Metadata-Version: 2.1
Name: esa
Version: 0.5.1
Summary: A python package that makes PowerWorld Simauto easier yet more powerful to use
Home-page: https://github.com/mzy2240/ESA
Author: Zeyu Mao, Brandon Thayer
Author-email: zeyumao2@tamu.edu, blthayer@tamu.edu
License: MIT
Description: # Easy SimAuto (ESA)
        This Python package provides an easy to use and light-weight wrapper for
        interfacing with PowerWorld's Simulator Automation Server (SimAuto). 
        
        ## Why Use ESA?
        Directly interacting with PowerWorld via the Windows COM object can be
        quite cumbersome. Data type inputs and outputs can be odd, returns
        come back unlabeled, and you have to use pywin32 to interface with
        SimAuto. 
        
        ESA makes all these tasks quick and easy, is well documented, 
        automagically translates data to the appropriate types, and uses 
        Pandas DataFrames and Series where possible. For some motivating 
        examples, please the the "Quick Start" section of this document.
        
        ## Citation
        If you use ESA in any of your work, please use the following citation:
        ```latex
        @misc{ESA,
          author = {Zeyu Mao and Brandon Thayer},
          title = {Easy SimAuto (ESA)},
          year = {2019},
          publisher = {GitHub},
          journal = {GitHub repository},
          howpublished = {\url{https://github.com/mzy2240/ESA}},
          commit = {<copy + paste the specific commit you used here>}
        }
        ```
        
        ## Documentation
        ESA is documented [here](https://mzy2240.github.io/ESA/).
        
        ## Quick Start
        The following quick start example uses the IEEE 14 bus case, which can
        be found [in the repository](https://github.com/mzy2240/ESA/tree/master/tests/cases/ieee_14)
        or from [Texas A&M](https://electricgrids.engr.tamu.edu/electric-grid-test-cases/ieee-14-bus-system/).
        
        You can find API documentation [here](https://mzy2240.github.io/ESA/html/index.html).
        ```python
        # Import the SimAuto Wrapper (SAW)
        >>> from esa import SAW
        
        # Initialize SAW instance using 14 bus test case. Adapt path as needed
        # for your file system.
        >>> saw = SAW(FileName=r'C:\Users\myuser\git\ESA\tests\cases\ieee_14\IEEE 14 bus.pwb')
        
        # Solve the power flow.
        >>> saw.SolvePowerFlow()
        
        # Retrieve power flow results for buses. This will return a Pandas 
        # DataFrame to make your life easier.
        >>> bus_data = saw.get_power_flow_results('bus')
        >>> print(bus_data)
            BusNum BusName  BusPUVolt   BusAngle    BusNetMW  BusNetMVR
        0        1   Bus 1   1.060000   0.000000  232.391691 -16.549389
        1        2   Bus 2   1.045000  -4.982553   18.300001  30.855957
        2        3   Bus 3   1.010000 -12.725027  -94.199997   6.074852
        3        4   Bus 4   1.017672 -10.312829  -47.799999   3.900000
        4        5   Bus 5   1.019515  -8.773799   -7.600000  -1.600000
        5        6   Bus 6   1.070000 -14.220869  -11.200000   5.229700
        6        7   Bus 7   1.061520 -13.359558    0.000000   0.000000
        7        8   Bus 8   1.090000 -13.359571    0.000000  17.623067
        8        9   Bus 9   1.055933 -14.938458  -29.499999   4.584888
        9       10  Bus 10   1.050986 -15.097221   -9.000000  -5.800000
        10      11  Bus 11   1.056907 -14.790552   -3.500000  -1.800000
        11      12  Bus 12   1.055189 -15.075512   -6.100000  -1.600000
        12      13  Bus 13   1.050383 -15.156196  -13.500001  -5.800000
        13      14  Bus 14   1.035531 -16.033565  -14.900000  -5.000000
        
        # Retrieve power flow results for generators.
        >>> gen_data = saw.get_power_flow_results('gen')
        >>> print(gen_data)
           BusNum GenID       GenMW     GenMVR
        0       1     1  232.391691 -16.549389
        1       2     1   40.000001  43.555957
        2       3     1    0.000000  25.074852
        3       6     1    0.000000  12.729700
        4       8     1    0.000000  17.623067
        
        # Let's change generator injections! But first, we need to know which 
        # fields PowerWorld needs in order to identify generators. These fields
        # are known as key fields.
        >>> gen_key_fields = saw.get_key_fields_for_object_type('gen')
        >>> print(gen_key_fields['internal_field_name'])
        key_field_index
        0    BusNum
        1     GenID
        Name: internal_field_name, dtype: object
        >>> key_fields = gen_key_fields['internal_field_name'].tolist()
        >>> print(key_fields)
        ['BusNum', 'GenID']
        
        # Change generator active power injection at buses 3 and 8 via SimAuto
        # function.
        >>> params = key_fields + ['GenMW']
        >>> values = [[3, '1', 30], [8, '1', 50]]
        >>> saw.ChangeParametersMultipleElement(ObjectType='gen', ParamList=params, ValueList=values)
        
        # Did it work? Spoiler: it does!
        >>> new_gen_data = saw.GetParametersMultipleElement(ObjectType='gen', ParamList=params)
        >>> print(new_gen_data)
           BusNum GenID       GenMW
        0       1     1  232.391691
        1       2     1   40.000001
        2       3     1   30.000001
        3       6     1    0.000000
        4       8     1   50.000000
        
        # It would seem the generator active power injections have changed. Let's 
        # re-run the power flow and see if bus voltages and angles change. Spoiler:
        # they do.
        >>> saw.SolvePowerFlow()
        >>> new_bus_data = saw.get_power_flow_results('bus')
        >>> cols = ['BusPUVolt', 'BusAngle']
        >>> print(bus_data[cols] - new_bus_data[cols])
               BusPUVolt   BusAngle
        0   0.000000e+00   0.000000
        1  -1.100000e-07  -2.015596
        2  -5.700000e-07  -4.813164
        3  -8.650700e-03  -3.920185
        4  -7.207540e-03  -3.238592
        5  -5.900000e-07  -4.586528
        6  -4.628790e-03  -7.309167
        7  -3.190000e-06 -11.655362
        8  -7.189370e-03  -6.284631
        9  -6.256150e-03  -5.987861
        10 -3.514030e-03  -5.297895
        11 -2.400800e-04  -4.709888
        12 -1.351040e-03  -4.827348
        13 -4.736110e-03  -5.662158
        
        # Wouldn't it be easier if we could change parameters with a DataFrame?
        # Wouldn't it be nice if we didn't have to manually check if our updates
        # were respected? You're in luck!
        #
        # Create a copy of the gen_data DataFrame so that we can modify its 
        # values and use it to update parameters in PowerWorld.
        >>> gen_copy = gen_data.copy()
        # Change generation at buses 2, 3 and 6.
        >>> gen_copy.loc[gen_copy['BusNum'].isin([2, 3, 6]), 'GenMW'] = [0.0, 100.0, 100.0]
        >>> print(gen_copy)
           BusNum GenID       GenMW     GenMVR
        0       1     1  232.391691 -16.549389
        1       2     1    0.000000  43.555957
        2       3     1  100.000000  25.074852
        3       6     1  100.000000  12.729700
        4       8     1    0.000000  17.623067
        
        # Use helper function to both command the generators and to confirm that
        # PowerWorld respected the command. This is incredibly useful because
        # if you directly use ChangeParametersMultipleElements, PowerWorld may
        # unexpectedly not update the parameter you tried to change! If the 
        # following does not raise an exception, we're in good shape (it doesn't)!
        >>> saw.change_and_confirm_params_multiple_element(ObjectType='gen', command_df=gen_copy.drop('GenMVR', axis=1))
        
        # Run the power flow and observe the change in generation at the slack
        # bus (bus 1).
        >>> saw.SolvePowerFlow()
        >>> print(saw.get_power_flow_results('gen'))
           BusNum GenID       GenMW     GenMVR
        0       1     1   62.128144  14.986289
        1       2     1    0.000000  10.385347
        2       3     1  100.000000   0.000000
        3       6     1  100.000000  -3.893420
        4       8     1    0.000000  17.399502
        
        # What if we try to change generator voltage set points? Start by getting
        # a DataFrame with the current settings. Remember to always access the
        # key fields so that when we want to update parameters later PowerWorld
        # knows how to find the generators.
        >>> gen_v = saw.GetParametersMultipleElement('gen', key_fields + ['GenRegPUVolt'])
        >>> print(gen_v)
           BusNum GenID  GenRegPUVolt
        0       1     1      1.060000
        1       2     1      1.045000
        2       3     1      1.010001
        3       6     1      1.070001
        4       8     1      1.090003
        >>> gen_v['GenRegPUVolt'] = 1.0
        >>> print(gen_v)
           BusNum GenID  GenRegPUVolt
        0       1     1           1.0
        1       2     1           1.0
        2       3     1           1.0
        3       6     1           1.0
        4       8     1           1.0
        >>> saw.change_and_confirm_params_multiple_element('gen', gen_v)
        Traceback (most recent call last):
          File "<stdin>", line 1, in <module>
          File "C:\Users\blthayer\git\gym-powerworld\venv\lib\site-packages\esa\saw.py", line 201, in change_and_confirm_params_multiple_element
            raise CommandNotRespectedError(m)
        esa.saw.CommandNotRespectedError: After calling ChangeParametersMultipleElement, not all parameters were actually changed within PowerWorld. Try again with a different parameter (e.g. use GenVoltSet instead of GenRegPUVolt).
        
        # So, PowerWorld didn't respect that command, but we've been saved from
        # future confusion by the helper function.
        
        # Let's call the LoadState SimAuto function.
        >>> saw.LoadState()
        Traceback (most recent call last):
          File "<stdin>", line 1, in <module>
          File "C:\Users\blthayer\git\gym-powerworld\venv\lib\site-packages\esa\saw.py", line 635, in LoadState
            raise NotImplementedError(NIE_MSG)
        NotImplementedError: This method is either not complete or untested. We appreciate contributions, so if you would like to complete and test this method, please read contributing.md. If there is commented out code, you can uncomment it and re-install esa from source at your own risk.
        
        # This behavior is expected - if we have not implemented/tested a SimAuto
        # function, it will raise a NotImplementedError.
        ```
        
        ## Pre-requisites
        - Microsoft Windows 10 Operating System (PowerWorld is Windows only).
        - PowerWorld Simulator with SimAuto add-on installed.
        - [Git Large File Storage (LFS)](https://git-lfs.github.com/)
        (**OPTIONAL**: required to download case files and run tests). After
        installing Git LFS, simply change directories to this repository, and
        run `git lfs install`. You will likely need to run a `git pull` or
        `git lfs pull` after installing and setting up Git LFS. After initial
        setup, you shouldn't need to do anything else with Git LFS.
        - Python >=3.5.
        
        ### Notes on Python versions
        The authors of ESA have tested with Python 3.5,
        3.6, 3.7, and 3.8. Many users may find it easiest to use Anaconda,
        but this is not recommended for users familiar with using Pip and/or
        virtual environments directly (or via PyCharm), as Anaconda provides an
        unnecessarily bloated installation.
        
        #### Important Notes for PyCharm + Python 3.8
        If you use PyCharm to automatically create virtual environments for you,
        there's a little extra work to do to get everything working for Python
        3.8. Start up a terminal *inside* PyCharm (click on the `Terminal` 
        button which defaults to the lower left area). In the terminal, run:
        `python -m pip install -U --force-reinstall pip`. Note you may need to
        run this command twice - mine failed the first time.
        
        ## Installation
        This section covers installation via Pip, installation from source, and
        some __important__ post installation steps that **must** be taken.
        
        ### Installation with Pip (easiest)
        Use the Python package manager [pip](https://pip.pypa.io/en/stable/) to
        install ESA:
        
        ```bash
        pip install esa
        ```
        
        ### Installation from Source
        If you want to make modifications to ESA for your own purposes, you'll
        likely want to clone the Git repository and install from source. 
        Fortunately, this is quite easy. The following directions will assume
        that your project is at `C:\Users\myuser\git\myproject` and that your
        virtual environment is at `C:\Users\myuser\git\myproject\venv`. If 
        you're new to virtual environments, Python provides a nice
        [tutorial](https://docs.python.org/3/tutorial/venv.html).
        
        Start by cloning ESA into `C:\Users\myuser\git\ESA`. This can be 
        accomplished in a variety of ways, but perhaps the simplest is by using
        Git Bash:
        ```
        cd ~/git
        git clone https://github.com/mzy2240/ESA.git
        ```
        
        After the cloning has completed, close Git Bash and open up a command
        prompt. Run the following:
        
        ```cmd
        cd C:\Users\myuser\git\myproject
        venv\Scripts\activate.bat
        ```
        
        Your prompt should change to be prefixed by `(venv)` indicating that 
        your virtual environment has been activated. Now, perform the following:
        
        ```cmd
        cd ../ESA
        python setup.py install
        ```
        
        ### Post-Installation (optional)
        You need to run a post-installation script related to a
        pre-requisite Python package, [pywin32](https://github.com/mhammond/pywin32).
        As per pywin32's directions, you'll need to run the following with
        an __elevated__ (administrator) command prompt after navigating to your
        virtual environment's directory:
        ```cmd
        Scripts\activate.bat
        python Scripts/pywin32_postinstall.py -install
        ```
        (this `Scripts` directory can be found within your virtual environment
        where your Python packages are installed. If you followed along in the
        "Installation from Source" example, this `Scripts` directory would be
        found at `C:\Users\myuser\git\myproject\venv`.)
        
        ## License
        [MIT](https://choosealicense.com/licenses/mit/)
        
        ## Contributing
        We welcome contributions! Please read out `contributing.md`.
        
Platform: UNKNOWN
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: Microsoft :: Windows :: Windows 10
Description-Content-Type: text/markdown
