Update file SLEW_Case1_Electromagnetic_Phenomena.ipynb

634b3d01 · Marc Moritz · 6bc09643 · 634b3d01
Commit 634b3d01 authored 9 months ago by Marc Moritz
--- a/SLEW_Case1_Electromagnetic_Phenomena.ipynb
+++ b/SLEW_Case1_Electromagnetic_Phenomena.ipynb
@@ -217,7 +217,7 @@
   "cell_type": "markdown",
   "metadata": {},
   "source": [
-    "Enter VILLASweb under [https://slew.rwth-aachen.de/](https://slew.rwth-aachen.de/).  \n",
+    "Enter VILLASweb under [https://villas.k8s.eonerc.rwth-aachen.de](https://villas.k8s.eonerc.rwth-aachen.de).  \n",
    "Adjust the parameter *Ld_t* and run a corresponding simulation. Further instructions on how to handle VILLASweb you can find in the [SLEW Platform Tutorial](./SLEW_Platform_Tutorial.ipynb).  \n",
    "Then, enter your code snippet for result download in the following cell:"
   ]

 %% Cell type:markdown id: tags:

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

 # SLEW Case 1 - Electromagnetic Phenomena of Synchronous Machines

 ## Theoretical background

 ### The generator and its windings

 <img src="figures/SubtransientTransientSteadyMachine.svg" width="600" align="left">

 %% Cell type:markdown id: tags:

 The winding resistance (of armature i.e. stator) dissipates energy at rate proportional to the current squared. The DC components (part of total phase currents) decay ($T_a$). Those armature currents induce direct currents in the rotor windings. They decay with respect to time constant determined by the particular rotor circuit in which they flow:
  - DC component of the damper winding current decays with the d-axis subtransient short-circuit time constant $T''_d$
  - DC component of the field current decays with the field winding time constant, called the d-axis transient short circuit time constant $T'_d$
  - Resistance of damper windings is much higher than the resistance of the field winding $T''_d \leq T'_d$
 *\[text and figure adopted from J. Machowski, Z. Lubosny, J. Bialek, and J. R. Bumby, Power system dynamics: stability and control\]*

 %% Cell type:markdown id: tags:

 ## Case description

 %% Cell type:markdown id: tags:

 A round-rotor machine has the following values:
 - $X_{fd} = 0.1648$, $X_l = 0.15$, $X_d = 1.8099$, $X_q = 1.76$
 - $T'_{d_0} = 8.0669 s$, $T''_{d_0} = 0.03 s$, $T'_{q_0} = 0.9991 s$, $T''_{q_0} = 0.07 s$
 - $X''_d = 0.2299$, $X'_q = 0.65$, $X''_q = 0.25$
 - $f_n = 60 Hz$

 %% Cell type:markdown id: tags:

 ## Case tasks

 %% Cell type:markdown id: tags:

 1. Calculate $X'_d$, $R_{fd}$, $X_{Dd}$ and $R_{Dd}$ from the given quantities (you can neglect the leakage inductance).
 2. Apply $X'_d$ by adjusting *Ld_t* in VILLASweb and generate the corresponding short-circuit current plot.
 3. The open circuit time constant $T'_{do}$ shall be increased to $18s$
  a.) Find the corresponding value of $R_{fd}$ that leads to that increase.
  b.) Apply the new $T'_{do}$ by adjusting *Td0_t* in VILLASweb, run the simulation and observe the impact of such increase.
 4. The open circuit time constant $T''_{do}$ shall be increased to $0.09s$
  a.) Find the corresponding value of $R_{Dd}$ that leads to that increase.
  b.) Reset $T'_{do}$ to its original value and apply the new $T''_{do}$ instead by adjusting *Td0_s* in VILLASweb, run the simulation and observe the impact of such increase.

 %% Cell type:markdown id: tags:

 **You can check your calculation solutions and process the results from VILLASweb using the prepared notebook cells below.**

 %% Cell type:markdown id: tags:

 ## Case solutions

 %% Cell type:markdown id: tags:

 #### Setup your Python for post-processing

 %% Cell type:markdown id: tags:

 Import relevant Python packages by executing the following cell:

 %% Cell type:code id: 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/case1_output.mat', simplify_cells=True)

 %matplotlib widget
 ```

 %% Cell type:markdown id: tags:

 ### Subtask 1

 %% Cell type:markdown id: tags:

 *Calculate $X'_d$, $R_{fd}$, $X_{Dd}$ and $R_{Dd}$ from the given quantities (you can neglect the leakage inductance).*

 %% Cell type:markdown id: tags:

 To check your results, enter your solution for $X'_d$ rounded to 4 digits behind the comma:

 %% Cell type:code id: tags:

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

 %% Cell type:markdown id: tags:

 To check your results, enter your solution for $R_{fd}$ rounded to 4 digits behind the comma:

 %% Cell type:code id: tags:

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

 %% Cell type:markdown id: tags:

 To check your results, enter your solution for $X_{Dd}$ rounded to 4 digits behind the comma:

 %% Cell type:code id: tags:

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

 %% Cell type:markdown id: tags:

 To check your results, enter your solution for $R_{Dd}$ rounded to 4 digits behind the comma:

 %% Cell type:code id: tags:

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

 %% Cell type:markdown id: tags:

 ### Subtask 2

 %% Cell type:markdown id: tags:

 *Apply $X'_d$ by adjusting *Ld_t* in VILLASweb and generate the corresponding short-circuit current plot.*

 %% Cell type:markdown id: tags:

-Enter VILLASweb under [https://slew.rwth-aachen.de/](https://slew.rwth-aachen.de/).
+Enter VILLASweb under [https://villas.k8s.eonerc.rwth-aachen.de](https://villas.k8s.eonerc.rwth-aachen.de).
 Adjust the parameter *Ld_t* and run a corresponding simulation. Further instructions on how to handle VILLASweb you can find in the [SLEW Platform Tutorial](./SLEW_Platform_Tutorial.ipynb).
 Then, enter your code snippet for result download in the following cell:

 %% Cell type:code id: tags:

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

 %% Cell type:markdown id: tags:

 #### Plot the results

 %% Cell type:code id: tags:

 ``` python
 results_file_name='EMT_SynGenDQ7odTrapez_OperationalParams_SMIB_Fault_JsonSyngenParams.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=False)

 # Plot the currents
 plt.figure(figsize=(8,12))
 name_list = ['i_gen_0', 'i_gen_1', 'i_gen_2']
 phases = ['a', 'b', 'c']
 for name in name_list:
    i = name_list.index(name)
    plt.subplot(3,1,1+i)
    plt.ylabel("current (kA)")
    plt.xlabel("time (s)")
    plt.plot(ts_res1[name].time, ts_res1[name].values/1e3, label='SG task 2 (phase '+phases[i]+')', color='C0')
    plt.xlim([0, 1])
    plt.legend(loc='upper right')
 plt.show()
 ```

 %% Cell type:markdown id: tags:

 ### Subtask 3

 %% Cell type:markdown id: tags:

 *3. The open circuit time constant $T'_{do}$ shall be increased to $18s$
  a.) Find the corresponding value of $R_{fd}$ that leads to that increase.
  b.) Apply the new $T'_{do}$ by adjusting *Td0_t* in VILLASweb, run the simulation and observe the impact of such increase.*

 %% Cell type:markdown id: tags:

 ### a.)

 %% Cell type:markdown id: tags:

 To check your results, enter your solution for $R_{fd}$ rounded to 7 digits behind the comma:

 %% Cell type:code id: tags:

 ``` python
 Rfd_T3a=input('Rfd in Subtask 3:')
 print('Your result is', 'correct!' if round(float(Rfd_T3a),7)==round(outputs['Rfd_T3a'],7) else 'incorrect. You should double-check your calculations.')
 ```

 %% Cell type:markdown id: tags:

 ### b.)

 %% Cell type:markdown id: tags:

 Enter VILLASweb under [https://slew.rwth-aachen.de/](https://slew.rwth-aachen.de/).
 Adjust the parameter *Td0_t* and run a corresponding simulation. Further instructions on how to handle VILLASweb you can find in the [SLEW Platform Tutorial](./SLEW_Platform_Tutorial.ipynb).
 Then, enter your code snippet for result download in the following cell:

 %% Cell type:code id: tags:

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

 %% Cell type:markdown id: tags:

 #### Plot the results

 %% Cell type:code id: tags:

 ``` python
 results_file_name='EMT_SynGenDQ7odTrapez_OperationalParams_SMIB_Fault_JsonSyngenParams.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 = ['i_gen_0', 'i_gen_1', 'i_gen_2']
 phases = ['a', 'b', 'c']
 for name in name_list:
    i = name_list.index(name)
    plt.subplot(3,1,1+i)
    plt.ylabel("current (kA)")
    plt.xlabel("time (s)")
    plt.plot(ts_res1[name].time, ts_res1[name].values/1e3, label='SG task 2 (phase '+phases[i]+')', color='C0')
    plt.plot(ts_res2[name].time, ts_res2[name].values/1e3, label='SG task 3 (phase '+phases[i]+')', color='C1', linestyle=':')
    plt.xlim([0, 1])
    plt.legend(loc='upper right')
 plt.show()
 ```

 %% Cell type:markdown id: tags:

 ### Subtask 4

 %% Cell type:markdown id: tags:

 *4. The open circuit time constant $T''_{do}$ shall be increased to $0.09s$
  a.) Find the corresponding value of $R_{Dd}$ that leads to that increase.
  b.) Reset $T'_{do}$ to its original value and apply the new $T''_{do}$ instead by adjusting *Td0_s* in VILLASweb, run the simulation and observe the impact of such increase.*

 %% Cell type:markdown id: tags:

 ### a.)

 %% Cell type:markdown id: tags:

 To check your results, enter your solution for $R_{Dd}$ rounded to 4 digits behind the comma:

 %% Cell type:code id: tags:

 ``` python
 RDd_T4a=input('RDd in Subtask 4:')
 print('Your result is', 'correct!' if round(float(RDd_T4a),4)==round(outputs['RDd_T4a'],4) else 'incorrect. You should double-check your calculations.')
 ```

 %% Cell type:markdown id: tags:

 ### b.)

 %% Cell type:markdown id: tags:

 Enter VILLASweb under [https://slew.rwth-aachen.de/](https://slew.rwth-aachen.de/).
 Adjust the parameter *Td0_s* and run a corresponding simulation. Further instructions on how to handle VILLASweb you can find in the [SLEW Platform Tutorial](./SLEW_Platform_Tutorial.ipynb).
 Then, enter your code snippet for result download in the following cell:

 %% Cell type:code id: tags:

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

 %% Cell type:markdown id: tags:

 #### Plot the results

 %% Cell type:code id: tags:

 ``` python
 results_file_name='EMT_SynGenDQ7odTrapez_OperationalParams_SMIB_Fault_JsonSyngenParams.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 = ['i_gen_0', 'i_gen_1', 'i_gen_2']
 phases = ['a', 'b', 'c']
 for name in name_list:
    i = name_list.index(name)
    plt.subplot(3,1,1+i)
    plt.ylabel("current (kA)")
    plt.xlabel("time (s)")
    plt.plot(ts_res1[name].time, ts_res1[name].values/1e3, label='SG task 2 (phase '+phases[i]+')', color='C0')
    plt.plot(ts_res3[name].time, ts_res3[name].values/1e3, label='SG task 4 (phase '+phases[i]+')', color='C1', linestyle=':')
    plt.xlim([0, 1])
    plt.legend(loc='upper right')
 plt.show()
 ```