4_east_west_(flatten_the_duck).ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "d0b8eb02-b436-4326-ba65-2befa30a89ce",
   "metadata": {},
   "source": [
    "In this notebook, we try to investigate the impact of east-west on the demand curve. We assume that the capacity remains constant (therefore investment costs are similar). This is not necessarily realistic, as more capacity can be installed using east-west (as described \"East-west oriented photovoltaic power systems: model, benefits and  technical evaluation\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "df8e4492-a54b-44d0-adfe-9803e0587946",
   "metadata": {},
   "source": [
    "# Here we only investigate a single point (Oldenburg)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "ae02f1ad-c9de-4204-9356-38411d1c3e38",
   "metadata": {},
   "outputs": [],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "import xarray as xr\n",
    "from get_load import get_load"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "a15f50d7-a9f3-42ba-bf3b-f1f0ce5fc45f",
   "metadata": {},
   "outputs": [],
   "source": [
    "### Get load of Oldenburg\n",
    "\n",
    "avg_demand_per_inh = 2 # MWh/a, rough estimate --> https://www.destatis.de/DE/Themen/Gesellschaft-Umwelt/Umwelt/UGR/private-haushalte/Tabellen/stromverbrauch-haushalte.html\n",
    "inhabitants = 168000 # inhabitants in Oldenburg\n",
    "annual_demand_ol = avg_demand_per_inh*inhabitants #MWh/a\n",
    "annual_demand_ol = annual_demand_ol*1e3 # kWh/a"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "8b9b705c-bfba-4c47-8f4f-403262b5453a",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_elec_demand = get_load(2017, demand_y=annual_demand_ol)[\"h0\"] # h0 means residential"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "47f26716-762b-4d1e-8dc2-305b9cf90716",
   "metadata": {},
   "outputs": [],
   "source": [
    "df_elec_demand = df_elec_demand.to_xarray()\n",
    "df_elec_demand = df_elec_demand.rename({\"index\":\"time\"})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "0c9c393c-6c55-4519-b823-6a2bce7af94b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'hour of the day')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.plot(df_elec_demand.sel({\"time\":\"2017-01-01\"}).values, label=\"2017-01-01\")\n",
    "plt.plot(df_elec_demand.sel({\"time\":\"2017-06-01\"}).values, label=\"2017-06-01\")\n",
    "plt.legend()\n",
    "plt.ylabel(\"demand [kWh]\")\n",
    "plt.xlabel(\"hour of the day\")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "d4c1b88f-9d82-463c-b0fc-94fb3f9be5ee",
   "metadata": {},
   "source": [
    "# PV"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "04063123-4fd4-4111-9748-cddd189bfb5a",
   "metadata": {},
   "outputs": [],
   "source": [
    "from atlite.pv.solar_position import SolarPosition\n",
    "from atlite.pv.irradiation import TiltedIrradiation\n",
    "from atlite.pv.solar_panel_model import SolarPanelModel\n",
    "from atlite.pv.orientation import get_orientation, SurfaceOrientation\n",
    "from atlite.convert import pv, convert_pv, get_orientation,get_solarpanelconfig"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "ce0a187e-6abb-43a7-a463-abdcd1fc100b",
   "metadata": {},
   "outputs": [],
   "source": [
    "#### Get roughly estimate of PV capacity in Oldenburg in 2023\n",
    "capacity_ol = 0.22*inhabitants #kWp # https://www.rechnerphotovoltaik.de/photovoltaik/in/niedersachsen/oldenburg-oldb"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "f0dbafd8-0db4-4bb4-8ae9-df7d5eb4e25d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "36960.0"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "capacity_ol"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "41ae771c-bd57-465c-a443-ab801638812b",
   "metadata": {},
   "outputs": [],
   "source": [
    "ds = xr.open_dataset(\"assets/data_2017_germany.nc\")\n",
    "ds_oldenburg = ds.sel({\"x\": [8.25], \"y\": [53]})\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "eb327b45-0ee8-4198-873f-3cecec375995",
   "metadata": {},
   "outputs": [
    {
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       "  /* fallback to plain text repr when CSS is not injected (untrusted notebook) */\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-header {\n",
       "  padding-top: 6px;\n",
       "  padding-bottom: 6px;\n",
       "  margin-bottom: 4px;\n",
       "  border-bottom: solid 1px var(--xr-border-color);\n",
       "}\n",
       "\n",
       ".xr-header > div,\n",
       ".xr-header > ul {\n",
       "  display: inline;\n",
       "  margin-top: 0;\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-obj-type,\n",
       ".xr-array-name {\n",
       "  margin-left: 2px;\n",
       "  margin-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-obj-type {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-sections {\n",
       "  padding-left: 0 !important;\n",
       "  display: grid;\n",
       "  grid-template-columns: 150px auto auto 1fr 20px 20px;\n",
       "}\n",
       "\n",
       ".xr-section-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-section-item input {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-item input + label {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label {\n",
       "  cursor: pointer;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-item input:enabled + label:hover {\n",
       "  color: var(--xr-font-color0);\n",
       "}\n",
       "\n",
       ".xr-section-summary {\n",
       "  grid-column: 1;\n",
       "  color: var(--xr-font-color2);\n",
       "  font-weight: 500;\n",
       "}\n",
       "\n",
       ".xr-section-summary > span {\n",
       "  display: inline-block;\n",
       "  padding-left: 0.5em;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label {\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in + label:before {\n",
       "  display: inline-block;\n",
       "  content: '►';\n",
       "  font-size: 11px;\n",
       "  width: 15px;\n",
       "  text-align: center;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:disabled + label:before {\n",
       "  color: var(--xr-disabled-color);\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label:before {\n",
       "  content: '▼';\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked + label > span {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-section-summary,\n",
       ".xr-section-inline-details {\n",
       "  padding-top: 4px;\n",
       "  padding-bottom: 4px;\n",
       "}\n",
       "\n",
       ".xr-section-inline-details {\n",
       "  grid-column: 2 / -1;\n",
       "}\n",
       "\n",
       ".xr-section-details {\n",
       "  display: none;\n",
       "  grid-column: 1 / -1;\n",
       "  margin-bottom: 5px;\n",
       "}\n",
       "\n",
       ".xr-section-summary-in:checked ~ .xr-section-details {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-array-wrap {\n",
       "  grid-column: 1 / -1;\n",
       "  display: grid;\n",
       "  grid-template-columns: 20px auto;\n",
       "}\n",
       "\n",
       ".xr-array-wrap > label {\n",
       "  grid-column: 1;\n",
       "  vertical-align: top;\n",
       "}\n",
       "\n",
       ".xr-preview {\n",
       "  color: var(--xr-font-color3);\n",
       "}\n",
       "\n",
       ".xr-array-preview,\n",
       ".xr-array-data {\n",
       "  padding: 0 5px !important;\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-array-data,\n",
       ".xr-array-in:checked ~ .xr-array-preview {\n",
       "  display: none;\n",
       "}\n",
       "\n",
       ".xr-array-in:checked ~ .xr-array-data,\n",
       ".xr-array-preview {\n",
       "  display: inline-block;\n",
       "}\n",
       "\n",
       ".xr-dim-list {\n",
       "  display: inline-block !important;\n",
       "  list-style: none;\n",
       "  padding: 0 !important;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list li {\n",
       "  display: inline-block;\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "}\n",
       "\n",
       ".xr-dim-list:before {\n",
       "  content: '(';\n",
       "}\n",
       "\n",
       ".xr-dim-list:after {\n",
       "  content: ')';\n",
       "}\n",
       "\n",
       ".xr-dim-list li:not(:last-child):after {\n",
       "  content: ',';\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-has-index {\n",
       "  font-weight: bold;\n",
       "}\n",
       "\n",
       ".xr-var-list,\n",
       ".xr-var-item {\n",
       "  display: contents;\n",
       "}\n",
       "\n",
       ".xr-var-item > div,\n",
       ".xr-var-item label,\n",
       ".xr-var-item > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-even);\n",
       "  margin-bottom: 0;\n",
       "}\n",
       "\n",
       ".xr-var-item > .xr-var-name:hover span {\n",
       "  padding-right: 5px;\n",
       "}\n",
       "\n",
       ".xr-var-list > li:nth-child(odd) > div,\n",
       ".xr-var-list > li:nth-child(odd) > label,\n",
       ".xr-var-list > li:nth-child(odd) > .xr-var-name span {\n",
       "  background-color: var(--xr-background-color-row-odd);\n",
       "}\n",
       "\n",
       ".xr-var-name {\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-var-dims {\n",
       "  grid-column: 2;\n",
       "}\n",
       "\n",
       ".xr-var-dtype {\n",
       "  grid-column: 3;\n",
       "  text-align: right;\n",
       "  color: var(--xr-font-color2);\n",
       "}\n",
       "\n",
       ".xr-var-preview {\n",
       "  grid-column: 4;\n",
       "}\n",
       "\n",
       ".xr-var-name,\n",
       ".xr-var-dims,\n",
       ".xr-var-dtype,\n",
       ".xr-preview,\n",
       ".xr-attrs dt {\n",
       "  white-space: nowrap;\n",
       "  overflow: hidden;\n",
       "  text-overflow: ellipsis;\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-var-name:hover,\n",
       ".xr-var-dims:hover,\n",
       ".xr-var-dtype:hover,\n",
       ".xr-attrs dt:hover {\n",
       "  overflow: visible;\n",
       "  width: auto;\n",
       "  z-index: 1;\n",
       "}\n",
       "\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  display: none;\n",
       "  background-color: var(--xr-background-color) !important;\n",
       "  padding-bottom: 5px !important;\n",
       "}\n",
       "\n",
       ".xr-var-attrs-in:checked ~ .xr-var-attrs,\n",
       ".xr-var-data-in:checked ~ .xr-var-data {\n",
       "  display: block;\n",
       "}\n",
       "\n",
       ".xr-var-data > table {\n",
       "  float: right;\n",
       "}\n",
       "\n",
       ".xr-var-name span,\n",
       ".xr-var-data,\n",
       ".xr-attrs {\n",
       "  padding-left: 25px !important;\n",
       "}\n",
       "\n",
       ".xr-attrs,\n",
       ".xr-var-attrs,\n",
       ".xr-var-data {\n",
       "  grid-column: 1 / -1;\n",
       "}\n",
       "\n",
       "dl.xr-attrs {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  display: grid;\n",
       "  grid-template-columns: 125px auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
       "  margin: 0;\n",
       "  float: left;\n",
       "  padding-right: 10px;\n",
       "  width: auto;\n",
       "}\n",
       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
       "}\n",
       "\n",
       ".xr-attrs dt:hover span {\n",
       "  display: inline-block;\n",
       "  background: var(--xr-background-color);\n",
       "  padding-right: 10px;\n",
       "}\n",
       "\n",
       ".xr-attrs dd {\n",
       "  grid-column: 2;\n",
       "  white-space: pre-wrap;\n",
       "  word-break: break-all;\n",
       "}\n",
       "\n",
       ".xr-icon-database,\n",
       ".xr-icon-file-text2 {\n",
       "  display: inline-block;\n",
       "  vertical-align: middle;\n",
       "  width: 1em;\n",
       "  height: 1.5em !important;\n",
       "  stroke-width: 0;\n",
       "  stroke: currentColor;\n",
       "  fill: currentColor;\n",
       "}\n",
       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.Dataset&gt;\n",
       "Dimensions:   (time: 8760, y: 1, x: 1)\n",
       "Coordinates:\n",
       "  * time      (time) datetime64[ns] 2017-01-01 ... 2017-12-31T23:00:00\n",
       "  * y         (y) float32 53.0\n",
       "    lat       (y) float32 53.0\n",
       "  * x         (x) float32 8.25\n",
       "    lon       (x) float32 8.25\n",
       "Data variables:\n",
       "    altitude  (time, y, x) float64 -1.038 -0.9689 -0.8514 ... -0.9682 -1.038\n",
       "    azimuth   (time, y, x) float64 0.2353 0.6676 1.012 ... 5.266 5.61 6.042</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.Dataset</div></div><ul class='xr-sections'><li class='xr-section-item'><input id='section-a7da3a7c-726b-47cf-92b1-5b472ee74159' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-a7da3a7c-726b-47cf-92b1-5b472ee74159' class='xr-section-summary'  title='Expand/collapse section'>Dimensions:</label><div class='xr-section-inline-details'><ul class='xr-dim-list'><li><span class='xr-has-index'>time</span>: 8760</li><li><span class='xr-has-index'>y</span>: 1</li><li><span class='xr-has-index'>x</span>: 1</li></ul></div><div class='xr-section-details'></div></li><li class='xr-section-item'><input id='section-cf340a31-e21e-4421-8641-3bb7b9c736a2' class='xr-section-summary-in' type='checkbox'  checked><label for='section-cf340a31-e21e-4421-8641-3bb7b9c736a2' class='xr-section-summary' >Coordinates: <span>(5)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>time</span></div><div class='xr-var-dims'>(time)</div><div class='xr-var-dtype'>datetime64[ns]</div><div class='xr-var-preview xr-preview'>2017-01-01 ... 2017-12-31T23:00:00</div><input id='attrs-d8a2cdcf-b59a-4d00-91d6-0b6805b2df16' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-d8a2cdcf-b59a-4d00-91d6-0b6805b2df16' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-17b9fb5e-5f3e-4026-bfee-4a453154b1ec' class='xr-var-data-in' type='checkbox'><label for='data-17b9fb5e-5f3e-4026-bfee-4a453154b1ec' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>long_name :</span></dt><dd>time</dd></dl></div><div class='xr-var-data'><pre>array([&#x27;2017-01-01T00:00:00.000000000&#x27;, &#x27;2017-01-01T01:00:00.000000000&#x27;,\n",
       "       &#x27;2017-01-01T02:00:00.000000000&#x27;, ..., &#x27;2017-12-31T21:00:00.000000000&#x27;,\n",
       "       &#x27;2017-12-31T22:00:00.000000000&#x27;, &#x27;2017-12-31T23:00:00.000000000&#x27;],\n",
       "      dtype=&#x27;datetime64[ns]&#x27;)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>y</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>53.0</div><input id='attrs-369c05fc-4dd0-4c58-9f15-900af4bd6b9f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-369c05fc-4dd0-4c58-9f15-900af4bd6b9f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-8bdbae48-f584-480c-94ee-bbb105c630fb' class='xr-var-data-in' type='checkbox'><label for='data-8bdbae48-f584-480c-94ee-bbb105c630fb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([53.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>(y)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>53.0</div><input id='attrs-1f51bf50-678a-449a-b9f3-497d832b7535' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-1f51bf50-678a-449a-b9f3-497d832b7535' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d2f3b246-7563-46d9-9f34-5b46ec8aa1e4' class='xr-var-data-in' type='checkbox'><label for='data-d2f3b246-7563-46d9-9f34-5b46ec8aa1e4' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array([53.], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span class='xr-has-index'>x</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>8.25</div><input id='attrs-3fa9daa1-e56a-4fbf-a35d-0b75efa99da7' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-3fa9daa1-e56a-4fbf-a35d-0b75efa99da7' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-b1221f4e-8b53-4c8f-ba6b-0c918cbfa3cc' class='xr-var-data-in' type='checkbox'><label for='data-b1221f4e-8b53-4c8f-ba6b-0c918cbfa3cc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([8.25], dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>(x)</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>8.25</div><input id='attrs-795c0900-78da-412f-82f8-475b3d2a350e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-795c0900-78da-412f-82f8-475b3d2a350e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-56dd6531-a140-44b1-82e1-0458f687a2bb' class='xr-var-data-in' type='checkbox'><label for='data-56dd6531-a140-44b1-82e1-0458f687a2bb' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array([8.25], dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e51ba6f6-20c0-4831-b870-ac3cea4a622f' class='xr-section-summary-in' type='checkbox'  checked><label for='section-e51ba6f6-20c0-4831-b870-ac3cea4a622f' class='xr-section-summary' >Data variables: <span>(2)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>altitude</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>-1.038 -0.9689 ... -0.9682 -1.038</div><input id='attrs-0fc3483e-4db2-4911-8359-9b9cc7f2f148' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0fc3483e-4db2-4911-8359-9b9cc7f2f148' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-6e175314-75a4-426f-889c-8768946bcda9' class='xr-var-data-in' type='checkbox'><label for='data-6e175314-75a4-426f-889c-8768946bcda9' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>time shift :</span></dt><dd>0 days 00:00:00</dd><dt><span>units :</span></dt><dd>rad</dd></dl></div><div class='xr-var-data'><pre>array([[[-1.03808056]],\n",
       "\n",
       "       [[-0.96888788]],\n",
       "\n",
       "       [[-0.85138495]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[-0.85026135]],\n",
       "\n",
       "       [[-0.96815243]],\n",
       "\n",
       "       [[-1.03801653]]])</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>azimuth</span></div><div class='xr-var-dims'>(time, y, x)</div><div class='xr-var-dtype'>float64</div><div class='xr-var-preview xr-preview'>0.2353 0.6676 1.012 ... 5.61 6.042</div><input id='attrs-c95fc94d-e067-4f2c-8cfc-8ebee12057cb' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-c95fc94d-e067-4f2c-8cfc-8ebee12057cb' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-01134ba3-3a7b-409e-b33f-59c1d0e213cd' class='xr-var-data-in' type='checkbox'><label for='data-01134ba3-3a7b-409e-b33f-59c1d0e213cd' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>time shift :</span></dt><dd>0 days 00:00:00</dd><dt><span>units :</span></dt><dd>rad</dd></dl></div><div class='xr-var-data'><pre>array([[[0.23529552]],\n",
       "\n",
       "       [[0.66764435]],\n",
       "\n",
       "       [[1.01244277]],\n",
       "\n",
       "       ...,\n",
       "\n",
       "       [[5.26645323]],\n",
       "\n",
       "       [[5.61036858]],\n",
       "\n",
       "       [[6.04197772]]])</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-2fa448c8-80b4-4e53-8ce0-fba9b55fe777' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-2fa448c8-80b4-4e53-8ce0-fba9b55fe777' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.Dataset>\n",
       "Dimensions:   (time: 8760, y: 1, x: 1)\n",
       "Coordinates:\n",
       "  * time      (time) datetime64[ns] 2017-01-01 ... 2017-12-31T23:00:00\n",
       "  * y         (y) float32 53.0\n",
       "    lat       (y) float32 53.0\n",
       "  * x         (x) float32 8.25\n",
       "    lon       (x) float32 8.25\n",
       "Data variables:\n",
       "    altitude  (time, y, x) float64 -1.038 -0.9689 -0.8514 ... -0.9682 -1.038\n",
       "    azimuth   (time, y, x) float64 0.2353 0.6676 1.012 ... 5.266 5.61 6.042"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "time_shift = 0 # relevant if sarah-2 data is used\n",
    "solar_position = SolarPosition(ds_oldenburg, time_shift)\n",
    "solar_position.load() # this takes some time"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "4ef3732d-9a59-41e3-b1b7-c9aae4e32b75",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "{'slope': 50.0, 'azimuth': 90}\n",
      "{'slope': 40.0, 'azimuth': 180}\n",
      "{'slope': 50.0, 'azimuth': 270}\n",
      "CPU times: user 157 ms, sys: 8.78 ms, total: 165 ms\n",
      "Wall time: 164 ms\n"
     ]
    }
   ],
   "source": [
    "%%time \n",
    "\n",
    "def get_pv(orientation):\n",
    "    panel = \"CSi\"\n",
    "    panel = get_solarpanelconfig(panel)\n",
    "    print(orientation)\n",
    "    orientation = get_orientation(orientation)\n",
    "    \n",
    "    surface_orientation = SurfaceOrientation(ds_oldenburg, solar_position, orientation)\n",
    "    irradiation = TiltedIrradiation(\n",
    "        ds_oldenburg,\n",
    "        solar_position,\n",
    "        surface_orientation,\n",
    "        trigon_model=\"simple\",\n",
    "        clearsky_model=\"simple\",\n",
    "    )\n",
    "    ds_oldenburg_cf = SolarPanelModel(ds_oldenburg, irradiation, panel)\n",
    "    #ds_oldenburg_cf = (solar_panel * capacity_ol)\n",
    "    ds_oldenburg_cf = ds_oldenburg_cf.isel({\"x\":0,\"y\":0})\n",
    "    return ds_oldenburg_cf\n",
    "\n",
    "\n",
    "ds_east = get_pv({'slope': 50., 'azimuth': 90})\n",
    "ds_south = get_pv({'slope': 40., 'azimuth': 180})\n",
    "ds_west = get_pv({'slope': 50., 'azimuth': 270})"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5c41208d-4549-4e3a-9886-c0e272165d8f",
   "metadata": {
    "tags": []
   },
   "source": [
    "# The duck curve"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2496ba4a-f6f1-4a9d-bd87-fa497fc0500f",
   "metadata": {},
   "source": [
    "![asd](assets/duck_curve.jpg)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9414e23d-e38d-4e26-b542-9ba65d8575ea",
   "metadata": {},
   "source": [
    "source: https://www.synergy.net.au/Blog/2021/10/Everything-you-need-to-know-about-the-Duck-Curve"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "03a06068-0ecf-48ef-988d-baf6eb2b5dd9",
   "metadata": {},
   "outputs": [],
   "source": [
    "# We assume to that the capacity further grows quickly to make results more obvious\n",
    "capacity_expansion_factor = 2 # multiplier of todays capacity"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "2d5bb7bd-a482-4579-bc6a-aca379099c34",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0, 'hour of the day')"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "dt = \"2017-06-01\"\n",
    "plt.plot((df_elec_demand).sel({\"time\":dt}), label=\"Demand\")\n",
    "plt.plot((df_elec_demand - ds_south*capacity_ol*capacity_expansion_factor).sel({\"time\":dt}), label=\"Residual demand (South)\")\n",
    "plt.plot((df_elec_demand - (ds_west*1/2 + ds_east*1/2)*capacity_ol*capacity_expansion_factor).sel({\"time\":dt}), label=\"Residual demand (East-West)\")\n",
    "plt.plot((df_elec_demand - (ds_west*1/3 + ds_south*1/3 + ds_east*1/3)*capacity_ol*capacity_expansion_factor).sel({\"time\":dt}), label=\"Residual demand (East-West-South)\")\n",
    "\n",
    "plt.legend()\n",
    "plt.ylabel(\"demand [kWh]\")\n",
    "plt.xlabel(\"hour of the day\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "74831d15-115d-430e-bab7-7181614e11c8",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "}\n",
       "\n",
       ".xr-attrs dt,\n",
       ".xr-attrs dd {\n",
       "  padding: 0;\n",
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       "\n",
       ".xr-attrs dt {\n",
       "  font-weight: normal;\n",
       "  grid-column: 1;\n",
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       "\n",
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       "\n",
       ".xr-attrs dd {\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray ()&gt;\n",
       "array(2.65838628e+08)\n",
       "Coordinates:\n",
       "    y        float32 53.0\n",
       "    lat      float32 53.0\n",
       "    x        float32 8.25\n",
       "    lon      float32 8.25</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-53a785cd-ab24-4f0f-a7db-fd0f85b385a3' class='xr-array-in' type='checkbox' checked><label for='section-53a785cd-ab24-4f0f-a7db-fd0f85b385a3' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>2.658e+08</span></div><div class='xr-array-data'><pre>array(2.65838628e+08)</pre></div></div></li><li class='xr-section-item'><input id='section-a8bfe238-477c-41cc-936d-1f2da63deb37' class='xr-section-summary-in' type='checkbox'  checked><label for='section-a8bfe238-477c-41cc-936d-1f2da63deb37' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>y</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>53.0</div><input id='attrs-9ad05d3b-33d2-4fda-ba09-6b8fd8fdfb3e' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-9ad05d3b-33d2-4fda-ba09-6b8fd8fdfb3e' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3d36a73d-b504-438d-88df-115b4e47c07c' class='xr-var-data-in' type='checkbox'><label for='data-3d36a73d-b504-438d-88df-115b4e47c07c' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array(53., dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>53.0</div><input id='attrs-0bfc37a4-e27a-4464-994c-9d8f78fb54a0' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0bfc37a4-e27a-4464-994c-9d8f78fb54a0' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-3e9fb725-f2b2-41cb-97ed-d3b2356c8dbc' class='xr-var-data-in' type='checkbox'><label for='data-3e9fb725-f2b2-41cb-97ed-d3b2356c8dbc' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array(53., dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>8.25</div><input id='attrs-4daf0042-c437-4d45-9193-03f52ad98d82' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-4daf0042-c437-4d45-9193-03f52ad98d82' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-54101090-63fb-4ff5-9b08-a6eee0a3a402' class='xr-var-data-in' type='checkbox'><label for='data-54101090-63fb-4ff5-9b08-a6eee0a3a402' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array(8.25, dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>8.25</div><input id='attrs-0d0e67de-fff3-418c-bb44-ef5ba56011fe' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-0d0e67de-fff3-418c-bb44-ef5ba56011fe' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-d4c7377e-2def-498a-88d3-c63e45746793' class='xr-var-data-in' type='checkbox'><label for='data-d4c7377e-2def-498a-88d3-c63e45746793' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array(8.25, dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-f9b03c3c-8896-43d1-8f3d-5d78470a41d3' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-f9b03c3c-8896-43d1-8f3d-5d78470a41d3' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray ()>\n",
       "array(2.65838628e+08)\n",
       "Coordinates:\n",
       "    y        float32 53.0\n",
       "    lat      float32 53.0\n",
       "    x        float32 8.25\n",
       "    lon      float32 8.25"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_t = (df_elec_demand - ds_south*capacity_ol*capacity_expansion_factor)\n",
    "ds_t.where(ds_t>0).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "7f470346-1a7a-4bb1-b342-99b888460a3a",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "\n",
       ".xr-attrs dt,\n",
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       "</style><pre class='xr-text-repr-fallback'>&lt;xarray.DataArray ()&gt;\n",
       "array(2.81837198e+08)\n",
       "Coordinates:\n",
       "    y        float32 53.0\n",
       "    lat      float32 53.0\n",
       "    x        float32 8.25\n",
       "    lon      float32 8.25</pre><div class='xr-wrap' style='display:none'><div class='xr-header'><div class='xr-obj-type'>xarray.DataArray</div><div class='xr-array-name'></div></div><ul class='xr-sections'><li class='xr-section-item'><div class='xr-array-wrap'><input id='section-6312fe12-66c3-4749-a456-24b290370950' class='xr-array-in' type='checkbox' checked><label for='section-6312fe12-66c3-4749-a456-24b290370950' title='Show/hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-array-preview xr-preview'><span>2.818e+08</span></div><div class='xr-array-data'><pre>array(2.81837198e+08)</pre></div></div></li><li class='xr-section-item'><input id='section-0614ce94-20b2-44b9-ade1-dd585ddb1596' class='xr-section-summary-in' type='checkbox'  checked><label for='section-0614ce94-20b2-44b9-ade1-dd585ddb1596' class='xr-section-summary' >Coordinates: <span>(4)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><ul class='xr-var-list'><li class='xr-var-item'><div class='xr-var-name'><span>y</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>53.0</div><input id='attrs-796bff12-d356-42b5-bb38-cdf8eddd527f' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-796bff12-d356-42b5-bb38-cdf8eddd527f' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-69861560-a44b-48c0-96e0-446633401418' class='xr-var-data-in' type='checkbox'><label for='data-69861560-a44b-48c0-96e0-446633401418' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array(53., dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lat</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>53.0</div><input id='attrs-8c1a6952-79a1-402d-86da-ce9696e6b4d2' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-8c1a6952-79a1-402d-86da-ce9696e6b4d2' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-98c93b87-782b-42c5-8a61-fcec179f16d1' class='xr-var-data-in' type='checkbox'><label for='data-98c93b87-782b-42c5-8a61-fcec179f16d1' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_north</dd><dt><span>long_name :</span></dt><dd>latitude</dd></dl></div><div class='xr-var-data'><pre>array(53., dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>x</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>8.25</div><input id='attrs-515db44f-4ba5-4ffb-be40-ac2a3494a03b' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-515db44f-4ba5-4ffb-be40-ac2a3494a03b' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-e2236237-05b8-47c5-9df7-d45385a528be' class='xr-var-data-in' type='checkbox'><label for='data-e2236237-05b8-47c5-9df7-d45385a528be' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array(8.25, dtype=float32)</pre></div></li><li class='xr-var-item'><div class='xr-var-name'><span>lon</span></div><div class='xr-var-dims'>()</div><div class='xr-var-dtype'>float32</div><div class='xr-var-preview xr-preview'>8.25</div><input id='attrs-430548be-f4c0-4058-ba72-c634881836d5' class='xr-var-attrs-in' type='checkbox' ><label for='attrs-430548be-f4c0-4058-ba72-c634881836d5' title='Show/Hide attributes'><svg class='icon xr-icon-file-text2'><use xlink:href='#icon-file-text2'></use></svg></label><input id='data-f7e8008d-3b5c-4f02-8fc1-f7c6026fd35d' class='xr-var-data-in' type='checkbox'><label for='data-f7e8008d-3b5c-4f02-8fc1-f7c6026fd35d' title='Show/Hide data repr'><svg class='icon xr-icon-database'><use xlink:href='#icon-database'></use></svg></label><div class='xr-var-attrs'><dl class='xr-attrs'><dt><span>units :</span></dt><dd>degrees_east</dd><dt><span>long_name :</span></dt><dd>longitude</dd></dl></div><div class='xr-var-data'><pre>array(8.25, dtype=float32)</pre></div></li></ul></div></li><li class='xr-section-item'><input id='section-e7e7df52-44ea-4059-b493-49b64f40e8b5' class='xr-section-summary-in' type='checkbox' disabled ><label for='section-e7e7df52-44ea-4059-b493-49b64f40e8b5' class='xr-section-summary'  title='Expand/collapse section'>Attributes: <span>(0)</span></label><div class='xr-section-inline-details'></div><div class='xr-section-details'><dl class='xr-attrs'></dl></div></li></ul></div></div>"
      ],
      "text/plain": [
       "<xarray.DataArray ()>\n",
       "array(2.81837198e+08)\n",
       "Coordinates:\n",
       "    y        float32 53.0\n",
       "    lat      float32 53.0\n",
       "    x        float32 8.25\n",
       "    lon      float32 8.25"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_t = df_elec_demand - (ds_west*capacity_ol + ds_east*capacity_ol)\n",
    "ds_t.where(ds_t>0).sum()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "c8033d62-da9f-43cb-956e-ce5ea3072450",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "036ca230-6dbf-45a3-b4c2-8fc4d43e66e1",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "70701.38338546651\n",
      "264761101.32086074\n"
     ]
    },
    {
     "data": {
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>16304.594982</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>53.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>8.25</td>\n",
       "      <td>8.25</td>\n",
       "      <td>-20514.790790</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>53.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>8.25</td>\n",
       "      <td>8.25</td>\n",
       "      <td>16544.769756</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>53.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>8.25</td>\n",
       "      <td>8.25</td>\n",
       "      <td>29068.591808</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>53.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>8.25</td>\n",
       "      <td>8.25</td>\n",
       "      <td>43295.007616</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>53.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>8.25</td>\n",
       "      <td>8.25</td>\n",
       "      <td>70701.383385</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            y     lat        x      lon          name\n",
       "count  8760.0  8760.0  8760.00  8760.00   8760.000000\n",
       "mean     53.0    53.0     8.25     8.25  30223.870014\n",
       "std       0.0     0.0     0.00     0.00  16304.594982\n",
       "min      53.0    53.0     8.25     8.25 -20514.790790\n",
       "25%      53.0    53.0     8.25     8.25  16544.769756\n",
       "50%      53.0    53.0     8.25     8.25  29068.591808\n",
       "75%      53.0    53.0     8.25     8.25  43295.007616\n",
       "max      53.0    53.0     8.25     8.25  70701.383385"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_t = (df_elec_demand - ds_south*capacity_ol*capacity_expansion_factor)\n",
    "print(ds_t.where(ds_t>0).max().values)\n",
    "print(ds_t.where(ds_t).sum().values)\n",
    "\n",
    "ds_all_south = ds_t.copy()\n",
    "ds_all_south.to_dataframe(\"name\").describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "d47fc312-8b60-4ae9-866a-87528dbded7a",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "70701.38338546651\n",
      "281837198.2725042\n"
     ]
    },
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>y</th>\n",
       "      <th>lat</th>\n",
       "      <th>x</th>\n",
       "      <th>lon</th>\n",
       "      <th>name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>8760.0</td>\n",
       "      <td>8760.0</td>\n",
       "      <td>8760.00</td>\n",
       "      <td>8760.00</td>\n",
       "      <td>8760.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>53.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>8.25</td>\n",
       "      <td>8.25</td>\n",
       "      <td>32173.196085</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
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       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>53.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>8.25</td>\n",
       "      <td>8.25</td>\n",
       "      <td>-0.570464</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>53.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>8.25</td>\n",
       "      <td>8.25</td>\n",
       "      <td>18452.616909</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>53.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>8.25</td>\n",
       "      <td>8.25</td>\n",
       "      <td>30945.123341</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>53.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>8.25</td>\n",
       "      <td>8.25</td>\n",
       "      <td>43295.007616</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>53.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>8.25</td>\n",
       "      <td>8.25</td>\n",
       "      <td>70701.383385</td>\n",
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      ],
      "text/plain": [
       "            y     lat        x      lon          name\n",
       "count  8760.0  8760.0  8760.00  8760.00   8760.000000\n",
       "mean     53.0    53.0     8.25     8.25  32173.196085\n",
       "std       0.0     0.0     0.00     0.00  14615.368694\n",
       "min      53.0    53.0     8.25     8.25     -0.570464\n",
       "25%      53.0    53.0     8.25     8.25  18452.616909\n",
       "50%      53.0    53.0     8.25     8.25  30945.123341\n",
       "75%      53.0    53.0     8.25     8.25  43295.007616\n",
       "max      53.0    53.0     8.25     8.25  70701.383385"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_t = df_elec_demand - (ds_west*1/2 + ds_east*1/2)*capacity_ol*capacity_expansion_factor\n",
    "print(ds_t.where(ds_t>0).max().values)\n",
    "print(ds_t.where(ds_t>0).sum().values)\n",
    "ds_east_west = ds_t.copy()\n",
    "ds_east_west.to_dataframe(\"name\").describe()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "d7b795c6-8e8d-4931-913f-9b4ea02d0f09",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "70701.38338546651\n",
      "276169556.1920192\n"
     ]
    },
    {
     "data": {
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       "</style>\n",
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>y</th>\n",
       "      <th>lat</th>\n",
       "      <th>x</th>\n",
       "      <th>lon</th>\n",
       "      <th>name</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>8760.0</td>\n",
       "      <td>8760.0</td>\n",
       "      <td>8760.00</td>\n",
       "      <td>8760.00</td>\n",
       "      <td>8760.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>53.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>8.25</td>\n",
       "      <td>8.25</td>\n",
       "      <td>31523.420728</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>0.0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.00</td>\n",
       "      <td>0.00</td>\n",
       "      <td>14941.827915</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>53.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>8.25</td>\n",
       "      <td>8.25</td>\n",
       "      <td>-4200.445271</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>53.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>8.25</td>\n",
       "      <td>8.25</td>\n",
       "      <td>17712.358754</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>53.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>8.25</td>\n",
       "      <td>8.25</td>\n",
       "      <td>30247.934805</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>53.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>8.25</td>\n",
       "      <td>8.25</td>\n",
       "      <td>43295.007616</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>53.0</td>\n",
       "      <td>53.0</td>\n",
       "      <td>8.25</td>\n",
       "      <td>8.25</td>\n",
       "      <td>70701.383385</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "            y     lat        x      lon          name\n",
       "count  8760.0  8760.0  8760.00  8760.00   8760.000000\n",
       "mean     53.0    53.0     8.25     8.25  31523.420728\n",
       "std       0.0     0.0     0.00     0.00  14941.827915\n",
       "min      53.0    53.0     8.25     8.25  -4200.445271\n",
       "25%      53.0    53.0     8.25     8.25  17712.358754\n",
       "50%      53.0    53.0     8.25     8.25  30247.934805\n",
       "75%      53.0    53.0     8.25     8.25  43295.007616\n",
       "max      53.0    53.0     8.25     8.25  70701.383385"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "ds_t = df_elec_demand - (ds_west*1/3 + ds_south*1/3 + ds_east*1/3)*capacity_ol*capacity_expansion_factor\n",
    "print(ds_t.where(ds_t>0).max().values)\n",
    "print(ds_t.where(ds_t>0).sum().values)\n",
    "ds_east_west_south = ds_t.copy()\n",
    "ds_east_west_south.to_dataframe(\"name\").describe()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "0c23b5ae-58c0-45c3-a1c6-6959b9bc8021",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 1.0, 'hourly mean in the entire year')"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "ds_all_south.groupby(\"time.hour\").mean().plot()\n",
    "ds_east_west.groupby(\"time.hour\").mean().plot()\n",
    "ds_east_west_south.groupby(\"time.hour\").mean().plot()\n",
    "plt.title(\"hourly mean in the entire year\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "3e7edf15-50bc-4079-b054-64ef4f5cea14",
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0, 0.5, 'Values')"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.boxplot([ds_all_south, ds_east_west, ds_east_west_south])\n",
    "\n",
    "# Adding titles and labels\n",
    "plt.title('Distribution of residual demands')\n",
    "plt.xticks([1, 2, 3], ['South', 'East-West', 'East-South-West'])\n",
    "plt.ylabel('Values')\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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