Dummy change for testing of JupyterHub Execution

32bcec09 · Marc Moritz · a03be3fb · 32bcec09
Commit 32bcec09 authored 3 weeks ago by Marc Moritz
--- a/SLEW_Case2_Electromechanical_Phenomena.ipynb
+++ b/SLEW_Case2_Electromechanical_Phenomena.ipynb
@@ -50,6 +50,7 @@
   "id": "58c9e2a2",
   "metadata": {},
   "source": [
+    "This is a test change (05.06.2025)\n",
    "A $200$ MVA round-rotor generator is connected to an infinite bus system of nominal frequency of $50 Hz$ through a step-up transformer with reactance of $0.13 p.u.$ and a transmission line with reactance of  $0.17 p.u.$ . The generator’s transient reactance is $x'_{d} = 0.23 p.u.$ and the inertia constant is $H = 4 s$. The synchronous generator mechanical power is set to $0.6 p.u.$ and the steady-state emf $E = 1.1 p.u.$"
   ]
  },

 %% Cell type:markdown id:cfe34583 tags:

 <style>
 /* Set the font for the entire notebook to Times New Roman */
 * {
    font-family: "Times New Roman", Times, serif;
 }
 </style>

 <div>
    <img src="figures/slew_logo.png" style="float: right;height: 15em;">
 </div>

 # SLEW Case 2 - Electromechanical Dynamics: Small-signal Stability

 ## Theoretical background
 ### The Linearized Swing Equation
 The swing equation is the fundamental equation that determines the rotor dynamics of a synchronous machine.
 $$M\frac{d^{2}\delta}{dt^{2}} = P_{m} - P_{e}(\delta) - D\frac{d\delta}{dt}$$

 For small signal stability analysis, the swing equation can be linearized in the vicinity of the operating point $\delta = \delta_{0}$:
 $$M\frac{d^{2}\Delta\delta}{dt^{2}} + D\frac{d\Delta\delta}{dt}  + K_{e^{'}}\Delta\delta =  0 $$
 where $K_{e^{'}}$ is the transient synchronizing power coefficient at $\delta = \delta_{0}$:
 $$K_{e^{'}} = \frac{\partial P_{e^{'}}}{\partial \delta^{'}}\mid_{\delta = \delta_{0}}$$

 The characteristic equation and the roots of the linearized swing equation are as follows:
 $$\lambda^{2} + \frac{D}{M}\lambda + \frac{K_{e^{'}}}{M} =  0 $$

 $$\lambda_{1,2} = -\frac{D}{2M} \pm \sqrt{\left(\frac{D}{2M}\right)^{2} - \frac{K_{e^{'}}}{M}} $$

 %% Cell type:markdown id:eb59e0e7 tags:

 ***
 ## Case description

 %% Cell type:markdown id:58c9e2a2 tags:

+This is a test change (05.06.2025)
 A $200$ MVA round-rotor generator is connected to an infinite bus system of nominal frequency of $50 Hz$ through a step-up transformer with reactance of $0.13 p.u.$ and a transmission line with reactance of  $0.17 p.u.$ . The generator’s transient reactance is $x'_{d} = 0.23 p.u.$ and the inertia constant is $H = 4 s$. The synchronous generator mechanical power is set to $0.6 p.u.$ and the steady-state emf $E = 1.1 p.u.$

 %% Cell type:markdown id:a6940104 tags:

 ***
 ## Case tasks

 %% Cell type:markdown id:f3323e4f tags:

 #### Task 1
 If at the given operating point the system eigen-values are as follows:
  $$\lambda_{1,2} = -0.06254 \pm 8.8318j $$

 &nbsp;&nbsp;&nbsp;&nbsp;a) Determine whether the system response following a small disturbance is overdamped, critically damped or underdamped.

 &nbsp;&nbsp;&nbsp;&nbsp;b) Verify your findings by calculating the damping coefficient *D* (not to be confused with the damping ratio ζ ) of the synchronous generator and then applying the damping value *"D"* in SLEW and generating the corresponding power and angle plots.

 #### Task 2
 If the system response following a small disturbance is critically damped.

 &nbsp;&nbsp;&nbsp;&nbsp;a) Determine the synchronous generator damping coefficient (not to be confused with the damping ratio ζ ).

 &nbsp;&nbsp;&nbsp;&nbsp;b) Apply the calculated damping value in SLEW and generate the corresponding power and angle plots.

 &nbsp;&nbsp;&nbsp;&nbsp;c) Increase the damping coefficient (not to be confused with the damping ratio ζ ) value further and observe the impact of such increase.

 %% Cell type:markdown id:1fc3c700 tags:

 **You can process the results from SLEW (as required in 1 and 2) using the prepared notebook cells below.**

 %% Cell type:markdown id:9da09483 tags:

 ***
 ## Case solutions

 %% Cell type:markdown id:d1a0ab6c tags:

 #### First Setup your Python for post-processing

 %% Cell type:markdown id:8432a231 tags:

 Import relevant Python packages by executing the following cell:

 %% Cell type:code id:5bb649a9 tags:

 ``` python
 from IPython.display import display
 from villas.web.result import Result
 from pprint import pprint
 import tempfile
 import os
 from villas.dataprocessing.readtools import *
 from villas.dataprocessing.timeseries import *
 import matplotlib.pyplot as plt
 import scipy.io as sio
 outputs = sio.loadmat('outputs/case2_output.mat', simplify_cells=True)
 #matplotlib widget
 %matplotlib widget
 ```

 %% Cell type:markdown id:290ba8ba tags:

 ### Task 1

 %% Cell type:markdown id:3564b4be tags:

 If at the given operating point the system eigen-values are as follows:
  $$\lambda_{1,2} = -0.06254 \pm 8.8318j $$

 %% Cell type:markdown id:29d31393 tags:

 #### a)
 Determine whether the system response following a small disturbance is overdamped, critically damped or underdamped.


 %% Cell type:code id:e1620ea2 tags:

 ``` python
 import scipy.io
 import ipywidgets as widgets
 from IPython.display import display, clear_output

 # Load the solution from the .mat file
 mat_data = scipy.io.loadmat('outputs/case2_output.mat')
 correct_answer = mat_data['correct_answer'][0]

 # Create a radio button widget for the damping question
 radio_btn = widgets.RadioButtons(
    options=['Overdamped', 'Critically Damped', 'Underdamped'],
    description='Select the correct answer:',
    disabled=False
 )

 # Create an output widget to display the result
 output = widgets.Output()

 # Function to check the student's answer, display the result, and disable further attempts
 def check_answer(b):
    with output:
        clear_output()  # Clear previous output
        selected = radio_btn.value
        if selected == correct_answer:
            print("Your answer is correct! The Eigenvalues are complex conjugate pair with an imaginary part \ineq 0, therefore the system is underdamped.")
        else:
            print("Incorrect. Try again!")

        # Disable the radio buttons and the submit button after the first attempt
        #radio_btn.disabled = True
        #submit_btn.disabled = True

 # Create a button to submit the answer
 submit_btn = widgets.Button(description="Submit Answer")

 # Link the submit button to the check_answer function
 submit_btn.on_click(check_answer)

 # Display the radio button, submit button, and output widget
 display(radio_btn, submit_btn, output)
 ```

 %% Cell type:markdown id:b08ba784 tags:

 #### b)
 Verify your findings by calculating the damping coefficient (not to be confused with the damping ratio ζ ) of the synchronous generator and then applying the damping value in SLEW and generating the corresponding power and angle plots.
 To check your results, enter your solution for *"D"* rounded to 4 digits after the decimal point:

 %% Cell type:code id:4d8c545c tags:

 ``` python
 D=input('D in Subtask 1.b:')
 print('Your result is', 'correct!' if round(float(D),4)==round(outputs['D_T1b'],4) else 'incorrect. You should double-check your calculations.')
 ```

 %% Cell type:markdown id:5592eeac tags:

 Download simulation results from SLEW

 %% Cell type:markdown id:192ea4fa tags:

 Enter SLEW under [https://slew.k8s.eonerc.rwth-aachen.de](https://slew.k8s.eonerc.rwth-aachen.de).
 Adjust the parameter *"D"* and run a corresponding simulation.
 Then, enter your code snippet for result download in the following cell:

 %% Cell type:code id:3a922965 tags:

 ``` python
 # Access result using token
 r = Result(1, 'xyz', endpoint='https://slew.k8s.eonerc.rwth-aachen.de')
 ```

 %% Cell type:markdown id:7d391ebd tags:

 #### Plot the results

 %% Cell type:code id:609cbf87 tags:

 ``` python
 results_file_name='SP_SynGenTrStab_SMIB_Fault_SlewCase2_JsonSyngenParams_SP.csv'

 # Get file by name
 f = r.get_file_by_name(results_file_name)

 # Create temp dir
 tmpdir = tempfile.mkdtemp()
 results_file_path = os.path.join(tmpdir,results_file_name)

 # Load files as bytes
 f = f.download(dest=results_file_path)

 # Get time series object from csv
 ts_res1 = read_timeseries_csv(results_file_path, print_status=True)

 # Plot the currents
 plt.figure(figsize=(8,12))
 name_list = ['Rotor Angle','Output Power']
 plt.subplot(2,1,1)
 plt.ylabel("Angle (degree)")
 plt.xlabel("time (s)")
 plt.plot(ts_res1['delta_r_gen'].time, ts_res1['delta_r_gen'].values, label='Rotor Angle task 1.b', color='C0')
 plt.xlim([1, 30])
 plt.legend(loc='upper right')

 plt.subplot(2,1,2)
 plt.ylabel("Power (MW)")
 plt.xlabel("time (s)")
 plt.plot(ts_res1['P_elec'].time, ts_res1['P_elec'].values/1e6, label='Output Power task 1.b', color='C1')
 plt.xlim([1, 30])
 plt.legend(loc='upper right')
 plt.show()
 ```

 %% Cell type:markdown id:8ef9b8b2 tags:

 ### Task 2

 %% Cell type:markdown id:00d2e239 tags:

 If the system response following a small disturbance is critically damped.

 %% Cell type:markdown id:b1a6d35b tags:

 #### a)
 Determine the synchronous generator damping coefficient (not to be confused with the damping ratio ζ ).

 To check your results, enter your solution for *"D"* rounded to 4 digits behind the comma:

 %% Cell type:code id:e70ae849 tags:

 ``` python
 D=input('D in Subtask 2.a:')
 print('Your result is', 'correct!' if round(float(D),4)==round(outputs['D_T2a'],4) else 'incorrect. You should double-check your calculations.')
 ```

 %% Cell type:markdown id:6ab41b23 tags:

 #### b)
 Apply the calculated damping value in SLEW and generate the corresponding power and angle plots.

 Download simulation results from SLEW

 %% Cell type:markdown id:5f52f99d tags:

 Enter SLEW under [https://slew.k8s.eonerc.rwth-aachen.de](https://slew.k8s.eonerc.rwth-aachen.de).
 Adjust the parameter *"D"* and run a corresponding simulation.
 Then, enter your code snippet for result download in the following cell:

 %% Cell type:code id:921256f6 tags:

 ``` python
 # Access result using token
 r = Result(1, 'xyz', endpoint='https://slew.k8s.eonerc.rwth-aachen.de')
 ```

 %% Cell type:markdown id:4d20385b tags:

 #### Plot the results

 %% Cell type:code id:ba064129 tags:

 ``` python
 results_file_name='SP_SynGenTrStab_SMIB_Fault_SlewCase2_JsonSyngenParams_SP.csv'

 # Get file by name
 f = r.get_file_by_name(results_file_name)

 # Create temp dir
 tmpdir = tempfile.mkdtemp()
 results_file_path = os.path.join(tmpdir,results_file_name)

 # Load files as bytes
 f = f.download(dest=results_file_path)

 # Get time series object from csv
 ts_res2 = read_timeseries_csv(results_file_path, print_status=False)

 # Plot the currents
 plt.figure(figsize=(8,12))
 name_list = ['Rotor Angle','Output Power']
 plt.subplot(2,1,1)
 plt.ylabel("Angle (degree)")
 plt.xlabel("time (s)")
 plt.plot(ts_res2['delta_r_gen'].time, ts_res2['delta_r_gen'].values,  label='Rotor  Angle task 2.b', color='C0')
 plt.plot(ts_res1['delta_r_gen'].time, ts_res1['delta_r_gen'].values, label='Rotor  Angle task 1.b', color='black', linestyle=':')
 plt.xlim([1, 30])
 plt.legend(loc='upper right')

 plt.subplot(2,1,2)
 plt.ylabel("Power (MW)")
 plt.xlabel("time (s)")
 plt.plot(ts_res2['P_elec'].time, ts_res2['P_elec'].values/1e6,  label='Output Power task 2.b', color='C1')
 plt.plot(ts_res1['P_elec'].time, ts_res1['P_elec'].values/1e6, label='Output Power task 1.b', color='black', linestyle=':')
 plt.xlim([1, 30])
 plt.legend(loc='upper right')
 plt.show()
 ```

 %% Cell type:markdown id:18f20b09 tags:

 #### c)
 Increase the damping coefficient (not to be confused with the damping ratio ζ ) value (for example by a factor of 2) further and observe the impact of such increase.

 Download simulation results from SLEW

 %% Cell type:markdown id:4f967ccb tags:

 Enter SLEW under [https://slew.k8s.eonerc.rwth-aachen.de](https://slew.k8s.eonerc.rwth-aachen.de).
 Adjust the parameter *"D"* and run a corresponding simulation.
 Then, enter your code snippet for result download in the following cell:

 %% Cell type:code id:79b309eb tags:

 ``` python
 # Access result using token
 r = Result(1, 'xyz', endpoint='hhttps://slew.k8s.eonerc.rwth-aachen.de')
 ```

 %% Cell type:markdown id:a4dbb836 tags:

 #### Plot the results

 %% Cell type:code id:ba53ba36 tags:

 ``` python
 results_file_name='SP_SynGenTrStab_SMIB_Fault_SlewCase2_JsonSyngenParams_SP.csv'

 # Get file by name
 f = r.get_file_by_name(results_file_name)

 # Create temp dir
 tmpdir = tempfile.mkdtemp()
 results_file_path = os.path.join(tmpdir,results_file_name)

 # Load files as bytes
 f = f.download(dest=results_file_path)

 # Get time series object from csv
 ts_res3 = read_timeseries_csv(results_file_path, print_status=False)

 # Plot the currents
 plt.figure(figsize=(8,12))
 name_list = ['Rotor Angle','Output Power']
 plt.subplot(2,1,1)
 plt.ylabel("Angle (degree)")
 plt.xlabel("time (s)")
 plt.plot(ts_res3['delta_r_gen'].time, ts_res3['delta_r_gen'].values, label='Rotor  Angle task 2.c', color='C0')
 plt.plot(ts_res2['delta_r_gen'].time, ts_res2['delta_r_gen'].values,  label='Rotor  Angle task 2.b', color='black', linestyle=':')
 plt.xlim([1, 30])
 plt.legend(loc='upper right')

 plt.subplot(2,1,2)
 plt.ylabel("Power (MW)")
 plt.xlabel("time (s)")
 plt.plot(ts_res3['P_elec'].time, ts_res3['P_elec'].values/1e6, label='Output Power task 2.c', color='C1')
 plt.plot(ts_res2['P_elec'].time, ts_res2['P_elec'].values/1e6,  label='Output Power task 2.b', color='black', linestyle=':')
 plt.xlim([1, 30])
 plt.legend(loc='upper right')
 plt.show()
 ```

 %% Cell type:code id:d74fe01a tags:

 ``` python
 ```