{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Security-Constrained Optimisation\n",
    "\n",
    "In this example, the dispatch of generators is optimised using the security-constrained linear OPF, to guaranteed that no branches are overloaded by certain branch outages."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pypsa, os\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "network = pypsa.examples.scigrid_de(from_master=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "There are some infeasibilities without line extensions."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "for line_name in [\"316\", \"527\", \"602\"]:\n",
    "    network.lines.loc[line_name, \"s_nom\"] = 1200\n",
    "\n",
    "now = network.snapshots[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Performing security-constrained linear OPF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "branch_outages = network.lines.index[:15]\n",
    "network.sclopf(now, branch_outages=branch_outages, solver_name=\"cbc\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "For the PF, set the P to the optimised P."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "network.generators_t.p_set = network.generators_t.p_set.reindex(\n",
    "    columns=network.generators.index\n",
    ")\n",
    "network.generators_t.p_set.loc[now] = network.generators_t.p.loc[now]\n",
    "\n",
    "network.storage_units_t.p_set = network.storage_units_t.p_set.reindex(\n",
    "    columns=network.storage_units.index\n",
    ")\n",
    "network.storage_units_t.p_set.loc[now] = network.storage_units_t.p.loc[now]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Check no lines are overloaded with the linear contingency analysis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "p0_test = network.lpf_contingency(now, branch_outages=branch_outages)\n",
    "p0_test"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Check loading as per unit of s_nom in each contingency"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "max_loading = (\n",
    "    abs(p0_test.divide(network.passive_branches().s_nom, axis=0)).describe().loc[\"max\"]\n",
    ")\n",
    "max_loading"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "np.allclose(max_loading, np.ones((len(max_loading))))"
   ]
  }
 ],
 "metadata": {
  "@webio": {
   "lastCommId": null,
   "lastKernelId": null
  },
  "kernelspec": {
   "display_name": "",
   "language": "python",
   "name": ""
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}