examples/Ex2_EnterService.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "2cdfb179",
   "metadata": {},
   "source": [
    "# Dynamic Simulation of Enter Service Performance"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "063086ae",
   "metadata": {},
   "outputs": [],
   "source": [
    "from opender import DER, DER_PV\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ac5d2f7d",
   "metadata": {},
   "source": [
    "### Enter Service Ramp"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "9da1a26e",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create OpenDER object and configure enter service delay as 50s, enter service ramp time as 100s\n",
    "der_obj = DER_PV()\n",
    "der_obj.der_file.ES_DELAY = 50\n",
    "der_obj.der_file.ES_RAMP_RATE = 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "84496ef3",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Initialize DER in Trip state\n",
    "der_obj.der_file.STATUS_INIT = 'OFF'\n",
    "der_obj.der_file.ES_PERMIT_SERVICE = False\n",
    "der_obj.update_der_input(v_pu=1, f=60, p_dc_pu=1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "fd96f567",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Configure dynamic simulation timestep\n",
    "t_s = 1\n",
    "DER.t_s = t_s\n",
    "t = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "710b534c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Prepare arrays for plotting\n",
    "t_plot = []\n",
    "v_plot = []\n",
    "p_plot = []\n",
    "stat_plot = []"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "b509bb5c",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Simulate for 200s\n",
    "while t < 200:\n",
    "    \n",
    "    # At 25s, permit DER to enter service\n",
    "    if t> 25:\n",
    "        der_obj.der_file.ES_PERMIT_SERVICE = True\n",
    "\n",
    "    # calculate output power each time step\n",
    "    P, Q = der_obj.run()\n",
    "\n",
    "    # save result\n",
    "    t_plot.append(t)\n",
    "    p_plot.append(der_obj.p_out_pu)\n",
    "    stat_plot.append(der_obj.der_status)\n",
    "    v_plot.append(der_obj.der_input.v_meas_pu)\n",
    "\n",
    "    # increase t\n",
    "    t = t + t_s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "9cf200de",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot figure\n",
    "fig = plt.figure()\n",
    "plt.clf()\n",
    "ax1=plt.subplot(2, 1, 1)\n",
    "plt.plot(t_plot, p_plot, label='P_out (pu)')\n",
    "plt.grid()\n",
    "plt.legend()\n",
    "plt.subplot(2, 1, 2, sharex=ax1)\n",
    "plt.plot(t_plot, stat_plot, label='DER status')\n",
    "plt.grid()\n",
    "plt.legend()\n",
    "plt.xlabel('Time (s)')\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "81ed658f",
   "metadata": {},
   "source": [
    "Notice the DER takes a delay of 50s after receiving the permit service signal, before entering service. The enter service ramp takes 100s."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cb799732",
   "metadata": {},
   "source": [
    "### Enter Service Randomized Delay"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "7a0e8159",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Reset DER, disable enter service ramp, and enable randomized delay\n",
    "der_obj.reinitialize()\n",
    "der_obj.der_file.ES_PERMIT_SERVICE = False\n",
    "der_obj.update_der_input(v_pu=1, f=60, p_dc_pu=1)\n",
    "der_obj.der_file.ES_RAMP_RATE = 0\n",
    "der_obj.der_file.ES_RANDOMIZED_DELAY = 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "8b8e6e7f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Configure dynamic simulation timestep\n",
    "t_s = 1\n",
    "DER.t_s = t_s\n",
    "t = 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "8f890bf1",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Prepare arrays for plotting\n",
    "t_plot = []\n",
    "v_plot = []\n",
    "p_plot = []\n",
    "stat_plot = []"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "de496c1f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Simulate for 200s\n",
    "while t < 200:\n",
    "    \n",
    "    # At 25s, permit DER to enter service\n",
    "    if t> 25:\n",
    "        der_obj.der_file.ES_PERMIT_SERVICE = True\n",
    "\n",
    "    # calculate output power each time step\n",
    "    P, Q = der_obj.run()\n",
    "\n",
    "    # save result\n",
    "    t_plot.append(t)\n",
    "    p_plot.append(der_obj.p_out_pu)\n",
    "    stat_plot.append(der_obj.der_status)\n",
    "    v_plot.append(der_obj.der_input.v_meas_pu)\n",
    "\n",
    "    # increase t\n",
    "    t = t + t_s"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "fa3d9b8d",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# plot figure\n",
    "fig = plt.figure()\n",
    "plt.clf()\n",
    "ax1=plt.subplot(2, 1, 1)\n",
    "plt.plot(t_plot, p_plot, label='P_out (pu)')\n",
    "plt.grid()\n",
    "plt.legend()\n",
    "plt.subplot(2, 1, 2, sharex=ax1)\n",
    "plt.plot(t_plot, stat_plot, label='DER status')\n",
    "plt.grid()\n",
    "plt.legend()\n",
    "plt.xlabel('Time (s)')\n",
    "plt.tight_layout()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5d870c81",
   "metadata": {},
   "source": [
    "Notice the DER took an additional randomized delay of 100s after the 50s delay to enter service. This is an exception to the ramp start for DER plants < 500kVA."
   ]
  }
 ],
 "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": "3.7.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}