below_ground) + ' ' + str(thermal_boundary.u_value) + ' ' + \
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str(0.85*window_area) + ' '
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if window_area <= 0.001:
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string = string + '0 0 0 '
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else:
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string = string + str(thermal_boundary.thermal_openings[0].frame_ratio) + ' ' + \
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str(thermal_boundary.thermal_openings[0].overall_u_value) + ' ' + \
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str(thermal_boundary.thermal_openings[0].g_value) + ' '
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if thermal_boundary.outside_solar_absorptance is not None:
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string += str(thermal_boundary.shortwave_reflectance) + '\r\n'
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else:
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string += '0 \r\n'
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file += string
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file += '\r\n'
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file += 's 20 polyg 1\r\n'
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file += 'p 20 12 % Monthly ambient temperature\r\n'
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external_temperature = building.external_temperature[cte.MONTH]
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for i in range(0, len(external_temperature)):
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file += str(i+1) + ' ' + str(external_temperature.at[i, key]) + '\r\n'
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file += '\r\n'
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file += 's 21 polyg 1\r\n'
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file += 'p 21 12 % Monthly sky temperature\r\n'
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i = 1
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sky_temperature = wt.sky_temperature(external_temperature[[key]].to_numpy().T[0])
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for temperature in sky_temperature:
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file += str(i) + ' ' + str(temperature) + '\r\n'
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i += 1
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i = 0
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for surface in surfaces:
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file += '\r\n'
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file += 's ' + str(101 + i) + ' polyg 1 % Monthly surface radiation (W/sqm)\r\n'
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file += 'p ' + str(101 + i) + ' 12 % Azimuth ' + str(np.rad2deg(surface.azimuth)) + \
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', inclination ' + str(np.rad2deg(surface.inclination)) + ' degrees\r\n'
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if surface.type != 'Ground':
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global_irradiance = surface.global_irradiance[cte.MONTH]
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for j in range(0, len(global_irradiance)):
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file += str(j + 1) + ' ' + str(global_irradiance.at[j, 'sra']) + '\r\n'
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else:
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for j in range(0, 12):
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file += str(j + 1) + ' 0\r\n'
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i += 1
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file += '\r\n'
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file += '% ONE YEAR\r\n'
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file += 's 300 cum 4.1 4.2\r\n'
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file += 's 303 atend 300.1 300.2\r\n'
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file += '\r\n'
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file += 's ' + str(310) + ' WRITE\r\n'
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file += '4.1 4.2\r\n'
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file += 'p ' + str(310) + '\r\n'
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file += '1 % Mode\r\n'
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file += '0 % Suppress FNQ inputs\r\n'
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file += "'" + str(insel_outputs_path) + "' % File name\r\n"
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file += "'*' % Fortran format\r\n"
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return file
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@staticmethod
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def demand(insel_outputs_path):
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heating = []
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cooling = []
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with open(Path(insel_outputs_path).resolve()) as csv_file:
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csv_reader = csv.reader(csv_file)
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for line in csv_reader:
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demand = str(line).replace("['", '').replace("']", '').split()
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for i in range(0, 2):
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if demand[i] != 'NaN':
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aux = float(demand[i])*1000 # kWh to Wh
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demand[i] = str(aux)
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heating.append(demand[0])
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cooling.append(demand[1])
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monthly_heating = pd.DataFrame(heating, columns=['INSEL'])
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monthly_cooling = pd.DataFrame(cooling, columns=['INSEL'])
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return monthly_heating, monthly_cooling
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145
main.py
145
main.py
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@ -16,21 +16,16 @@ from helpers import monthly_values as mv
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from simplified_radiosity_algorithm import SimplifiedRadiosityAlgorithm
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from imports.geometry_factory import GeometryFactory
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from imports.weather_factory import WeatherFactory
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from city_model_structure.city import City
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from monthly_demand_calculation import MonthlyDemandCalculation
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from helpers.enrich_city import EnrichCity
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from imports.construction_factory import ConstructionFactory
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from imports.usage_factory import UsageFactory
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from exports.energy_building_exports_factory import EnergyBuildingsExportsFactory
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from insel.monthly_demand_calculation import MonthlyDemandCalculation
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parser = ArgumentParser(description='Monthly energy balance workflow v0.1.')
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parser = ArgumentParser(description='Monthly energy balance workflow v1.0.')
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required = parser.add_argument_group('required arguments')
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parser.add_argument('--geometry_type', '-g', help='Geometry type {citygml}', default='citygml')
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required.add_argument('--input_geometry_file', '-i', help='Input geometry file', required=True)
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parser.add_argument('--use_pickle_file', '-p', help='Use pickle file instead of importing geometry file', default=False,
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required=True)
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parser.add_argument('--populated_step_in_pickle', '-ps', help='Physics and usage parameters already in pickle file',
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default=False, required=True)
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parser.add_argument('--weather_step_in_pickle', '-ws', help='Weather parameters already in pickle file',
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default=False, required=True)
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parser.add_argument('--use_cached_sra_file', '-u', help='Use sra files from cache, instead of freshly calculated sra '
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'files', default=False)
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required.add_argument('--project_folder', '-f', help='Project folder', required=True)
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@ -45,113 +40,91 @@ keep_files = True
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print('begin_time', datetime.datetime.now())
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# Step 1: Initialize the city model
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pickle_file = ''
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if ast.literal_eval(args.use_pickle_file):
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pickle_file = Path(args.input_geometry_file).resolve()
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city = City.load(pickle_file)
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else:
|
||||
file = Path(args.input_geometry_file).resolve()
|
||||
pickle_file = Path(str(file).replace('.gml', '.pickle'))
|
||||
city = GeometryFactory(args.geometry_type, file).city
|
||||
print(len(city.buildings))
|
||||
for building in city.buildings:
|
||||
volume = building.volume
|
||||
if str(volume) == 'inf':
|
||||
sys.stderr.write(f'Building {building.name} has geometry errors. It has been removed from the city\n')
|
||||
city.remove_city_object(building)
|
||||
city.save(pickle_file)
|
||||
file = Path(args.input_geometry_file).resolve()
|
||||
city = GeometryFactory(args.geometry_type, file).city
|
||||
for building in city.buildings:
|
||||
volume = building.volume
|
||||
if str(volume) == 'inf':
|
||||
sys.stderr.write(f'Building {building.name} has geometry errors. It has been removed from the city\n')
|
||||
city.remove_city_object(building)
|
||||
|
||||
print('begin_populating_time', datetime.datetime.now())
|
||||
# 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
|
||||
else:
|
||||
populated_city = EnrichCity(city).enriched_city(construction_format='nrcan', usage_format='hft')
|
||||
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()
|
||||
for building in city.buildings:
|
||||
building.year_of_construction = 2006
|
||||
if building.function is None:
|
||||
building.function = 'large office'
|
||||
building.attic_heated = 0
|
||||
building.basement_heated = 1
|
||||
ConstructionFactory('nrel', city).enrich()
|
||||
UsageFactory('comnet', city).enrich()
|
||||
|
||||
print('begin_weather_time', datetime.datetime.now())
|
||||
# Step 3: Populate city adding climate-related parameters
|
||||
weather_format = 'epw'
|
||||
weather_step_in_pickle = ast.literal_eval(args.weather_step_in_pickle)
|
||||
if not weather_step_in_pickle:
|
||||
city.climate_reference_city = args.climate_reference_city
|
||||
path = (Path(args.project_folder) / 'tmp').resolve()
|
||||
city.climate_file = (path / f'{args.climate_reference_city}.cli').resolve()
|
||||
WeatherFactory(weather_format, populated_city, file_name=args.weather_file_name).enrich()
|
||||
for building in populated_city.buildings:
|
||||
if cte.HOUR not in building.external_temperature:
|
||||
print('No external temperature found')
|
||||
sys.exit()
|
||||
city.climate_reference_city = args.climate_reference_city
|
||||
tmp_path = (Path(args.project_folder) / 'tmp').resolve()
|
||||
city.climate_file = (tmp_path / f'{args.climate_reference_city}.cli').resolve()
|
||||
WeatherFactory(weather_format, city, file_name=args.weather_file_name).enrich()
|
||||
for building in city.buildings:
|
||||
if cte.HOUR not in building.external_temperature:
|
||||
print('No external temperature found')
|
||||
sys.exit()
|
||||
|
||||
if cte.MONTH not in building.external_temperature:
|
||||
building.external_temperature[cte.MONTH] = mv.MonthlyValues().\
|
||||
get_mean_values(building.external_temperature[cte.HOUR][[weather_format]])
|
||||
if cte.MONTH not in building.external_temperature:
|
||||
building.external_temperature[cte.MONTH] = mv.MonthlyValues().\
|
||||
get_mean_values(building.external_temperature[cte.HOUR][[weather_format]])
|
||||
|
||||
max_buildings_handled_by_sra = 500
|
||||
for building in city.buildings:
|
||||
for surface in building.surfaces:
|
||||
surface.swr = 0.2
|
||||
sra = SimplifiedRadiosityAlgorithm(city, Path(args.project_folder).resolve(), args.weather_file_name)
|
||||
if ast.literal_eval(args.use_cached_sra_file):
|
||||
sra.results()
|
||||
sra.set_irradiance_surfaces(populated_city)
|
||||
max_buildings_handled_by_sra = 500
|
||||
sra = SimplifiedRadiosityAlgorithm(city, Path(args.project_folder).resolve(), args.weather_file_name)
|
||||
if ast.literal_eval(args.use_cached_sra_file):
|
||||
sra.set_irradiance_surfaces(city)
|
||||
else:
|
||||
total_number_of_buildings = len(city.buildings)
|
||||
if total_number_of_buildings > max_buildings_handled_by_sra:
|
||||
radius = 80
|
||||
for building in city.buildings:
|
||||
new_city = city.region(building.centroid, radius)
|
||||
sra_new = SimplifiedRadiosityAlgorithm(new_city, Path(args.project_folder).resolve(), args.weather_file_name)
|
||||
sra_new.call_sra(weather_format, keep_files=True)
|
||||
sra_new.set_irradiance_surfaces(city, building_name=building.name)
|
||||
else:
|
||||
total_number_of_buildings = len(city.buildings)
|
||||
if total_number_of_buildings > max_buildings_handled_by_sra:
|
||||
radius = 80
|
||||
for building in city.buildings:
|
||||
new_city = city.region(building.centroid, radius)
|
||||
sra_new = SimplifiedRadiosityAlgorithm(new_city, Path(args.project_folder).resolve(), args.weather_file_name)
|
||||
sra_new.call_sra(weather_format, keep_files=True)
|
||||
sra_new.set_irradiance_surfaces(populated_city, building_name=building.name)
|
||||
else:
|
||||
sra.call_sra(weather_format, 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_user_assignment_time', datetime.datetime.now())
|
||||
# Step 4: Assign user defined parameters
|
||||
for building in populated_city.buildings:
|
||||
building.attic_heated = 2
|
||||
building.basement_heated = 0
|
||||
sra.call_sra(weather_format, keep_files=keep_files)
|
||||
sra.set_irradiance_surfaces(city)
|
||||
|
||||
print('begin_insel_time', datetime.datetime.now())
|
||||
# Step 5: Demand calculation calling INSEL
|
||||
MonthlyDemandCalculation(city, args.project_folder, weather_format).monthly_demand()
|
||||
EnergyBuildingsExportsFactory('insel_monthly_energy_balance', city, tmp_path).export()
|
||||
insel = MonthlyDemandCalculation(city, tmp_path, weather_format)
|
||||
insel.run()
|
||||
insel.results()
|
||||
|
||||
print('begin_write_results_time', datetime.datetime.now())
|
||||
# Step 6: Print results
|
||||
print_results = None
|
||||
file = 'city name: ' + city.name + '\n'
|
||||
for building in populated_city.buildings:
|
||||
for building in city.buildings:
|
||||
insel_file_name = building.name + '.insel'
|
||||
building_results = building.heating[cte.MONTH].rename(columns={'INSEL': building.name})
|
||||
heating_results = building.heating[cte.MONTH].rename(columns={'INSEL': f'{building.name} heating Wh'})
|
||||
cooling_results = building.cooling[cte.MONTH].rename(columns={'INSEL': f'{building.name} cooling Wh'})
|
||||
if print_results is None:
|
||||
print_results = building_results
|
||||
print_results = heating_results
|
||||
else:
|
||||
print_results = pd.concat([print_results, building_results], axis='columns')
|
||||
print_results = pd.concat([print_results, heating_results], axis='columns')
|
||||
print_results = pd.concat([print_results, cooling_results], axis='columns')
|
||||
file += '\n'
|
||||
file += 'name: ' + building.name + '\n'
|
||||
file += 'year of construction: ' + building.year_of_construction + '\n'
|
||||
file += 'year of construction: ' + str(building.year_of_construction) + '\n'
|
||||
file += 'function: ' + building.function + '\n'
|
||||
file += 'floor area: ' + str(building.thermal_zones[0].floor_area) + '\n'
|
||||
file += 'floor area: ' + str(building.internal_zones[0].area) + '\n'
|
||||
file += 'storeys: ' + str(building.storeys_above_ground) + '\n'
|
||||
file += 'heated_volume: ' + str(building.volume) + '\n'
|
||||
file += 'volume: ' + str(building.volume) + '\n'
|
||||
|
||||
full_path_results = Path(args.project_folder + '/outputs/heating_demand.csv').resolve()
|
||||
full_path_results = Path(args.project_folder + '/outputs/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)
|
||||
|
||||
pickle_file = Path(str(pickle_file).replace('.pickle', '_demand.pickle'))
|
||||
populated_city.save(pickle_file)
|
||||
|
||||
print('end_time', datetime.datetime.now())
|
||||
|
|
|
|||
|
|
@ -1,181 +0,0 @@
|
|||
"""
|
||||
TestMebWorkflow tests and validates the complete Monthly Energy Balance workflow
|
||||
SPDX - License - Identifier: LGPL - 3.0 - or -later
|
||||
Copyright © 2020 Project Author Pilar Monsalvete pilar_monsalvete@yahoo.es
|
||||
"""
|
||||
|
||||
from pathlib import Path
|
||||
from unittest import TestCase
|
||||
import numpy as np
|
||||
import subprocess
|
||||
from subprocess import SubprocessError, TimeoutExpired, CalledProcessError
|
||||
|
||||
from insel.insel import Insel
|
||||
from insel.templates.monthly_energy_balance import MonthlyEnergyBalance as templates
|
||||
from imports.geometry_factory import GeometryFactory
|
||||
from populate import Populate
|
||||
from imports.weather_factory import WeatherFactory
|
||||
from helpers import monthly_values as mv
|
||||
from simplified_radiosity_algorithm.simplified_radiosity_algorithm import SimplifiedRadiosityAlgorithm as sralgorithm
|
||||
from city_model_structure.city import City
|
||||
|
||||
|
||||
class TestMebWorkflow(TestCase):
|
||||
"""
|
||||
TestMebWorkflow TestCase 1
|
||||
"""
|
||||
def setUp(self) -> None:
|
||||
"""
|
||||
Test setup
|
||||
:return: None
|
||||
"""
|
||||
self._example_path = (Path(__file__).parent.parent / 'tests_data').resolve()
|
||||
self._geometry_type = 'citygml'
|
||||
self._use_cached_sra_file = False
|
||||
self._input_geometry_file = (self._example_path / 'gis' / '2050_bp_2buildings.gml').resolve()
|
||||
self._project_folder = Path(__file__).parent.parent
|
||||
self._cli_weather_file = (self._example_path / 'weather' / 'inseldb_new_york_city.cli').resolve()
|
||||
self._city_gml = None
|
||||
self._city = None
|
||||
self._populated_city = None
|
||||
self._monthly_temperatures = None
|
||||
self._city_with_weather = None
|
||||
self._city_with_cli = None
|
||||
self._city_with_dat = None
|
||||
self._pickle_file = (self._example_path / 'gis' / 'kelowna_test_case.pickle').resolve()
|
||||
self._pickle_file_populated = Path(str(self._pickle_file).replace('.pickle', '_populated.pickle'))
|
||||
self._pickle_file_populated_weather = Path(str(self._pickle_file_populated).replace('.pickle', '_weather.pickle'))
|
||||
self._city_name = 'Summerland'
|
||||
|
||||
def _get_citygml(self, use_pickle=False):
|
||||
if self._city_gml is None:
|
||||
if use_pickle:
|
||||
self._city_gml = City.load(self._pickle_file)
|
||||
else:
|
||||
file_path = self._input_geometry_file
|
||||
self._city_gml = GeometryFactory('citygml', file_path).city
|
||||
self.assertIsNotNone(self._city_gml, 'city is none')
|
||||
return self._city_gml
|
||||
|
||||
def _get_citygml_populated(self, use_pickle):
|
||||
if self._populated_city is None:
|
||||
self._city = self._get_citygml(use_pickle=use_pickle)
|
||||
self._populated_city = Populate(self._city).populated_city
|
||||
return self._populated_city
|
||||
|
||||
def _get_citygml_with_weather(self, use_pickle):
|
||||
if self._city_with_weather is None:
|
||||
weather_format = 'epw'
|
||||
self._city_with_weather = self._get_citygml(use_pickle=use_pickle)
|
||||
weather_path = (self._example_path / 'weather').resolve()
|
||||
WeatherFactory(weather_format, self._city_with_weather, base_path=weather_path)
|
||||
for building in self._city_with_weather.buildings:
|
||||
building.external_temperature['month'] = mv.MonthlyValues(). \
|
||||
get_mean_values(building.external_temperature['hour'][['epw']])
|
||||
|
||||
sra_file_name = 'SRA'
|
||||
sra = sralgorithm(Path(self._project_folder).resolve(), sra_file_name, Path(self._cli_weather_file).resolve(),
|
||||
self._city_with_weather.city_objects, lower_corner=self._city_with_weather.lower_corner)
|
||||
if self._use_cached_sra_file:
|
||||
sra.results()
|
||||
else:
|
||||
sra.call_sra(weather_format, keep_files=True)
|
||||
sra.set_irradiance_surfaces(self._city_with_weather)
|
||||
return self._city_with_weather
|
||||
|
||||
def _get_cli_single_building(self, building_name, radius, use_pickle):
|
||||
weather_format = 'epw'
|
||||
self._city_with_cli = self._get_citygml(use_pickle=use_pickle)
|
||||
building = self._city_with_cli.city_object(building_name)
|
||||
new_city = self._city_with_cli.region(building.centroid, radius)
|
||||
sra_file_name = 'SRA'
|
||||
print('location', building.centroid)
|
||||
print('lower corner', new_city.lower_corner)
|
||||
full_path_cli = (self._example_path / 'weather' / 'inseldb_Summerland.cli').resolve()
|
||||
sra = sralgorithm(Path(self._project_folder).resolve(), sra_file_name, full_path_cli, new_city.city_objects,
|
||||
lower_corner=new_city.lower_corner)
|
||||
sra.call_sra(weather_format, keep_files=True)
|
||||
sra.set_irradiance_surfaces(self._city_with_cli, building_name=building_name)
|
||||
return self._city_with_cli
|
||||
|
||||
def test_populate_city(self):
|
||||
"""
|
||||
Test populate class
|
||||
:return: none
|
||||
"""
|
||||
# populated_city = self._get_citygml_populated(True)
|
||||
# populated_city.save(pickle_file_populated)
|
||||
populated_city = City.load(self._pickle_file_populated)
|
||||
self.assertIsNotNone(populated_city.city_objects, 'city_objects is none')
|
||||
for building in populated_city.buildings:
|
||||
self.assertIsNotNone(building.usage_zones, 'city_object return none')
|
||||
self.assertIsNotNone(building.thermal_zones, 'city_object return none')
|
||||
|
||||
def test_weather_assignment(self):
|
||||
"""
|
||||
Test the weather assignment
|
||||
:return: none
|
||||
"""
|
||||
weather_city = self._get_citygml_with_weather(False)
|
||||
for building in weather_city.buildings:
|
||||
self.assertFalse(building.external_temperature['month'].empty, 'monthly external temperature return none')
|
||||
for surface in building.surfaces:
|
||||
if surface.type != 'Ground':
|
||||
self.assertIsNotNone(surface.global_irradiance['month'], 'monthly irradiance return none')
|
||||
|
||||
def test_insel_call(self):
|
||||
"""
|
||||
Test the insel template generation and engine call
|
||||
:return: none
|
||||
"""
|
||||
self._get_citygml_populated(False)
|
||||
city = self._get_citygml_with_weather(False)
|
||||
expected_values = [[13619.57, 3.65], [14886.33, 1.67]]
|
||||
i = 0
|
||||
for building in city.buildings:
|
||||
full_path_out = Path(self._project_folder / 'outputs' / (building.name + '_insel.out')).resolve()
|
||||
full_path_out.parent.mkdir(parents=True, exist_ok=True)
|
||||
insel_file_name = building.name + '.insel'
|
||||
content = templates.generate_meb_template(building, full_path_out)
|
||||
self.assertIsNotNone(content, 'content return empty')
|
||||
Insel(Path(self._project_folder).resolve(), insel_file_name, content, mode=2,
|
||||
keep_files=True).run()
|
||||
building.heating['month'], building.cooling['month'] = templates.demand(full_path_out)
|
||||
values = building.heating['month'][['INSEL']].to_numpy()
|
||||
self.assertEqual(expected_values[i][0], np.around(float(values[11]), decimals=2), 'wrong value monthly heating')
|
||||
values = building.cooling['month'][['INSEL']].to_numpy()
|
||||
self.assertEqual(expected_values[i][1], np.around(float(values[11]), decimals=2), 'wrong value monthly cooling')
|
||||
i += 1
|
||||
|
||||
def test_city_with_weather_building_by_building(self):
|
||||
radius = 100
|
||||
building_names = ['BLD100086', 'BLD131702', 'BLD132148', 'BLD126221', 'BLD131081', 'BLD135303', 'BLD130088',
|
||||
'BLD128703', 'BLD121900', 'BLD141378', 'BLD135375', 'BLD126801', 'BLD120774', 'BLD118577',
|
||||
'BLD129395', 'BLD126848', 'BLD115972', 'BLD138959', 'BLD122103', 'BLD114335', 'BLD124272',
|
||||
'BLD107027', 'BLD105415', 'BLD129867', 'BLD133164', 'BLD119241', 'BLD106658', 'BLD114097',
|
||||
'BLD130182', 'BLD121456', 'BLD123516', 'BLD126061', 'BLD128845', 'BLD138802', 'BLD129673']
|
||||
building_names = ['BLD100086']
|
||||
|
||||
city = self._get_city_with_dat(True)
|
||||
for building in city.buildings:
|
||||
self.assertTrue(building.external_temperature, 'external temperature return none')
|
||||
|
||||
for building_name in building_names:
|
||||
print(building_name)
|
||||
weather_city = self._get_cli_single_building(building_name, radius, True)
|
||||
# for building in weather_city.city_objects:
|
||||
# if building.name == building_name:
|
||||
# for surface in building.surfaces:
|
||||
# if surface.type != 'Ground':
|
||||
# self.assertTrue(surface.global_irradiance, 'global irradiance return none in calculated building')
|
||||
# else:
|
||||
# for surface in building.surfaces:
|
||||
# self.assertFalse(surface.global_irradiance, 'global irradiance return not none in not calculated building')
|
||||
|
||||
def test_sra(self):
|
||||
_executable = 'shortwave_integer'
|
||||
_full_path_in = (Path(__file__).parent.parent / 'tmp\SRA.xml').resolve()
|
||||
try:
|
||||
completed = subprocess.run([_executable, str(_full_path_in)])
|
||||
except (SubprocessError, TimeoutExpired, CalledProcessError) as error:
|
||||
raise Exception(error)
|
||||
Loading…
Reference in New Issue
Block a user