examples/ex8.ipynb

{
    "cells": [
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "# Changing Setpoints"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "This notebook shows an example of changing the generator setpoints in a time-domain simulation. Data in this example is trivial, but the example can be retrofitted for scenarios such as economic dispatch incorporation or reinforcement learning.\n",
                "\n",
                "Steps are the folllwing:\n",
                "\n",
                "1. Initialize a system by running the power flow,\n",
                "2. Set the first simulation stop time in `TDS.config.tf`,\n",
                "3. Run the simulation,\n",
                "3. Update the setpoints,\n",
                "4. Set the new simulation stop time and repeat from 3 until the end."
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "## Step 1: Case Setup"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 1,
            "metadata": {
                "ExecuteTime": {
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                "execution": {
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                    "shell.execute_reply": "2021-09-26T22:41:51.755953Z"
                }
            },
            "outputs": [],
            "source": [
                "import andes\n",
                "from andes.utils import get_case"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 2,
            "metadata": {
                "ExecuteTime": {
                    "end_time": "2021-03-19T20:13:22.290011Z",
                    "start_time": "2021-03-19T20:13:21.560840Z"
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                    "shell.execute_reply": "2021-09-26T22:41:52.421887Z"
                }
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            "outputs": [
                {
                    "name": "stderr",
                    "output_type": "stream",
                    "text": [
                        "Working directory: \"/home/hacui/repos/andes/examples\"\n",
                        "> Loaded config from file \"/home/hacui/.andes/andes.rc\"\n",
                        "> Loaded generated Python code in \"/home/hacui/.andes/pycode\".\n",
                        "Parsing input file \"/home/hacui/repos/andes/andes/cases/kundur/kundur_full.xlsx\"...\n",
                        "Input file parsed in 0.2635 seconds.\n",
                        "System internal structure set up in 0.0315 seconds.\n",
                        "-> System connectivity check results:\n",
                        "  No islanded bus detected.\n",
                        "  System is interconnected.\n",
                        "  Each island has a slack bus correctly defined and enabled.\n",
                        "\n",
                        "-> Power flow calculation\n",
                        "           Numba: Off\n",
                        "   Sparse solver: KLU\n",
                        " Solution method: NR method\n",
                        "Power flow initialized in 0.0087 seconds.\n",
                        "0: |F(x)| = 14.9282832\n",
                        "1: |F(x)| = 3.608627841\n",
                        "2: |F(x)| = 0.1701107882\n",
                        "3: |F(x)| = 0.002038626956\n",
                        "4: |F(x)| = 3.745104027e-07\n",
                        "Converged in 5 iterations in 0.0108 seconds.\n",
                        "Initialization for dynamics completed in 0.0395 seconds.\n",
                        "Initialization was successful.\n",
                        "Report saved to \"kundur_full_out.txt\" in 0.0023 seconds.\n"
                    ]
                },
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": [
                        "-> Single process finished in 0.5215 seconds.\n"
                    ]
                }
            ],
            "source": [
                "kundur = get_case('kundur/kundur_full.xlsx')\n",
                "\n",
                "ss = andes.run(kundur)"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 3,
            "metadata": {
                "ExecuteTime": {
                    "end_time": "2021-03-19T20:13:22.297356Z",
                    "start_time": "2021-03-19T20:13:22.292557Z"
                },
                "execution": {
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                    "shell.execute_reply": "2021-09-26T22:41:52.427317Z"
                }
            },
            "outputs": [],
            "source": [
                "# disable the Toggle in this case\n",
                "ss.Toggle.alter('u', 1, 0)"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "## Step 2: Set the First Stop Time"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 4,
            "metadata": {
                "ExecuteTime": {
                    "end_time": "2021-03-19T20:13:22.305395Z",
                    "start_time": "2021-03-19T20:13:22.302336Z"
                },
                "execution": {
                    "iopub.execute_input": "2021-09-26T22:41:52.432122Z",
                    "iopub.status.busy": "2021-09-26T22:41:52.429462Z",
                    "iopub.status.idle": "2021-09-26T22:41:52.432582Z",
                    "shell.execute_reply": "2021-09-26T22:41:52.432907Z"
                }
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            "outputs": [],
            "source": [
                "# simulate to t=1 sec\n",
                "\n",
                "# specify the first stop in `ss.TDS.config.tf`\n",
                "ss.TDS.config.tf = 1"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "## Step 3: Run Simulation"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 5,
            "metadata": {
                "ExecuteTime": {
                    "end_time": "2021-03-19T20:13:22.499102Z",
                    "start_time": "2021-03-19T20:13:22.308794Z"
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                    "shell.execute_reply": "2021-09-26T22:41:52.578395Z"
                }
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            "outputs": [
                {
                    "name": "stderr",
                    "output_type": "stream",
                    "text": [
                        "\n",
                        "-> Time Domain Simulation Summary:\n",
                        "Sparse Solver: KLU\n",
                        "Simulation time: 0.0-1 s.\n",
                        "Fixed step size: h=33.33 ms. Shrink if not converged.\n"
                    ]
                },
                {
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                        "text/plain": [
                            "  0%|          | 0/100 [00:00<?, ?%/s]"
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                    "output_type": "display_data"
                },
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                    "name": "stderr",
                    "output_type": "stream",
                    "text": [
                        "Simulation completed in 0.0245 seconds.\n",
                        "Outputs to \"kundur_full_out.lst\" and \"kundur_full_out.npz\".\n",
                        "Outputs written in 0.0039 seconds.\n"
                    ]
                },
                {
                    "data": {
                        "text/plain": [
                            "True"
                        ]
                    },
                    "execution_count": 5,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "ss.TDS.run()"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "## Step 4. Apply the auxiliary power setpoints to `TGOV1.paux0.v`"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "First, let's check the equations of TGOV1. `ss.TGOV1.paux0` is associated with equation `0 = paux - paux0`, in which `paux` is added to the power input equation."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 6,
            "metadata": {
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                    "end_time": "2021-03-19T20:13:22.519088Z",
                    "start_time": "2021-03-19T20:13:22.503939Z"
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            "outputs": [
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": [
                        "Model <TGOV1> in Group <TurbineGov>\n",
                        "TGOV1 turbine governor model.\n",
                        "\n",
                        "Implements the PSS/E TGOV1 model without deadband.\n",
                        "\n",
                        "Parameters\n",
                        "\n",
                        " Name  |            Description            | Default | Unit |    Properties   \n",
                        "-------+-----------------------------------+---------+------+-----------------\n",
                        " idx   | unique device idx                 |         |      |                 \n",
                        " u     | connection status                 | 1       | bool |                 \n",
                        " name  | device name                       |         |      |                 \n",
                        " syn   | Synchronous generator idx         |         |      | mandatory,unique\n",
                        " Tn    | Turbine power rating. Equal to    |         | MVA  |                 \n",
                        "       | `Sn` if not provided.             |         |      |                 \n",
                        " wref0 | Base speed reference              | 1       | p.u. |                 \n",
                        " R     | Speed regulation gain (mach. base | 0.050   | p.u. | ipower          \n",
                        "       | default)                          |         |      |                 \n",
                        " VMAX  | Maximum valve position            | 1.200   | p.u. | power           \n",
                        " VMIN  | Minimum valve position            | 0       | p.u. | power           \n",
                        " T1    | Valve time constant               | 0.100   |      |                 \n",
                        " T2    | Lead-lag lead time constant       | 0.200   |      |                 \n",
                        " T3    | Lead-lag lag time constant        | 10      |      |                 \n",
                        " Dt    | Turbine damping coefficient       | 0       |      | power           \n",
                        " Sg    | Rated power from generator        | 0       | MVA  |                 \n",
                        " ug    | Generator connection status       | 0       | bool |                 \n",
                        " Vn    | Rated voltage from generator      | 0       | kV   |                 \n",
                        "\n",
                        "Variables\n",
                        "\n",
                        " Name  |   Type   |             Description              | Unit | Properties\n",
                        "-------+----------+--------------------------------------+------+-----------\n",
                        " LAG_y | State    | State in lag TF                      |      | v_str     \n",
                        " LL_x  | State    | State in lead-lag                    |      | v_str     \n",
                        " omega | ExtState | Generator speed                      | p.u. |           \n",
                        " paux  | Algeb    | Auxiliary power input                |      | v_str     \n",
                        " pout  | Algeb    | Turbine final output power           |      | v_str     \n",
                        " wref  | Algeb    | Speed reference variable             |      | v_str     \n",
                        " pref  | Algeb    | Reference power input                |      | v_str     \n",
                        " wd    | Algeb    | Generator speed deviation            | p.u. | v_str     \n",
                        " pd    | Algeb    | Pref plus speed deviation times gain | p.u. | v_str     \n",
                        " LL_y  | Algeb    | Output of lead-lag                   |      | v_str     \n",
                        " tm    | ExtAlgeb | Mechanical power interface to SynGen |      |           \n",
                        "\n",
                        "Initialization Equations\n",
                        "\n",
                        " Name  |   Type   | Initial Value\n",
                        "-------+----------+--------------\n",
                        " LAG_y | State    | pd * 1 / 1   \n",
                        " LL_x  | State    | LAG_y        \n",
                        " omega | ExtState |              \n",
                        " paux  | Algeb    | paux0        \n",
                        " pout  | Algeb    | ue * tm0     \n",
                        " wref  | Algeb    | wref0        \n",
                        " pref  | Algeb    | tm0 * R      \n",
                        " wd    | Algeb    | 0            \n",
                        " pd    | Algeb    | ue * tm0     \n",
                        " LL_y  | Algeb    | LAG_y        \n",
                        " tm    | ExtAlgeb |              \n",
                        "\n",
                        "Differential Equations\n",
                        "\n",
                        " Name  |   Type   | RHS of Equation \"T x' = f(x, y)\" | T (LHS)\n",
                        "-------+----------+----------------------------------+--------\n",
                        " LAG_y | State    | 1 * pd - 1 * LAG_y               | T1     \n",
                        " LL_x  | State    | (LAG_y - LL_x)                   | T3     \n",
                        " omega | ExtState |                                  |        \n",
                        "\n",
                        "Algebraic Equations\n",
                        "\n",
                        "Name  |   Type   |                RHS of Equation \"0 = g(x, y)\"               \n",
                        "------+----------+------------------------------------------------------------\n",
                        " paux | Algeb    | paux0 - paux                                               \n",
                        " pout | Algeb    | ue * (LL_y - Dt * wd) - pout                               \n",
                        " wref | Algeb    | wref0 - wref                                               \n",
                        " pref | Algeb    | pref0 * R - pref                                           \n",
                        " wd   | Algeb    | ue * (omega - wref) - wd                                   \n",
                        " pd   | Algeb    | ue*(- wd + pref + paux) * gain - pd                        \n",
                        " LL_y | Algeb    | 1 * T2 * (LAG_y - LL_x) + 1 * LL_x * T3 - LL_y * T3+       \n",
                        "      |          | LL_LT1_z1 * LL_LT2_z1 * (LL_y - 1 * LL_x)                  \n",
                        " tm   | ExtAlgeb | ue * (pout - tm0)                                          \n",
                        "\n",
                        "Services\n",
                        "\n",
                        " Name  | Equation |     Type    \n",
                        "-------+----------+-------------\n",
                        " ue    | u * ug   | ConstService\n",
                        " pref0 | tm0      | ConstService\n",
                        " paux0 | 0        | ConstService\n",
                        " gain  | ue/R     | ConstService\n",
                        "\n",
                        "Discretes\n",
                        "\n",
                        "  Name   |    Type    |      Info     \n",
                        "---------+------------+---------------\n",
                        " LAG_lim | AntiWindup | Limiter in Lag\n",
                        " LL_LT1  | LessThan   |               \n",
                        " LL_LT2  | LessThan   |               \n",
                        "\n",
                        "Blocks\n",
                        "\n",
                        "Name |     Type      | Info\n",
                        "-----+---------------+-----\n",
                        " LAG | LagAntiWindup |     \n",
                        " LL  | LeadLag       |     \n",
                        "\n",
                        "\n",
                        "Config Fields in [TGOV1]\n",
                        "\n",
                        "   Option     | Value |                Info                | Acceptable values\n",
                        "--------------+-------+------------------------------------+------------------\n",
                        " allow_adjust | 1     | allow adjusting upper or lower     | (0, 1)           \n",
                        "              |       | limits                             |                  \n",
                        " adjust_lower | 0     | adjust lower limit                 | (0, 1)           \n",
                        " adjust_upper | 1     | adjust upper limit                 | (0, 1)           \n",
                        "\n",
                        "\n"
                    ]
                }
            ],
            "source": [
                "print(ss.TGOV1.doc())"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 7,
            "metadata": {
                "ExecuteTime": {
                    "end_time": "2021-03-19T20:13:22.529826Z",
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                }
            },
            "outputs": [
                {
                    "data": {
                        "text/plain": [
                            "array([0., 0., 0., 0.])"
                        ]
                    },
                    "execution_count": 7,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "ss.TGOV1.paux0.v"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 8,
            "metadata": {
                "ExecuteTime": {
                    "end_time": "2021-03-19T20:13:22.539756Z",
                    "start_time": "2021-03-19T20:13:22.534130Z"
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                    "shell.execute_reply": "2021-09-26T22:41:52.602406Z"
                }
            },
            "outputs": [
                {
                    "data": {
                        "text/plain": [
                            "array([0., 0., 0., 0.])"
                        ]
                    },
                    "execution_count": 8,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "# look up the original values of TGOV1 make sure they are as expected\n",
                "\n",
                "ss.TGOV1.paux0.v"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 9,
            "metadata": {
                "ExecuteTime": {
                    "end_time": "2021-03-19T20:13:22.546373Z",
                    "start_time": "2021-03-19T20:13:22.544173Z"
                },
                "execution": {
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            "outputs": [],
            "source": [
                "# MUST use in-place assignments. \n",
                "# Here, we increase the setpoint of the 0-th generator\n",
                "\n",
                "# method 1: use in-place assignment again\n",
                "\n",
                "ss.TGOV1.paux0.v[0] = 0.05\n",
                "\n",
                "# method 2: use ``ss.TGOV1.alter()``\n",
                "\n",
                "# ss.TGOV1.alter('paux0', 1, 0.05)"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 10,
            "metadata": {
                "ExecuteTime": {
                    "end_time": "2021-03-19T20:13:22.551802Z",
                    "start_time": "2021-03-19T20:13:22.548389Z"
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                "execution": {
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                    "shell.execute_reply": "2021-09-26T22:41:52.613057Z"
                }
            },
            "outputs": [
                {
                    "data": {
                        "text/plain": [
                            "array([0.05, 0.  , 0.  , 0.  ])"
                        ]
                    },
                    "execution_count": 10,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "ss.TGOV1.paux0.v"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "Continue to simulate to 2 seconds."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 11,
            "metadata": {
                "ExecuteTime": {
                    "end_time": "2021-03-19T20:13:22.555851Z",
                    "start_time": "2021-03-19T20:13:22.553588Z"
                },
                "execution": {
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                    "shell.execute_reply": "2021-09-26T22:41:52.619047Z"
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            },
            "outputs": [],
            "source": [
                "ss.TDS.config.tf = 2"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 12,
            "metadata": {
                "ExecuteTime": {
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                            "version_minor": 0
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                            "  0%|          | 0/100 [00:00<?, ?%/s]"
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                    "metadata": {},
                    "output_type": "display_data"
                },
                {
                    "name": "stderr",
                    "output_type": "stream",
                    "text": [
                        "Simulation completed in 0.0916 seconds.\n",
                        "Outputs to \"kundur_full_out.lst\" and \"kundur_full_out.npz\".\n",
                        "Outputs written in 0.0032 seconds.\n"
                    ]
                },
                {
                    "data": {
                        "text/plain": [
                            "True"
                        ]
                    },
                    "execution_count": 12,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "ss.TDS.run()"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 13,
            "metadata": {
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                {
                    "data": {
                        "image/png": "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\n",
                        "text/plain": [
                            "<Figure size 480x320 with 1 Axes>"
                        ]
                    },
                    "metadata": {
                        "needs_background": "light"
                    },
                    "output_type": "display_data"
                },
                {
                    "data": {
                        "text/plain": [
                            "(<Figure size 480x320 with 1 Axes>, <AxesSubplot:xlabel='Time [s]'>)"
                        ]
                    },
                    "execution_count": 13,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "ss.TDS.plotter.plot(ss.TGOV1.paux)"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 14,
            "metadata": {
                "ExecuteTime": {
                    "end_time": "2021-03-19T20:13:24.736064Z",
                    "start_time": "2021-03-19T20:13:23.906408Z"
                },
                "execution": {
                    "iopub.execute_input": "2021-09-26T22:41:53.839939Z",
                    "iopub.status.busy": "2021-09-26T22:41:53.827388Z",
                    "iopub.status.idle": "2021-09-26T22:41:54.670798Z",
                    "shell.execute_reply": "2021-09-26T22:41:54.671184Z"
                }
            },
            "outputs": [
                {
                    "data": {
                        "image/png": 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\n",
                        "text/plain": [
                            "<Figure size 480x320 with 1 Axes>"
                        ]
                    },
                    "metadata": {
                        "needs_background": "light"
                    },
                    "output_type": "display_data"
                },
                {
                    "data": {
                        "text/plain": [
                            "(<Figure size 480x320 with 1 Axes>, <AxesSubplot:xlabel='Time [s]'>)"
                        ]
                    },
                    "execution_count": 14,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "ss.TDS.plotter.plot(ss.TGOV1.pout)"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 15,
            "metadata": {
                "ExecuteTime": {
                    "end_time": "2021-03-19T20:13:25.014751Z",
                    "start_time": "2021-03-19T20:13:24.739696Z"
                },
                "execution": {
                    "iopub.execute_input": "2021-09-26T22:41:54.675715Z",
                    "iopub.status.busy": "2021-09-26T22:41:54.674499Z",
                    "iopub.status.idle": "2021-09-26T22:41:55.292894Z",
                    "shell.execute_reply": "2021-09-26T22:41:55.293267Z"
                }
            },
            "outputs": [
                {
                    "data": {
                        "image/png": 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\n",
                        "text/plain": [
                            "<Figure size 480x320 with 1 Axes>"
                        ]
                    },
                    "metadata": {
                        "needs_background": "light"
                    },
                    "output_type": "display_data"
                },
                {
                    "data": {
                        "text/plain": [
                            "(<Figure size 480x320 with 1 Axes>, <AxesSubplot:xlabel='Time [s]'>)"
                        ]
                    },
                    "execution_count": 15,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "ss.TDS.plotter.plot(ss.GENROU.omega)"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "## Step 5: Set Another New Setpoints and New Ending TIme.\n",
                "\n",
                "In this example, we clear the auxiliary power previously set to `TGOV1.paux0.v`"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 16,
            "metadata": {
                "ExecuteTime": {
                    "end_time": "2021-03-19T20:13:25.018446Z",
                    "start_time": "2021-03-19T20:13:25.016455Z"
                },
                "execution": {
                    "iopub.execute_input": "2021-09-26T22:41:55.297967Z",
                    "iopub.status.busy": "2021-09-26T22:41:55.297473Z",
                    "iopub.status.idle": "2021-09-26T22:41:55.300246Z",
                    "shell.execute_reply": "2021-09-26T22:41:55.300764Z"
                }
            },
            "outputs": [],
            "source": [
                "# method 1: use in-place assignment again\n",
                "\n",
                "ss.TGOV1.paux0.v[0] = 0.\n",
                "\n",
                "# method 2: use ``ss.TGOV1.alter()``\n",
                "\n",
                "# ss.TGOV1.alter('paux0', 1, 0)\n",
                "\n",
                "# set the new ending time to 10 sec.\n",
                "ss.TDS.config.tf = 10"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 17,
            "metadata": {
                "ExecuteTime": {
                    "end_time": "2021-03-19T20:13:26.308257Z",
                    "start_time": "2021-03-19T20:13:25.019594Z"
                },
                "execution": {
                    "iopub.execute_input": "2021-09-26T22:41:55.304817Z",
                    "iopub.status.busy": "2021-09-26T22:41:55.304316Z",
                    "iopub.status.idle": "2021-09-26T22:41:56.777619Z",
                    "shell.execute_reply": "2021-09-26T22:41:56.778204Z"
                }
            },
            "outputs": [
                {
                    "data": {
                        "application/vnd.jupyter.widget-view+json": {
                            "model_id": "b99e933f27444045bbc750a67d6903f4",
                            "version_major": 2,
                            "version_minor": 0
                        },
                        "text/plain": [
                            "  0%|          | 0/100 [00:00<?, ?%/s]"
                        ]
                    },
                    "metadata": {},
                    "output_type": "display_data"
                },
                {
                    "name": "stderr",
                    "output_type": "stream",
                    "text": [
                        "Simulation completed in 0.6068 seconds.\n",
                        "Outputs to \"kundur_full_out.lst\" and \"kundur_full_out.npz\".\n",
                        "Outputs written in 0.0275 seconds.\n"
                    ]
                },
                {
                    "data": {
                        "text/plain": [
                            "True"
                        ]
                    },
                    "execution_count": 17,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "ss.TDS.run()"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 18,
            "metadata": {
                "ExecuteTime": {
                    "end_time": "2021-03-19T20:13:26.578840Z",
                    "start_time": "2021-03-19T20:13:26.313049Z"
                },
                "execution": {
                    "iopub.execute_input": "2021-09-26T22:41:56.780897Z",
                    "iopub.status.busy": "2021-09-26T22:41:56.780138Z",
                    "iopub.status.idle": "2021-09-26T22:41:56.988481Z",
                    "shell.execute_reply": "2021-09-26T22:41:56.989070Z"
                }
            },
            "outputs": [
                {
                    "data": {
                        "image/png": 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\n",
                        "text/plain": [
                            "<Figure size 480x320 with 1 Axes>"
                        ]
                    },
                    "metadata": {
                        "needs_background": "light"
                    },
                    "output_type": "display_data"
                },
                {
                    "data": {
                        "text/plain": [
                            "(<Figure size 480x320 with 1 Axes>, <AxesSubplot:xlabel='Time [s]'>)"
                        ]
                    },
                    "execution_count": 18,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "ss.TDS.plotter.plot(ss.TGOV1.paux)"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 19,
            "metadata": {
                "ExecuteTime": {
                    "end_time": "2021-03-19T20:13:26.866303Z",
                    "start_time": "2021-03-19T20:13:26.583667Z"
                },
                "execution": {
                    "iopub.execute_input": "2021-09-26T22:41:56.991745Z",
                    "iopub.status.busy": "2021-09-26T22:41:56.991033Z",
                    "iopub.status.idle": "2021-09-26T22:41:57.284121Z",
                    "shell.execute_reply": "2021-09-26T22:41:57.284691Z"
                }
            },
            "outputs": [
                {
                    "data": {
                        "image/png": 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\n",
                        "text/plain": [
                            "<Figure size 480x320 with 1 Axes>"
                        ]
                    },
                    "metadata": {
                        "needs_background": "light"
                    },
                    "output_type": "display_data"
                },
                {
                    "data": {
                        "text/plain": [
                            "(<Figure size 480x320 with 1 Axes>, <AxesSubplot:xlabel='Time [s]'>)"
                        ]
                    },
                    "execution_count": 19,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "ss.TDS.plotter.plot(ss.GENROU.omega)"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 20,
            "metadata": {
                "execution": {
                    "iopub.execute_input": "2021-09-26T22:41:57.287146Z",
                    "iopub.status.busy": "2021-09-26T22:41:57.286493Z",
                    "iopub.status.idle": "2021-09-26T22:41:58.279313Z",
                    "shell.execute_reply": "2021-09-26T22:41:58.278821Z"
                }
            },
            "outputs": [
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": [
                        "\"/home/hacui/repos/andes/examples/kundur_full_out.npz\" removed.\r\n",
                        "\"/home/hacui/repos/andes/examples/kundur_full_out.txt\" removed.\r\n",
                        "\"/home/hacui/repos/andes/examples/kundur_full_out.lst\" removed.\r\n"
                    ]
                }
            ],
            "source": [
                "!andes misc -C"
            ]
        }
    ],
    "metadata": {
        "kernelspec": {
            "display_name": "Python 3 (ipykernel)",
            "language": "python",
            "name": "python3"
        },
        "language_info": {
            "codemirror_mode": {
                "name": "ipython",
                "version": 3
            },
            "file_extension": ".py",
            "mimetype": "text/x-python",
            "name": "python",
            "nbconvert_exporter": "python",
            "pygments_lexer": "ipython3",
            "version": "3.9.10"
        },
        "varInspector": {
            "cols": {
                "lenName": 16,
                "lenType": 16,
                "lenVar": 40
            },
            "kernels_config": {
                "python": {
                    "delete_cmd_postfix": "",
                    "delete_cmd_prefix": "del ",
                    "library": "var_list.py",
                    "varRefreshCmd": "print(var_dic_list())"
                },
                "r": {
                    "delete_cmd_postfix": ") ",
                    "delete_cmd_prefix": "rm(",
                    "library": "var_list.r",
                    "varRefreshCmd": "cat(var_dic_list()) "
                }
            },
            "types_to_exclude": [
                "module",
                "function",
                "builtin_function_or_method",
                "instance",
                "_Feature"
            ],
            "window_display": false
        }
    },
    "nbformat": 4,
    "nbformat_minor": 4
}