{
    "cells": [
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "# ANDES Demonstration of HYGOV on IEEE 14-Bus System\n",
                "\n",
                "Prepared by Jinning Wang. Last revised on December 15, 2021."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 1,
            "metadata": {},
            "outputs": [],
            "source": [
                "import andes\n",
                "from andes.utils.paths import get_case\n",
                "\n",
                "andes.config_logger(stream_level=20)"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 2,
            "metadata": {},
            "outputs": [
                {
                    "name": "stderr",
                    "output_type": "stream",
                    "text": [
                        "Working directory: \"/Users/jinningwang/Documents/work/andes/examples/demonstration\"\n",
                        "Loaded config from file \"/Users/jinningwang/.andes/andes.rc\"\n",
                        "Loaded generated Python code in \"/Users/jinningwang/.andes/pycode\".\n",
                        "Parsing input file \"/Users/jinningwang/Documents/work/andes/andes/cases/ieee14/ieee14_hygov.xlsx\"...\n",
                        "Input file parsed in 0.3788 seconds.\n",
                        "System internal structure set up in 0.0324 seconds.\n"
                    ]
                },
                {
                    "data": {
                        "text/plain": [
                            "True"
                        ]
                    },
                    "execution_count": 2,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "ss = andes.load(get_case('ieee14/ieee14_hygov.xlsx'),\n",
                "                setup=False,\n",
                "                no_output=True)\n",
                "ss.setup()"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "## Simulation\n",
                "\n",
                "Turbine governor `HYGOV_1` is connected to `GENROU_5`."
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 3,
            "metadata": {
                "scrolled": true
            },
            "outputs": [
                {
                    "name": "stderr",
                    "output_type": "stream",
                    "text": [
                        "-> System connectivity check results:\n",
                        "  No islanded bus detected.\n",
                        "  A total of 1 island(s) detected.\n",
                        "  Each island has a slack bus correctly defined and enabled.\n",
                        "\n",
                        "-> Power flow calculation\n",
                        "   Sparse solver: KLU\n",
                        " Solution method: NR method\n",
                        "Numba compilation initiated with caching.\n",
                        "Power flow initialized in 0.3313 seconds.\n",
                        "0: |F(x)| = 0.5605182134\n",
                        "1: |F(x)| = 0.006202200332\n",
                        "2: |F(x)| = 5.819382825e-06\n",
                        "3: |F(x)| = 6.967745825e-12\n",
                        "Converged in 4 iterations in 0.0041 seconds.\n"
                    ]
                },
                {
                    "data": {
                        "text/plain": [
                            "True"
                        ]
                    },
                    "execution_count": 3,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "ss.PFlow.run()"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 4,
            "metadata": {},
            "outputs": [
                {
                    "name": "stderr",
                    "output_type": "stream",
                    "text": [
                        "\n",
                        "-> Time Domain Simulation Summary:\n",
                        "Sparse Solver: KLU\n",
                        "Simulation time: 0.0-20 s.\n",
                        "Fixed step size: h=33.33 ms. Shrink if not converged.\n",
                        "Numba compilation initiated with caching.\n",
                        "Initialization for dynamics completed in 0.2339 seconds.\n",
                        "Initialization was successful.\n"
                    ]
                },
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": [
                        "<Toggle Toggle_1>: Line.Line_1 status changed to 0 at t=1.0 sec.    \n",
                        "<Toggle Toggle_2>: Line.Line_1 status changed to 1 at t=1.1 sec.    \n",
                        "100%|███████████████████████████████| 100/100 [00:00<00:00, 102.64%/s]"
                    ]
                },
                {
                    "name": "stderr",
                    "output_type": "stream",
                    "text": [
                        "Simulation completed in 0.9746 seconds.\n"
                    ]
                },
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": [
                        "\n"
                    ]
                },
                {
                    "data": {
                        "text/plain": [
                            "True"
                        ]
                    },
                    "execution_count": 4,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "ss.TDS.config.tf = 20\n",
                "ss.TDS.run()"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 5,
            "metadata": {},
            "outputs": [
                {
                    "data": {
                        "image/png": 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\n",
                        "text/plain": [
                            "<Figure size 600x400 with 1 Axes>"
                        ]
                    },
                    "metadata": {
                        "needs_background": "light"
                    },
                    "output_type": "display_data"
                },
                {
                    "data": {
                        "image/png": 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\n",
                        "text/plain": [
                            "<Figure size 600x400 with 1 Axes>"
                        ]
                    },
                    "metadata": {
                        "needs_background": "light"
                    },
                    "output_type": "display_data"
                },
                {
                    "data": {
                        "text/plain": [
                            "(<Figure size 600x400 with 1 Axes>, <AxesSubplot:xlabel='Time [s]'>)"
                        ]
                    },
                    "execution_count": 5,
                    "metadata": {},
                    "output_type": "execute_result"
                }
            ],
            "source": [
                "ss.TDS.plt.plot(ss.HYGOV.pout)\n",
                "ss.TDS.plt.plot(ss.TGOV1.pout)"
            ]
        },
        {
            "cell_type": "markdown",
            "metadata": {},
            "source": [
                "## Cleanup"
            ]
        },
        {
            "cell_type": "code",
            "execution_count": 6,
            "metadata": {},
            "outputs": [
                {
                    "name": "stdout",
                    "output_type": "stream",
                    "text": [
                        "\r\n",
                        "    _           _         | Version 1.5.6.post65+ga6129ca0\r\n",
                        "   /_\\  _ _  __| |___ ___ | Python 3.7.10 on Darwin, 12/16/2021 02:25:41 PM\r\n",
                        "  / _ \\| ' \\/ _` / -_|_-< | \r\n",
                        " /_/ \\_\\_||_\\__,_\\___/__/ | This program comes with ABSOLUTELY NO WARRANTY.\r\n",
                        "\r\n",
                        "No output file found in the working directory.\r\n"
                    ]
                }
            ],
            "source": [
                "!andes misc -C"
            ]
        }
    ],
    "metadata": {
        "interpreter": {
            "hash": "b8c542af61804583455bb3cc02c5acff1b7eab71b36b048085e6e502c5a0f30d"
        },
        "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": "3.7.10"
        }
    },
    "nbformat": 4,
    "nbformat_minor": 2
}