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ANDES can be used as a command-line tool or a library. The command-line interface (CLI) comes handy to run studies. As a library, it can be used interactively in the IPython shell or the Jupyter Notebook. This chapter describes the most common usages.
Please see the cheatsheet if you are looking for quick help.
ANDES is invoked from the command line using the command andes.
Running andes without any input is equal to andes -h or andes --help. It prints out a preamble with version and environment
information and help commands:
ANDES 0.6.8 (Git commit id 0ace2bc0, Python 3.7.6 on Darwin)
Session: hcui7, 02/09/2020 08:34:35 PM
usage: andes [-h] [-v {10,20,30,40,50}] {run,plot,misc,prepare,selftest} ...
positional arguments:
{run,plot,misc,prepare,selftest}
[run]: run simulation routine; [plot]: plot simulation
results; [prepare]: run the symbolic-to-numeric
preparation; [misc]: miscellaneous functions.
optional arguments:
-h, --help show this help message and exit
-v {10,20,30,40,50}, --verbose {10,20,30,40,50}
Program logging level. Available levels are 10-DEBUG,
20-INFO, 30-WARNING, 40-ERROR or 50-CRITICAL. The
default level is 20-INFO.
The first level of commands are chosen from
{run,plot,misc,prepare,selftest}. Each command contains a group of
subcommands, which can be looked up with -h. For example, use andes run -h to look up the subcommands in run. The most commonly used
commands will be explained in the following.
andes has an option for the program verbosity level, controlled by
-v or --verbose. Accpeted levels are the same as in the logging
module: 10 - DEBUG, 20 - INFO, 30 - WARNING, 40 - ERROR, 50 - CRITICAL.
To show debugging outputs, use -v 10.
After installing ANDES, it is encouraged to use andes selftest to run
tests and check the basic functionality. It might take a minute to run
the whole self-test suite. Results are printed as the tests proceed. An
example output looks like :
ANDES 0.6.8 (Git commit id 0ace2bc0, Python 3.7.6 on Darwin)
Session: hcui7, 02/09/2020 08:44:07 PM
test_docs (test_1st_system.TestSystem) ... ok
test_limiter (test_discrete.TestDiscrete) ... ok
test_sorted_limiter (test_discrete.TestDiscrete) ... ok
test_switcher (test_discrete.TestDiscrete) ... ok
test_pflow_mpc (test_pflow_matpower.TestMATPOWER) ... ok
test_count (test_pjm.Test5Bus) ... ok
test_idx (test_pjm.Test5Bus) ... ok
test_names (test_pjm.Test5Bus) ... ok
test_pflow (test_pjm.Test5Bus) ... ok
100%|██████████████████████████████████████████| 100/100 [00:02<00:00, 39.29%/s]
ok
----------------------------------------------------------------------
Ran 10 tests in 21.289s
OK
Test cases can grow, and there could be more cases than above. Make sure that all tests have passed.
The symbolically defined models in ANDES need to be generated into
numerical code for simulation. The code generation can be manually
called with andes prepare. Generated code are stored in folder
.andes/calls.pkl in your home directory. In addition, andes selftest
implicitly calls the code generation. If you are using ANDES as a
package in the user mode, you won't need to call it again.
For developers, andes prepare needs to be called immediately following
any model equation modification. Otherwise, simulation results will not
reflect the new equations and will likely lead to an error.
Option -q or --quick can be used to speed up the code generation. It
skips the generation of LaTeX-formatted equations, which are only used
in documentation and the interactive mode.
andes run is the entry point for power system analysis routines.
andes run takes one positional argument, filename , along with other
optional keyword arguments. filename is the test case path, either
relative or absolute. Without other options, ANDES will run power flow
calculation for the provided file.
Option -r or -routine is used for specifying the analysis routine,
followed by the routine name. Available routine names include pflow, tds, eig. pflow for power flow,
tds for time domain simulation, and
eig for eigenvalue analysis.
pflow is default even if -r is not
given.
For example, to run time-domain simulation for kundur_full.xlsx in the
current directory, run
andes run kundur_full.xlsx -r tdsTwo output files, kundur_full_out.lst and kundur_full_out.npy will
be created for variable names and values, respectively.
Likewise, to run eigenvalue analysis for kundur_full.xlsx, use
andes run kundur_full.xlsx -r eigThe eigenvalue report will be written in a text file named
kundur_full_eig.txt.
To perform a power flow study for test case named kundur_full.xlsx in
the current directory, run
andes run kundur_full.xlsxThe full path to the case file is also accepted, for example,
andes run /home/user/andes/cases/kundur/kundur_full.xlsxPower flow reports will be saved to the current directory in which andes is called. The power flow report contains four sections: a) system statistics, b) ac bus and dc node data, c) ac line data, and d) the initialized values of other algebraic variables and state variables.
To run the time domain simulation (TDS) for kundur_full.xlsx, run
andes run kundur_full.xlsx -r tdsThe output looks like:
ANDES 0.6.8 (Git commit id 0ace2bc0, Python 3.7.6 on Darwin)
Session: hcui7, 02/09/2020 10:35:37 PM
Parsing input file </Users/hcui7/repos/andes/tests/kundur_full.xlsx>
Input file kundur_full.xlsx parsed in 0.5425 second.
-> Power flow calculation with Newton Raphson method:
0: |F(x)| = 14.9283
1: |F(x)| = 3.60859
2: |F(x)| = 0.170093
3: |F(x)| = 0.00203827
4: |F(x)| = 3.76414e-07
Converged in 5 iterations in 0.0080 second.
Report saved to </Users/hcui7/repos/andes/tests/kundur_full_out.txt> in 0.0036 second.
-> Time Domain Simulation:
Initialization tests passed.
Initialization successful in 0.0152 second.
0%| | 0/100 [00:00<?, ?%/s]
<Toggle 0>: Applying status toggle on Line idx=Line_8
100%|██████████████████████████████████████████| 100/100 [00:03<00:00, 28.99%/s]
Simulation completed in 3.4500 seconds.
TDS outputs saved in 0.0377 second.
-> Single process finished in 4.4310 seconds.
This execution first solves the power flow as a starting point. Next, the numerical integration simulates 20 seconds, during which a predefined breaker opensat 2 seconds.
TDS produces two output files by default: a NumPy data file
ieee14_syn_out.npy and a variable name list file ieee14_syn_out.lst.
The list file contains three columns: variable indices, variabla name in
plain text, and variable name in LaTeX format. The variable indices are
needed to plot the needed variable.
ANDES takes multiple files inputs or wildcard. Multiprocessing will be
triggered if more than one valid input files are found. For example, to
run power flow for files with a prefix of case5 and a suffix (file
extension) of .m, run
andes run case5*.mTest cases that match the pattern, including case5.m and case57.m,
will be processed.
ANDES recognizes a few input formats and can convert input systems into
the xlsx format. This function is useful when one wants to use models
that are unique in ANDES.
The command for converting is --convert, following the output format
(only xlsx is currently supported). For example, to convert case5.m
into the xlsx format, run
andes run case5.m --convert xlsxThe output will look like :
ANDES 0.6.8 (Git commit id 0ace2bc0, Python 3.7.6 on Darwin)
Session: hcui7, 02/09/2020 10:22:14 PM
Parsing input file </Users/hcui7/repos/andes/cases/matpower/case5.m>
CASE5 Power flow data for modified 5 bus, 5 gen case based on PJM 5-bus system
Input file case5.m parsed in 0.0033 second.
xlsx file written to </Users/hcui7/repos/andes/cases/matpower/case5.xlsx>
Converted file /Users/hcui7/repos/andes/cases/matpower/case5.xlsx written in 0.5079 second.
-> Single process finished in 0.8765 second.
Note that --convert will only create sheets for existing models. In
case one want to create template sheets to add models later,
--convertall can be used instead.
andes plot is the command-line tool for plotting. It currently
supports time-domain simulation data. Three positional arguments are
required, and a dozen of optional arguments are supported.
-
positional arguments:
Argument Description datfile dat file name. x x axis variable index y y axis variable index
For example, to plot the generator speed variable of synchronous
generator 1 omega Syn 1 versus time, read the indices of the variable
(44) and time (0), run
andes plot ieee14_syn_out.npy 0 44In this command, - ande splot is a plotting command for TDS output
files. ieee14_syn_out.npy is data file name. 0 is the index of
Time for the x-axis. 44 is the index of omega Syn 1.
The y-axis variabla indices can also be specified in the Python range
fashion . For example, andes plot ieee14_syn_out.npy 0 44:69:6 will
plot the variables at indices 44, 50, 56, 62, and 68.
andes plot will attempt to render the image with LaTeX if dvipng
program is in the search path. In case LaTeX is available but fails
(happens on Windows), the option -d can be used to disable LaTeX
rendering.
Other optional arguments are listed in the following.
-
optional arguments:
Argument Description -h, --help show this help message and exit --xmin LEFT x axis minimum value --xmax RIGHT x axis maximum value --ymax YMAX y axis maximum value --ymin YMIN y axis minimum value --checkinit -x XLABEL, --xlabel XLABEL
-y YLABEL, --ylabel YLABEL
check initialization value
manual x-axis text label
y-axis text label
-s, --save save to file -g, --grid grid on -d, --no_latex disable LaTex formatting -n, --no_show do not show the plot window --ytimes YTIMES y times --dpi DPI image resolution in dot per inch (DPI)
andes misc contains miscellaneous functions, such as configuration and
output cleaning.
ANDES uses a configuration file to set runtime configs for the system
routines, and models. --save-config saves all configs to a file. By
default, it saves to ~/.andes/andes.conf file.
With --edit-config, you can edit the configuration of ANDES run by
saving the config and editing it.
Run andes misc --save-config to save the config file to the default
location. Then, run andes misc --edit-config to edit it. On Microsoft
Windows, it will open up a notepad. On Linux, it will use the $EDITOR
environment variable or use gedit by default. On macOS, the default is
vim.
-C, --clean
Option to remove any generated files. Removes files with any of the
following suffix: _out.txt (power flow report), _out.dat (time
domain data), _out.lst (time domain variable list), and _eig.txt
(eigenvalue report).
This section is a tutorial for using ANDES in an interactive environment. All interactive shells are supported, including Python shell, IPython, Jupyter Notebook and Jupyter Lab. The examples below uses Jupyter Notebook.
Jupyter notebook is used as an example. Jupyter notebook can be installed with
conda install jupyter notebookAfter the installation, change directory to the folder that you wish to store notebooks, start the notebook with
jupyter notebookA browser window should open automatically with the notebook browser loaded. To create a new notebook, use the "New" button at the top right corner.
Like other Python libraries, ANDES can be imported into an interactive Python environment.
>>> import andes >>> andes.main.config_logger(log_file=None)
The config_logger is needed to print logging information in the
current session. Otherwise, information messages will be silenced, and
only warnings and error will be printed.
To enable debug messages, use
>>> andes.main.config_logger(stream_level=10, log_file=None)
If you have not run andes prepare, use the command once to generate
code
>>> andes.main.prepare()
Before running studies, a "System" object needs to be create to hold the
system data. The System object can be created by passing the path to the
case file the entrypoint function. For example, to run the file
kundur_full.xlsx in the same directory as the notebook, use
>>> ss = andes.main.run('kundur_full.xlsx')
This function will parse the input file, run the power flow, and return the system as an object. Outputs will look like :
Parsing input file </Users/hcui7/notebooks/kundur/kundur_full.xlsx>
Input file kundur_full.xlsx parsed in 0.4172 second.
-> Power flow calculation with Newton Raphson method:
0: |F(x)| = 14.9283
1: |F(x)| = 3.60859
2: |F(x)| = 0.170093
3: |F(x)| = 0.00203827
4: |F(x)| = 3.76414e-07
Converged in 5 iterations in 0.0222 second.
Report saved to </Users/hcui7/notebooks/kundur_full_out.txt> in 0.0015 second.
-> Single process finished in 0.4677 second.
In this example, ss is an instance of andes.System. It contains
member attributes for models, routines, and numerical DAE.
Naming convention for the System attributes are as follows
- Model attributes share the same name as class names. For example,
ss.Busis theBusinstance. - Routine attributes share the same name as class names. For example,
ss.PFlowandss.TDSare the routine instances. - The numerical DAE instance is in lower case
ss.dae.
Parameters for the loaded system can be easily inspected in Jupyter Notebook using Pandas.
Input parameters for each model instance is in the cache.df_in
attribute. For example, to view the input parameters for Bus, use :
>>> ss.Bus.cache.df_in
A table will be printed with the columns being each parameter and the rows being Bus instances. Parameter in the table is the same as the input file without per-unit conversion.
Parameters are converted to per unit values under system base. To view
the per unit values, use the cache.df attribute. For example, to view
the system-base per unit value of GENROU, use :
>>> ss.GENROU.cache.df
Three routines are currently supported: PFlow, TDS and EIG. Each routine
provides a run() method to execute. The System instance contains
member attributes having the same names. For example, to run the
time-domain simulation for ss, use :
>>> ss.TDS.run()
TDS comes with a plotting utility for interactive usage. After running
the simulation, a Plotter attributed will be created for TDS. To use
the plotter, provide the attribute instance of the variable to plot. For
example, to plot all the generator speed, use :
>>> ss.TDS.Plotter.plot(ss.GENROU.omega)
Optional indices is accepted to choose the specific elements to plot. It
can be passed as a tuple to the a argument :
>>> ss.TDS.Plotter.plot(ss.GENROU.omega, a=(0, ))
In the above example, the speed of the "zero-th" generator will be plotted.
A lambda function can be passed to argument ycalc to scale the values.
This is useful to convert a per-unit variable to nominal. For example,
to plot generator speed in Hertz, use :
>>> ss.TDS.Plotter.plot(ss.GENROU.omega, a=(0, ),
ycalc=lambda x: 60*x,
)
A few formatting arguments are supported:
-
grid = Trueto turn on grid display -
greyscale = Trueto switch to greyscale -
ylabeltakes a string for the y-axis label
Each ANDES models offers pretty print of LaTeX-formatted equations in the jupyter notebook environment.
To use this feature, symbolic equations need to be generated in the current session using :
import dill
dill.settings['recurse'] = True
import andes
ss = andes.system.System()
ss.prepare()
This process may take several seconds to complete. Once done, equations
can be viewed by accessing ss.<ModelName>.<EquationName>_print, where
<ModelName> is the model name and <EquationName> is the equation
name.
Supported equation names include the following:
-
f: differential equations for states (\textbf{f}=\dot{x}) -
g: algebraic equations for algebraic variables (\textbf{g}=0) -
df: derivatives offover all variables -
dg: derivatives ofgover all variables -
sthe value equations for service variables
For example, to print the algebraic equations of model GENCLS, one can
use ss.GENCLS.g_print.
In addition to equations, all variable symbols can be printed at
ss.<ModelName>.vars_print.
A cheatsheet is available for quick lookup of supported commands.
View the PDF version at
https://www.cheatography.com//cuihantao/cheat-sheets/andes-for-power-system-simulation/pdf/
The documentation can be made locally into a variety of formats. To make
HTML documentation, change directory to docs, and do
make htmlAfter a minute, HTML documentation will be saved to docs/build/html
with the index page being index.html.
A list of supported formats is as follows. Note that some format require additional compiler or library :
html to make standalone HTML files
dirhtml to make HTML files named index.html in directories
singlehtml to make a single large HTML file
pickle to make pickle files
json to make JSON files
htmlhelp to make HTML files and an HTML help project
qthelp to make HTML files and a qthelp project
devhelp to make HTML files and a Devhelp project
epub to make an epub
latex to make LaTeX files, you can set PAPER=a4 or PAPER=letter
latexpdf to make LaTeX and PDF files (default pdflatex)
latexpdfja to make LaTeX files and run them through platex/dvipdfmx
text to make text files
man to make manual pages
texinfo to make Texinfo files
info to make Texinfo files and run them through makeinfo
gettext to make PO message catalogs
changes to make an overview of all changed/added/deprecated items
xml to make Docutils-native XML files
pseudoxml to make pseudoxml-XML files for display purposes
linkcheck to check all external links for integrity
doctest to run all doctests embedded in the documentation (if enabled)
coverage to run coverage check of the documentation (if enabled)