65 lines
2.2 KiB
Python
65 lines
2.2 KiB
Python
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"""
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Monthly demand calculation using the monthly energy balance methodology based on the norm...
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SPDX - License - Identifier: LGPL - 3.0 - or -later
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Copyright © 2020 Project Author Pilar Monsalvete Alvarez de Uribarri pilar.monsalvete@concordia.ca
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"""
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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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import csv
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from insel.insel import Insel
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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._weather_format = weather_format
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def results(self):
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for building in self._city.buildings:
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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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try:
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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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value = '0'
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heating_year += float(value)
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yearly_heating = pd.DataFrame([heating_year], columns=['INSEL'])
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building.heating['year'] = yearly_heating
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cooling_year = 0
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for value in building.cooling['month']['INSEL']:
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if value == 'NaN':
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value = '0'
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cooling_year += float(value)
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yearly_cooling = pd.DataFrame([cooling_year], columns=['INSEL'])
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building.cooling['year'] = yearly_cooling
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except ValueError:
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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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