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Wang
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Added scenario with same random setpoints
1 parent 66a626d commit 22637ac

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‎office/winter/option1/same_random_sp/b.csv

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‎office/winter/option1/same_random_sp/closeloop_dataprocess.py

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import numpy as np
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import pandas as pd
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import json
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#coe1=json.load(open('zone1_result'))
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#coe2=json.load(open('zone2_result'))
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#coe3=json.load(open('zone3_result'))
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coe4=json.load(open('zone4_result'))
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coe5=json.load(open('zone5_result'))
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#coe6=json.load(open('zone6_result'))
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#coe7=json.load(open('zone7_result'))
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c1=['constant','tout','s','i','t1','t2','sp0','m','rh']
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print len(coe4)
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print len(coe5)
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print len(c1)
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"""
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tab1=pd.read_csv('zone4-1validation.csv')
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sum1=[0]*len(tab1)
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for i in range(len(coe1)-1):
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sum1=sum1+coe1['a'+str(i+1)]*tab1[c1[i+1]]
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sum1=sum1+coe1['a0']*len(tab1)
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#c2=['Tout','s','i','hsp','csp0','csp1','csp2','csp3','csp4','csp5','m0','m1','m2','m3','m4','m5','rh0','rh1','rh2','rh3','rh4','rh5']
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tab2=pd.read_csv('zone4-2validation.csv')
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sum2=[0]*len(tab2)
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for i in range(len(coe2)-1):
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sum2=sum2+coe2['a'+str(i+1)]*tab2[c1[i+1]]
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sum2=sum2+coe2['a0']*len(tab2)
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#c3=['Tout','s','i','hsp','csp0','csp1','csp2','m0','m1','m2','rh0','rh1','rh2']
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tab3=pd.read_csv('zone4-3validation.csv')
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sum3=[0]*len(tab3)
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for i in range(len(coe3)-1):
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sum3=sum3+coe3['a'+str(i+1)]*tab3[c1[i+1]]
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sum3=sum3+coe3['a0']*len(tab3)
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"""
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#c4=['Tout','s','i','hsp','csp0','m0','rh0']
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tab4=pd.read_csv('zone4validation.csv')
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sum4=[0]*len(tab4)
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sum4=coe4['a0']+coe4['a1']*tab4['tout']+coe4['a2']*tab4['s']+coe4['a3']*tab4['i']+coe4['a6']*tab4['sp']+coe4['a7']*tab4['m']+coe4['a8']*tab4['rh']
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#for i in range(len(coe4)-1):
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# sum4=sum4+coe4['a'+str(i+1)]*tab4[c1[i+1]]
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#sum4=sum4+coe4['a0']*len(tab4)
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tab5=pd.read_csv('zone5validation.csv')
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sum5=[0]*len(tab5)
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sum5=coe5['a0']+coe5['a1']*tab5['tout']+coe5['a2']*tab5['s']+coe5['a3']*tab5['i']+coe5['a6']*tab5['m']
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#sum5=[0]*len(tab5)
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#for i in range(len(coe5)-1):
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# sum5=sum5+coe5['a'+str(i+1)]*tab5[c1[i+1]]
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#sum5=sum5+coe5['a0']*len(tab5)
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tab=pd.DataFrame()
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"""
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tab['b1']=sum1
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tab['b2']=sum2
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tab['b3']=sum3
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"""
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tab['b4']=sum4
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tab['b5']=sum5
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tab.to_csv('b.csv')
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tab2=pd.DataFrame()
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#tab2['t1']=tab1['t1']
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#tab2['t2']=tab2['t1']
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#tab2['t3']=tab3['t1']
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tab2['t4']=tab4['t1']
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tab2['t5']=tab5['t1']
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tab2.to_csv('x0.csv')
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‎office/winter/option1/same_random_sp/data_process_plenum.py

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import pandas as pd
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import json
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filename='zone5'
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info = json.load(open(filename))
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tab=pd.read_csv('eplusout.csv')
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# solar radiation
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sol=[]
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for key in info["solar"]:
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sol.append(info["solar"][key])
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# zone information
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zones=[]
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for key in sorted(info["inputs"]["zones"]):
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zones.append(info["inputs"]["zones"][key])
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adjzones=[]
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for key in sorted(info["inputs"]["adjzones"]):
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adjzones.append(info["inputs"]["adjzones"][key])
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# terminal information
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termoutlet=[]
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for key in sorted(info["inputs"]["termoutlet"]):
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termoutlet.append(info["inputs"]["termoutlet"][key])
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tout=info["tout"]
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#hsp=info["hsp"]
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zmt=[]
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adjt=[]
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zmdm=[] # zone supply air flow rate
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zmdt=[] # zone supply air temperature
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int=[] # internal load
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inlet=[] # reheat coil inlet water temperature
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outlet=[] # reheat coil outlet water temperature
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mrh=[] # reheat coil water mass flow rate
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#rh=[]
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#sol=['Environment:Site Diffuse Solar Radiation Rate per Area [W/m2](TimeStep)','Environment:Site Direct Solar Radiation Rate per Area [W/m2](TimeStep)']
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for i in range(len(zones)):
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zmt.append(str(zones[i]).upper()+':Zone Mean Air Temperature [C](TimeStep)')
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int.append(str(zones[i]).upper()+':Zone Total Internal Total Heating Rate [W](TimeStep)')
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zmdm.append(str(termoutlet[i]).upper()+':System Node Mass Flow Rate [kg/s](TimeStep)')
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zmdt.append(str(termoutlet[i]).upper()+':System Node Temperature [C](TimeStep)')
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# inlet.append(str(rhtinlet[i]).upper()+':System Node Temperature [C](TimeStep)')
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# outlet.append(str(rhtoutlet[i]).upper()+':System Node Temperature [C](TimeStep)')
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# mrh.append(str(rhtoutlet[i]).upper()+':System Node Mass Flow Rate [kg/s](TimeStep)')
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#rh.append(str(zones[i]).upper()+' RHT COIL:Heating Coil Heating Rate [W](TimeStep)')
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for i in range(len(adjzones)):
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adjt.append(str(adjzones[i]).upper()+':Zone Mean Air Temperature [C](TimeStep)')
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tab['t1']=[0]*len(tab)
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tab['m1']=[0]*len(tab)
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tab['i']=[0]*len(tab)
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tab['s']=[0]*len(tab)
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#tab['rh']=[0]*len(tab)
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for i in range(len(zones)):
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tab['t1']=tab['t1']+tab[zmt[i]]*tab[zmdm[i]]
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tab['i']=tab['i']+tab[int[i]]
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tab['m1']=tab['m1']+tab[zmdm[i]]
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# tab['rh']=tab['rh']+tab[mrh[i]]*(tab[inlet[i]]-tab[outlet[i]])*4200
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for i in range(len(sol)):
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tab['s']=tab['s']+tab[sol[i]]
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tab2=pd.DataFrame()
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#for j in range(len(walls)):
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# tab2['w'+str(j)]=tab['w'+str(j+1)]
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tab2['tout']=tab[tout]
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tab2['s']=tab['s']
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tab2['i']=tab['i']
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tab2['t1']=tab['t1']/tab['m1']
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# adjacent zone temperature
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tab3=pd.read_csv('zone4rawdata.csv')
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tab2['t2']=tab3['t1']
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#for i in range(len(adjzones)):
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# name='t'+str(i+2)
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# tab2[name]=tab[adjt[i]]
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tab2['m']=tab[zmdm[0]]
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tab2['tret']=tab[zmdt[0]]
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#name='rh'+str(i)
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#tab2[name]=tab[mrh[i]]*(tab[inlet[i]]-tab[outlet[i]])*4200
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#tab2['rh']=tab['rh']
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tab2.to_csv(filename+'rawdata.csv')

‎office/winter/option1/same_random_sp/data_process_vav.py

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import pandas as pd
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import json
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filename='zone4'
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info = json.load(open(filename))
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tab=pd.read_csv('eplusout.csv')
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# solar radiation
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sol=[]
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for key in info["solar"]:
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sol.append(info["solar"][key])
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# zone information
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zones=[]
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for key in sorted(info["inputs"]["zones"]):
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zones.append(info["inputs"]["zones"][key])
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adjzones=[]
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for key in sorted(info["inputs"]["adjzones"]):
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adjzones.append(info["inputs"]["adjzones"][key])
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# terminal information
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termoutlet=[]
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for key in sorted(info["inputs"]["termoutlet"]):
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termoutlet.append(info["inputs"]["termoutlet"][key])
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# RHT information
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rhtinlet=[]
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for key in sorted(info["inputs"]["rhtinlet"]):
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rhtinlet.append(info["inputs"]["rhtinlet"][key])
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rhtoutlet=[]
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for key in sorted(info["inputs"]["rhtoutlet"]):
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rhtoutlet.append(info["inputs"]["rhtoutlet"][key])
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"""
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# wall information
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walls=[]
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for key in sorted(info["inputs"]["walls"]):
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walls.append(info["inputs"]["walls"][key])
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wallareas=[]
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for key in info["inputs"]["wallarea"]:
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wallareas.append(info["inputs"]["wallarea"][key])
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i=1
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for key2 in info["inputs"]["walls"]:
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tab['w'+str(i)]=[0]*len(tab)
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temp=[]
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area=0
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for key in info["inputs"]["walls"][key2]:
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tab['w'+str(i)]=tab['w'+str(i)]+(tab[info["inputs"]["walls"][key2][key].upper()+
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':Surface Inside Face Temperature [C](TimeStep)']+tab[info["inputs"]["walls"][key2][key].upper()+
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':Surface Outside Face Temperature [C](TimeStep)'])/2*(info["inputs"]["wallarea"][key2][key])
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area=area+info["inputs"]["wallarea"][key2][key]
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tab['w'+str(i)]=tab['w'+str(i)]/area
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i=i+1
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"""
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tout=info["tout"]
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#hsp=info["hsp"]
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zmt=[]
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adjt=[]
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zmdm=[] # zone supply air flow rate
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zmdt=[] # zone supply air temperature
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int=[] # internal load
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inlet=[] # reheat coil inlet water temperature
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outlet=[] # reheat coil outlet water temperature
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mrh=[] # reheat coil water mass flow rate
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#rh=[]
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#sol=['Environment:Site Diffuse Solar Radiation Rate per Area [W/m2](TimeStep)','Environment:Site Direct Solar Radiation Rate per Area [W/m2](TimeStep)']
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for i in range(len(zones)):
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zmt.append(str(zones[i]).upper()+':Zone Mean Air Temperature [C](TimeStep)')
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int.append(str(zones[i]).upper()+':Zone Total Internal Total Heating Rate [W](TimeStep)')
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zmdm.append(str(termoutlet[i]).upper()+':System Node Mass Flow Rate [kg/s](TimeStep)')
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zmdt.append(str(termoutlet[i]).upper()+'System Node Temperature [C](TimeStep)')
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inlet.append(str(rhtinlet[i]).upper()+':System Node Temperature [C](TimeStep)')
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outlet.append(str(rhtoutlet[i]).upper()+':System Node Temperature [C](TimeStep)')
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mrh.append(str(rhtoutlet[i]).upper()+':System Node Mass Flow Rate [kg/s](TimeStep)')
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#rh.append(str(zones[i]).upper()+' RHT COIL:Heating Coil Heating Rate [W](TimeStep)')
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for i in range(len(adjzones)):
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adjt.append(str(adjzones[i]).upper()+':Zone Mean Air Temperature [C](TimeStep)')
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tab['t1']=[0]*len(tab)
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tab['m1']=[0]*len(tab)
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tab['i']=[0]*len(tab)
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tab['s']=[0]*len(tab)
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tab['rh']=[0]*len(tab)
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for i in range(len(zones)):
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tab['t1']=tab['t1']+tab[zmt[i]]*tab[zmdm[i]]
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tab['i']=tab['i']+tab[int[i]]
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tab['m1']=tab['m1']+tab[zmdm[i]]
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tab['rh']=tab['rh']+tab[mrh[i]]*(tab[inlet[i]]-tab[outlet[i]])*4200
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for i in range(len(sol)):
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tab['s']=tab['s']+tab[sol[i]]
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tab2=pd.DataFrame()
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#for j in range(len(walls)):
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# tab2['w'+str(j)]=tab['w'+str(j+1)]
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tab2['tout']=tab[tout]
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tab2['s']=tab['s']
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tab2['i']=tab['i']
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tab2['t1']=tab['t1']/tab['m1']
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# for cav system
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if tab['m1'][0]==0:
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tab2['t1']=tab[zmt[0]]
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for i in range(len(adjzones)):
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name='t'+str(i+2)
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tab2[name]=tab[adjt[i]]
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for i in range(len(zones)):
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name='sp'+str(i)
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tab2[name]=tab[str(zones[i]).upper()+':Zone Thermostat Heating Setpoint Temperature [C](TimeStep)']
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#name='m'+str(i)
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#tab2[name]=tab[zmdm[i]]
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#name='rh'+str(i)
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#tab2[name]=tab[mrh[i]]*(tab[inlet[i]]-tab[outlet[i]])*4200
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tab2['sp']=(tab2['sp0']+tab2['sp1']+tab2['sp2']+tab2['sp3']+tab2['sp4'])/5
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tab2['m']=tab['m1']
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tab2['rh']=tab['rh']
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tab2.to_csv(filename+'rawdata.csv')

‎office/winter/option1/same_random_sp/eplusout.csv

+8,929
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