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Check the post "MPjobs tool for PSSe runs in Parallel". It has a link to download my tool, MPjobs and it includes a critical clearing time (CCT) study example. Follow the instruction in the readme.txt file. The data input is in cct1d.ini and the code that runs the study is in scripts\cct1d.py.
In this example, MPjobs runs multiple instances of cct1d.py according to data defined in cct1d.ini. The corresponding *.out and *.log created will have to be analyzed to assert CCT outcome. If a specific channels is monitored, plots of that channels for the multiple *.out files can be done to visualize the CCT outcome (for plotting check the post "Channels - tool to process outs files").

Check the post "MPjobs tool for PSSe runs in Parallel". It has a link to download my tool, MPjobs and it includes a critical clearing time (CCT) study example. Follow the instruction in the readme.txt file. The data input is in cct1d.ini and the code that runs the study is in scripts\cct1d.py. scripts\cct_1d.py.
In this example, MPjobs runs multiple instances of cct1d.py according to data defined in cct1d.ini. cct_1d.ini. The corresponding *.out and *.log created will have to be analyzed to assert CCT outcome. If a specific channels is monitored, plots of that channels for the multiple *.out files can be done to visualize the CCT outcome (for plotting check the post "Channels - tool to process outs files").

Check the post "MPjobs tool for PSSe runs in Parallel". It has a link to download my tool, MPjobs and it includes a critical clearing time (CCT) study example. Follow the instruction in the readme.txt file.
The CCT data input is in cct1d.ini and the code that runs the study is in scripts\cct_1d.py.
In this example, MPjobs runs multiple instances of cct1d.py according to data defined in cct_1d.ini. The corresponding *.out and *.log created will have to be analyzed to assert CCT outcome.
If a specific channels is are monitored, plots of that those channels for the multiple *.out files can be done to visualize the CCT outcome (for plotting check the post "Channels - tool to process outs files").

Check the post "MPjobs tool for PSSe runs in Parallel". It has a link to download my tool, MPjobs and it includes a critical clearing time (CCT) study example. Follow the instruction in the readme.txt file.
The CCT data input is in cct1d.ini and the code that runs the study is in scripts\cct_1d.py. In this example, MPjobs runs multiple instances of cct1d.py according to data defined in cct_1d.ini. The corresponding *.out and *.log created will have to be analyzed to assert CCT outcome.

The cct_1d.py expects to find a converted case and a snap file in the path specified in the ini file. When you have a non-converted case and a dyr file, the converted case and snap file can be created with the following script:

psspy.case('my.sav')
psspy.conl(0,1,1,[0,0],[ 100.0,0.0,0.0, 100.0])
psspy.conl(0,1,2,[0,0],[ 100.0,0.0,0.0, 100.0])
psspy.conl(0,1,3,[0,0],[ 100.0,0.0,0.0, 100.0])
psspy.cong()
psspy.ordr(0)
psspy.fact()
psspy.tysl(0)
psspy.tysl(0)
psspy.save('my_cnv.sav')

#** Read DYRE records -  system dynamics + solar PV dynamics
psspy.dyre_new([1,1,1,1],'my.dyr','','','')
#** Save snapshot for dynamics
psspy.snap([-1,-1,-1,-1,-1],'my.snp')

If specific channels are monitored, plots of those channels for the multiple *.out files can be done to visualize the CCT outcome (for plotting check the post "Channels - tool to process outs files").

Check the post "MPjobs tool for PSSe runs in Parallel". It has a link to download my tool, MPjobs and it includes a critical clearing time (CCT) study example. Follow the instruction in the readme.txt file.
The CCT data input is in cct1d.ini cct_1d.ini and the code that runs the study is in scripts\cct_1d.py. In this example, MPjobs runs multiple instances of cct1d.py cct_1d.py according to data defined in cct_1d.ini. The corresponding *.out and *.log created will have to be analyzed to assert CCT outcome.

The cct_1d.py cct_1d.py expects to find a converted case and a snap file in the path specified in the ini file. When you have a non-converted case and a dyr file, the converted case and snap file can be created with the following script:

psspy.case('my.sav')
psspy.conl(0,1,1,[0,0],[ 100.0,0.0,0.0, 100.0])
psspy.conl(0,1,2,[0,0],[ 100.0,0.0,0.0, 100.0])
psspy.conl(0,1,3,[0,0],[ 100.0,0.0,0.0, 100.0])
psspy.cong()
psspy.ordr(0)
psspy.fact()
psspy.tysl(0)
psspy.tysl(0)
psspy.save('my_cnv.sav')

#** Read DYRE records -  system dynamics + solar PV dynamics
psspy.dyre_new([1,1,1,1],'my.dyr','','','')
#** Save snapshot for dynamics
psspy.snap([-1,-1,-1,-1,-1],'my.snp')

If specific channels are monitored, plots of those channels for the multiple *.out files can be done to visualize the CCT outcome (for plotting check the post "Channels - tool to process outs files").