pypsa-eur/notebooks/intermed-results.ipynb

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  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import yaml"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "with open('../config.yaml') as f:\n",
    "    config = yaml.load(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from vresutils import shapes as vshapes\n",
    "from vresutils import plot as vplot"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pypsa\n",
    "import numpy as np\n",
    "import xarray as xr\n",
    "import pandas as pd\n",
    "import geopandas as gpd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib as mpl\n",
    "import matplotlib.pyplot as plt\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "n = pypsa.Network(\"../networks/base.nc\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Regions and p_nom_max"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Onshore"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "regions = gpd.read_file('../resources/regions_onshore.geojson').set_index('id')\n",
    "regions.index.name = 'name'\n",
    "regions['area'] = regions.to_crs(dict(proj='aea')).area / 1e6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds = xr.open_dataset('../resources/profile_onwind.nc')\n",
    "p_nom_max = ds['p_nom_max']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds['profile'].mean()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds.sel(name=ds['profile'].mean('time') > 0.01)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots(figsize=(12, 8))\n",
    "plt.colorbar(vplot.shapes(regions['geometry'], p_nom_max.to_pandas()/regions['area'], ax=ax))\n",
    "ax.set_aspect('equal')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds['profile'].mean('time')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots(figsize=(12, 8))\n",
    "plt.colorbar(vplot.shapes(regions['geometry'], ds['profile'].mean('time').to_pandas(), ax=ax))\n",
    "ax.set_aspect('equal')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Offshore"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "regions = gpd.read_file('../resources/regions_offshore.geojson').set_index('id')\n",
    "regions.index.name = 'name'\n",
    "regions['area'] = regions.to_crs(dict(proj='aea')).area / 1e6"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "ds = xr.open_dataset('../resources/profile_offwind.nc')\n",
    "p_nom_max = ds['p_nom_max']\n",
    "\n",
    "fig, ax = plt.subplots(figsize=(12, 8))\n",
    "plt.colorbar(vplot.shapes(regions['geometry'], p_nom_max.to_pandas()/regions['area'], ax=ax))\n",
    "ax.set_aspect('equal')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "potentials = xr.open_dataarray('../resources/potentials_onwind.nc')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "vsha"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "vshapes.country_cover(config['countries']).bounds"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "vplot.shapes([vshapes.country_cover(config['countries'])])\n",
    "vplot.shapes([vshapes.country_cover(config['countries'], include_eez=False)], facecolors='yellow')\n",
    "vplot.shapes(vshapes.countries(config['countries']), facecolors='None')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "fig, ax = plt.subplots(figsize=(12, 8))\n",
    "potentials.plot()\n",
    "#vplot.shapes(regions['geometry'], p_nom_max.to_pandas() == 0., facecolors='None', ax=ax)\n",
    "\n",
    "ax.set_aspect('equal')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import atlite"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "atlite.Cutout(config['renewable']['onwind']['cutout'])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
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   "cell_type": "code",
   "execution_count": null,
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