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Merge pull request #95 from lbl-srg/issue94_miscIntegrationSankeyMilpTerminal
Issue94 misc integration sankey milp terminal
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‎PythonResources/RunCases/extract_values_for_sankey.py‎

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#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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"""
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Created on Mon May 19 11:27:46 2025
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@author: casper
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This file extracts values from the results file to make the Sankey diagram.
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The diagram needs to be made manually in e!Sankey which only runs on Windows.
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"""
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import os
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import numpy as np
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import pandas as pd
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from GetVariables import *
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# python file under same folder
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#CWD = os.getcwd()
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CWD = os.path.dirname(os.path.abspath(__file__))
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mat_file_name = os.path.join(CWD, "simulations", "2025-07-10_base-crit", "2025-07-10-base-DetailedPlantFiveHubs.mat")
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nBui = 5 # Ensure this is consistent with the mat file
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_i = r'%%i%%' # placeholder string to be replaced with index
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J_to_kWh = 2.7777777777777776e-07
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#%% read results file
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var_list = list()
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# buildings
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var_list_pre_index = [
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f'bui[{_i}].ets.PCoo',
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f'bui[{_i}].dHChiWat_flow',
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f'bui[{_i}].dHHeaWat_flow',
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f'bui[{_i}].bui.disFloHea.PPum',
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f'bui[{_i}].bui.disFloCoo.PPum',
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f'QEtsHex_flow.u[{_i}]']
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var_list += index_var_list(var_list_pre_index,
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_i,
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range(1,nBui+1))
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# bui[1] doesn't have dhw
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var_list += index_var_list([f'bui[{_i}].dHHotWat_flow',
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f'bui[{_i}].ets.tanDhw.PEle'],
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_i,
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range(2,nBui+1))
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# ground connection has (nBui + 1) elements
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var_list += index_var_list(f'dis.heatPorts[{_i}].Q_flow',
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_i,
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range(1,nBui+2))
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# variables without an index
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var_list += ['cenPla.gen.ind.ySea',
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'cenPla.gen.hex.Q1_flow',
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'cenPla.gen.heaPum.P',
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'cenPla.gen.heaPum.QCon_flow',
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'cenPla.gen.heaPum.QEva_flow',
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'cenPla.QBorPer_flow',
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'cenPla.QBorCen_flow',
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'cenPla.gen.fanDryCoo.P',
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'cenPla.gen.pumDryCoo.P',
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'cenPla.gen.dryCoo.Q1_flow',
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'pumDis.P',
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'PEleNonHva.y',
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'PFanBuiSum.y',
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'EPvBat.u'
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]
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results = get_vars(var_list,
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mat_file_name,
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'dymola')
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#%% process results data
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# (source node, target node)
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# `energy carrier` influences colouring in the diagram
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data_dicts = [
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{
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("PV and bettery", "Electricity") : 0,
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("Electricity", "Buildings fans + non HVAC") : 0,
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("Electricity", "Pump coo") : 0,
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("Electricity", "Pump hea") : 0,
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("Electricity", "Pump DHW") : 0,
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("Electricity", "ETS") : 0,
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("Electricity", "Central plant chiller") : 0,
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("Electricity", "Dry cooler") : 0,
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("Electricity", "Pump district") : 0,
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("Heat ambient", "Dry cooler") : 0,
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("TEN", "Central plant chiller") : 0,
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("Dry cooler", "Heat ambient") : 0,
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("Central plant chiller", "TEN") : 0,
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("Economiser", "TEN") : 0,
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("Borefield", "TEN") : 0,
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("Ground", "TEN") : 0,
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("ETS", "Pump district") : 0,
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("TEN", "Economiser") : 0,
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("TEN", "Borefield") : 0,
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("TEN", "Ground") : 0,
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("Pump district", "ETS") : 0,
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("Pump coo", "ETS") : 0,
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("ETS", "Pump hea") : 0,
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("ETS", "DHW") : 0
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}
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for _ in range(5)]
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for sea in range(5):
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# for sea in range(1):
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if sea == 0:
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condition = None
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else:
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condition = np.array(results['cenPla.gen.ind.ySea'] == sea)
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data_dict = data_dicts[sea]
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# Electricity node
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data_dict[("PV and bettery", "Electricity")] = \
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abs(integrate_with_condition(results, 'EPvBat.u',
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condition = condition))
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data_dict[("Electricity", "Buildings fans + non HVAC")] = \
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abs(integrate_with_condition(results, 'PEleNonHva.y',
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condition = condition)) + \
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abs(integrate_with_condition(results, 'PFanBuiSum.y',
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condition = condition))
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data_dict[("Electricity", "Central plant chiller")] = \
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abs(integrate_with_condition(results, 'cenPla.gen.heaPum.P',
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condition = condition))
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data_dict[("Electricity", "Dry cooler")] = \
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abs(integrate_with_condition(results, 'cenPla.gen.fanDryCoo.P',
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condition = condition)) + \
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abs(integrate_with_condition(results, 'cenPla.gen.pumDryCoo.P',
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condition = condition))
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data_dict[("Electricity", "Pump district")] = \
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abs(integrate_with_condition(results, 'pumDis.P',
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condition = condition))
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# each building
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for i in range(1,nBui+1):
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data_dict[("Electricity", "ETS")] += \
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abs(integrate_with_condition(results, f'bui[{i}].ets.PCoo',
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condition = condition))
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data_dict[("Electricity", "Pump coo")] += \
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abs(integrate_with_condition(results, f'bui[{i}].bui.disFloCoo.PPum',
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condition = condition))
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data_dict[("Electricity", "Pump hea")] += \
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abs(integrate_with_condition(results, f'bui[{i}].bui.disFloHea.PPum',
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condition = condition))
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if i != 1: # bui[1] doesn't have dhw
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data_dict[("Electricity", "Pump DHW")] += \
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abs(integrate_with_condition(results, f'bui[{i}].ets.tanDhw.PEle',
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condition = condition))
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# Central plant node, previously computed links excluded
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data_dict[("Heat ambient", "Dry cooler")] = \
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abs(integrate_with_condition(results, 'cenPla.gen.dryCoo.Q1_flow',
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sign = 'negative',
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condition = condition))
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data_dict[("Dry cooler", "Heat ambient")] = \
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abs(integrate_with_condition(results, 'cenPla.gen.dryCoo.Q1_flow',
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sign = 'positive',
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condition = condition))
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data_dict[("Central plant chiller", "TEN")] = \
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abs(integrate_with_condition(results, 'cenPla.gen.heaPum.QCon_flow',
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sign = 'positive',
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condition = condition))
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data_dict[("TEN", "Central plant chiller")] = \
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abs(integrate_with_condition(results, 'cenPla.gen.heaPum.QCon_flow',
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sign = 'negative',
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condition = condition))
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# TEN node, previously computed links excluded
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data_dict[("Economiser", "TEN")] = \
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abs(integrate_with_condition(results, 'cenPla.gen.hex.Q1_flow',
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sign = 'positive',
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condition = condition))
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data_dict[("TEN", "Economiser")] = \
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abs(integrate_with_condition(results, 'cenPla.gen.hex.Q1_flow',
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sign = 'negative',
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condition = condition))
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data_dict[("Borefield", "TEN")] = \
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abs(integrate_with_condition(results, 'cenPla.QBorCen_flow',
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sign = 'positive',
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condition = condition)) + \
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abs(integrate_with_condition(results, 'cenPla.QBorPer_flow',
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sign = 'positive',
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condition = condition))
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data_dict[("TEN", "Borefield")] = \
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abs(integrate_with_condition(results, 'cenPla.QBorCen_flow',
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sign = 'negative',
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condition = condition)) + \
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abs(integrate_with_condition(results, 'cenPla.QBorPer_flow',
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sign = 'negative',
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condition = condition))
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# each pipe section
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for i in range(1,nBui+2):
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data_dict[("Ground", "TEN")] += \
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abs(integrate_with_condition(results, f'dis.heatPorts[{i}].Q_flow',
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sign = 'positive',
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condition = condition))
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data_dict[("TEN", "Ground")] += \
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abs(integrate_with_condition(results, f'dis.heatPorts[{i}].Q_flow',
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sign = 'negative',
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condition = condition))
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# each building
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for i in range(1,nBui+1):
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data_dict[("Pump district", "ETS")] += \
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abs(integrate_with_condition(results, f'QEtsHex_flow.u[{i}]',
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sign = 'positive',
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condition = condition))
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data_dict[("ETS", "Pump district")] += \
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abs(integrate_with_condition(results, f'QEtsHex_flow.u[{i}]',
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sign = 'negative',
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condition = condition))
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# ETS node, previously computed links excluded
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# each building
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for i in range(1,nBui+1):
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data_dict[("Pump coo", "ETS")] += \
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abs(integrate_with_condition(results, f'bui[{i}].dHChiWat_flow',
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condition = condition))
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data_dict[("ETS", "Pump hea")] += \
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abs(integrate_with_condition(results, f'bui[{i}].dHHeaWat_flow',
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condition = condition))
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if i != 1: # bui[1] doesn't have dhw
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data_dict[("ETS", "DHW")] += \
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abs(integrate_with_condition(results, f'bui[{i}].dHHotWat_flow',
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condition = condition))
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#%% output to Excel
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seasons = ['Whole year', 'Winter', 'Spring', 'Summer', 'Fall']
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with pd.ExcelWriter('sankey_modelica.xlsx', engine='openpyxl') as writer:
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for season, data_dict in zip(seasons, data_dicts):
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# Convert the dictionary to a DataFrame
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df = pd.DataFrame(list(data_dict.items()), columns=['From-To', 'kWh'])
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df[['From', 'To']] = pd.DataFrame(df['From-To'].tolist(), index=df.index)
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df['kWh'] = df['kWh'] * J_to_kWh
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df = df[['From', 'To', 'kWh']]
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df.to_excel(writer, sheet_name=season, index=False)

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