Added heatpump export module
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Peter Yefi
parent
ce2e46a236
commit
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@ -3,10 +3,10 @@ HeatPumpExport exports heatpump coefficient into several formats
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SPDX - License - Identifier: LGPL - 3.0 - or -later
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Copyright © 2021 Project Author Peter Yefi peteryefi@gmail.com
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"""
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import numpy as np
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from scipy.optimize import curve_fit
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from typing import Dict, Tuple
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import pandas as pd
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import subprocess
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from typing import List, Tuple, Union
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import yaml
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from string import Template
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class HeatPumpExport:
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@ -16,70 +16,131 @@ class HeatPumpExport:
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"""
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def __init__(self, base_path, city):
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self._base_path = (base_path / 'heat_pumps/coefficients.xlsx')
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self._template_path = (base_path / 'heat_pumps/template.txt')
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self._constants_path = (base_path / 'heat_pumps/constants.yaml')
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# needed to compute max demand.
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self._demand_path = (base_path / 'heat_pumps/demand.txt')
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self._city = city
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self._input_data = None
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self._base_path = base_path
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def export_xlsx(self):
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def run_insel(self, user_input, hp_model, data_type) -> None:
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"""
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Writes the coefficients computed from heat performance
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and cooling performance data to excel sheet
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:return: None
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"""
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writer = pd.ExcelWriter(self._base_path)
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heat_column_names = ["a1", "a2", "a3", "a4", "a5", "a6"]
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cool_column_names = ["b1", "b2", "b3", "b4", "b5", "b6"]
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heat_coff, cool_coff = self._compute_coefficients()
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for (k_cool, v_cool), (k_heat, v_heat) in \
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zip(heat_coff.items(), cool_coff.items()):
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heat_df = pd.DataFrame([v_heat["heat_cap"], v_heat["comp_power"]], columns=heat_column_names,
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index=["Heat Capacity", "Compressor Power"])
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heat_df.to_excel(writer, sheet_name=k_heat)
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cool_df = pd.DataFrame([v_heat["cool_cap"], v_heat["comp_power"]], columns=cool_column_names,
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index=["Cooling Capacity", "Compressor Power"])
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cool_df.to_excel(writer, sheet_name=k_cool, startrow=10)
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writer.save()
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def _compute_coefficients(self) -> Tuple[Dict, Dict]:
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"""
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Compute heat output and electrical demand coefficients
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from heating and cooling performance data
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:return: Tuple[Dict, Dict]
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"""
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out_temp = [25, 30, 32, 35, 40, 45] * 6
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heat_x_values = np.repeat([-5, 0, 7, 10, 15], 6)
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cool_x_values = np.repeat([6, 7, 8, 9, 10, 11], 6)
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cooling_coff = {}
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heating_coff = {}
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for energy_system in self._city.energy_systems:
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# Compute heat output coefficients
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heating_cap_popt, _ = curve_fit(self._objective_function, [heat_x_values, out_temp],
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energy_system.heat_pump.heating_capacity)
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heating_comp_power_popt, _ = curve_fit(self._objective_function, [heat_x_values, out_temp],
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energy_system.heat_pump.heating_comp_power)
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# Compute electricity demand coefficients
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cooling_cap_popt, _ = curve_fit(self._objective_function, [cool_x_values, out_temp],
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energy_system.heat_pump.cooling_capacity)
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cooling_comp_power_popt, _ = curve_fit(self._objective_function, [cool_x_values, out_temp],
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energy_system.heat_pump.cooling_comp_power)
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heating_coff[energy_system.heat_pump.model] = {"heat_cap": heating_cap_popt.tolist(),
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"comp_power": heating_comp_power_popt.tolist()}
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cooling_coff[energy_system.heat_pump.model] = {"cool_cap": cooling_cap_popt.tolist(),
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"comp_power": cooling_comp_power_popt.tolist()}
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return heating_coff, cooling_coff
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def _objective_function(self, xdata, a1, a2, a3, a4, a5, a6):
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"""
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Objective function for computing coefficients
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:param xdata:
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:param a1: float
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:param a2: float
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:param a3: float
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:param a4: float
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:param a5: float
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:param a6: float
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Runs insel and write the necessary files
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:param user_input: a dictionary containing the user
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values necessary to run insel
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:param hp_model: a string that indicates the heat
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pump model to be used e.g. 012, 015
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:param data_type: a string that indicates whether
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insel should run for heat or cooling performance
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:return:
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"""
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x, y = xdata
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return (a1 * x ** 2) + (a2 * x) + (a3 * x * y) + (a4 * y) + (a5 * y ** 2) + a6
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self._input_data = user_input
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# update input data with other data necessary to run insel
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capacity_coff, comp_power_coff = self._extract_model_coff(hp_model, data_type)
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self._update_input_data_with_coff(capacity_coff, comp_power_coff)
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# update input data with constants
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self._update_input_data_with_constants()
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# update input data with input and output files for insel
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self._update_input_data_with_files()
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insel_file_handler = None
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insel_template_handler = None
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try:
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# run insel
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insel_template_handler = open(self._template_path, "r")
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insel_template_handler = insel_template_handler.read()
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insel_template = Template(insel_template_handler).substitute(self._input_data)
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# create the insel file and write the template with substituted values into it
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insel_file = (self._base_path / 'heat_pumps/dompark_heat_pump.insel')
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insel_file_handler = open(insel_file, "w")
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insel_file_handler.write(insel_template)
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# Now run insel
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subprocess.call('insel', insel_file)
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except IOError as err:
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print("I/O exception: {}".format(err))
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except subprocess.CalledProcessError as err:
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print("Insel command error {}".format(err))
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else:
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print("Insel executed successfully")
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finally:
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insel_file_handler.close()
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insel_template_handler.close()
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def _update_input_data_with_files(self):
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"""
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Updates input data for insel with some files that will
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be written to after insel runs. Also specifies and input file
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which is the Heating Demand (demand.txt) file
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:return:
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"""
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self._input_data["HeatingDemand"] = self._demand_path
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self._input_data["fileOut1"] = (self._base_path / 'heat_pumps/technical_performance.csv')
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self._input_data["fileOut2"] = (self._base_path / 'heat_pumps/system_daily_emissions.cs')
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self._input_data["fileOut3"] = (self._base_path / 'heat_pumps/monthly_operational_costs.csv')
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self._input_data["fileOut4"] = (self._base_path / 'heat_pumps/monthly_fossil_fuel_consumptions.csv')
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self._input_data["fileOut5"] = (self._base_path / 'heat_pumps/system_monthly_emissions.csv')
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self._input_data["fileOut6"] = (self._base_path / 'heat_pumps/daily_hp_electricity_demand.csv')
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self._input_data["fileOut7"] = (self._base_path / 'heat_pumps/daily_operational_costs.csv')
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self._input_data["fileOut8"] = (self._base_path / 'heat_pumps/monthly_hp_electricity_demand.csv')
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self._input_data["fileOut9"] = (self._base_path / 'heat_pumps/daily_fossil_fuel_consumption.csv')
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self._input_data["fileOut10"] = (self._base_path / 'heat_pumps/hp_hourly_electricity_demand.csv')
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def _compute_max_demand(self):
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"""
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Retrieves the maximum demand value from
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the demands text file
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:return: float
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"""
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max_demand = -1
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with open(self._demand_path) as file_handler:
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for demand in file_handler.readlines():
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if float(demand) > max_demand:
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max_demand = float(demand)
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return max_demand
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def _update_input_data_with_constants(self):
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with open(self._constants_path) as file:
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constants_dict = yaml.load(file, Loader=yaml.FullLoader)
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for key, value in constants_dict.items():
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self._input_data[key] = value
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# compute maximum demand. TODO: This should come from catalog in the future
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max_demand = self._compute_max_demand()
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# compute TESCapacity
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self._input_data["TESCapacity"] = self._input_data["HoursOfStorageAtMaxDemand"] * (max_demand * 3.6) / (
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(self._input_data["Cp"] / 1000) * self._input_data["TemperatureDifference"])
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def _update_input_data_with_coff(self, capacity_coff, comp_power_coff):
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"""
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Updates the user data with coefficients derived from imports
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:param capacity_coff: heat or cooling capacity coefficients
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:param comp_power_coff: heat or cooling comppressor power coefficients
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:return:
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"""
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self._input_data["a1"] = capacity_coff[0]
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self._input_data["a2"] = capacity_coff[1]
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self._input_data["a3"] = capacity_coff[2]
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self._input_data["a4"] = capacity_coff[3]
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self._input_data["a5"] = capacity_coff[4]
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self._input_data["a6"] = capacity_coff[5]
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self._input_data["b1"] = comp_power_coff[0]
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self._input_data["b2"] = comp_power_coff[1]
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self._input_data["b3"] = comp_power_coff[2]
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self._input_data["b4"] = comp_power_coff[3]
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self._input_data["b5"] = comp_power_coff[4]
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self._input_data["b6"] = comp_power_coff[5]
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def _extract_model_coff(self, hp_model, data_type='heat') -> Union[Tuple[List, List], None]:
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"""
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Extracts heat pump coefficient data for a specific
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model. e.g 012, 140
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:param hp_model: the model type
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:param data_type: indicates whether we're extracting cooling
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or heating perfarmcn coefficients
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:return:
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"""
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for energy_system in self._city.energy_systems:
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if energy_system.heat_pump.model == hp_model:
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if data_type == 'heat':
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return energy_system.heat_pump.heating_capacity_coff, energy_system.heat_pump.heating_comp_power_coff
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return energy_system.heat_pump.cooling_capacity_coff, energy_system.heat_pump.cooling_comp_power_coff
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return None
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