city_retrofit/costing_package/peak_load.py

57 lines
2.0 KiB
Python

"""
Peak load module
SPDX - License - Identifier: LGPL - 3.0 - or -later
Copyright © 2023 Project Coder Guille Gutierrez guillermo.gutierrezmorote@concordia.ca
Code contributor Pilar Monsalvete Alvarez de Uribarri pilar.monsalvete@concordia.ca
Code contributor Oriol Gavalda Torrellas oriol.gavalda@concordia.ca
"""
import pandas as pd
import hub.helpers.constants as cte
class PeakLoad:
"""
Peak load class
"""
def __init__(self, building):
self._building = building
@property
def electricity_peak_load(self):
"""
Get the electricity peak load in W
"""
array = [None] * 12
heating = 0
cooling = 0
for system in self._building.energy_systems:
if cte.HEATING in system.demand_types:
heating = 1
if cte.COOLING in system.demand_types:
cooling = 1
if cte.MONTH in self._building.heating_peak_load.keys() and cte.MONTH in self._building.cooling_peak_load.keys():
peak_lighting = self._building.lighting_peak_load[cte.YEAR][0]
peak_appliances = self._building.appliances_peak_load[cte.YEAR][0]
monthly_electricity_peak = [0.9 * peak_lighting + 0.7 * peak_appliances] * 12
conditioning_peak = max(self._building.heating_peak_load[cte.MONTH], self._building.cooling_peak_load[cte.MONTH])
for i in range(len(conditioning_peak)):
if cooling == 1 and heating == 1:
conditioning_peak[i] = conditioning_peak[i]
continue
elif cooling == 0:
conditioning_peak[i] = self._building.heating_peak_load[cte.MONTH][i] * heating
else:
conditioning_peak[i] = self._building.cooling_peak_load[cte.MONTH][i] * cooling
monthly_electricity_peak[i] += 0.8 * conditioning_peak[i]
electricity_peak_load_results = pd.DataFrame(
monthly_electricity_peak,
columns=[f'electricity peak load W']
)
else:
electricity_peak_load_results = pd.DataFrame(array, columns=[f'electricity peak load W'])
return electricity_peak_load_results