multi_period_tutorial-all-outputs.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "08aafd5e-a8e8-480e-b9bd-1a82be37d0f9",
   "metadata": {},
   "source": [
    "# Multi-period modelling in oemof-solph (Tutorial)\n",
    "Welcome to this tutorial! :-)\n",
    "\n",
    "You will learn how to use the new multi-period modelling feature from oemof.solph v0.5.1.<br> \n",
    "To be able to run the code, make sure you have all the necessary dependencies installed. Check out the README.md for info on that.\n",
    "\n",
    "Now let's get started rightaways!"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b2bc90c2-2d92-429c-b481-cb5a942c5fa2",
   "metadata": {},
   "source": [
    "# Package imports\n",
    "First, we need to import the required packages"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "4325cdea-ef13-4ca1-8f30-98e83a455791",
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import oemof.solph as solph\n",
    "\n",
    "from multiperiod_tutorial.analyze_results import (\n",
    "    prepare_results, plot_single_investment_variable_multiple_dfs\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cd63dcaf-c35b-4c68-833f-567fa70e6f90",
   "metadata": {},
   "source": [
    "# Define some settings\n",
    "Before we get started, we define some global settings here."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "714c0572-9247-49d8-bfe2-3d55485169e4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# If you want to use another solver, please change the variable here\n",
    "solver = \"cbc\"  # cbc, cplex, gurobi, gplk\n",
    "# Ensure that fontsize in plots is well readable\n",
    "plt.rcParams.update({'font.size': 12})"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "63b0609c-2aec-456a-b0e1-87038dc21b37",
   "metadata": {},
   "source": [
    "# Set up the energy system\n",
    "For this example, we set up a simplistic energy system.\n",
    "Graph of energy system\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "306a9e4c-688f-4782-a3a9-f01991761417",
   "metadata": {},
   "source": [
    "## Define time index and periods\n",
    "The first thing we do, is to define our time index and the periods.<br>\n",
    "To keep out example simple, we only consider three periods, corresponding to the years 2020, 2030 and 2040 with three hourly timesteps each."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "d0fc314a-564e-4e51-b8cf-32caaaf706a5",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Define three pd.date_range objects\n",
    "t_idx_1 = pd.date_range(\"1/1/2020\", periods=3, freq=\"H\")\n",
    "t_idx_2 = pd.date_range(\"1/1/2030\", periods=3, freq=\"H\")\n",
    "t_idx_3 = pd.date_range(\"1/1/2040\", periods=3, freq=\"H\")\n",
    "\n",
    "# Transfer them to pd.Series\n",
    "t_idx_1_series = pd.Series(index=t_idx_1, dtype=\"float64\")\n",
    "t_idx_2_series = pd.Series(index=t_idx_2, dtype=\"float64\")\n",
    "t_idx_3_series = pd.Series(index=t_idx_3, dtype=\"float64\")\n",
    "\n",
    "# Combine them and use the index as pd.DatetimeIndex\n",
    "timeindex = pd.concat(\n",
    "    [t_idx_1_series, t_idx_2_series, t_idx_3_series]\n",
    ").index\n",
    "\n",
    "# periods are a list of pd.date_range objects\n",
    "periods = [t_idx_1, t_idx_2, t_idx_3]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "e3596069-f320-4e60-96e0-c0141a1fa4bf",
   "metadata": {},
   "source": [
    "## Define the actual energy system\n",
    "> **Important** to notice:\n",
    "> 1. You explicitly have to define the `periods` attribute.\n",
    "> 2. You can define both, `timeindex` and `timeincrement` for multi-period modelling. But you have to exercise caution that they are consistent with each other.\n",
    "> 3. You have to set `infer_last_interval=False`. The multi-period feature in this regard is not (yet) fully aligned with the default behaviour of oemof.solph.\n",
    "\n",
    "Note that `SuspiciousUsageWarnings` pop up:\n",
    "* This is intended behaviour informing you that what you do is new and somewhat experimental (though succesfully tested).\n",
    "* Also it warns you to pay attention on how to define `timeindex` and `timeincrement` in case you specify both."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "c097e1cb-f22e-4770-95db-746504aa5cce",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\mambaforge-data\\envs\\multi_period_oemof\\lib\\site-packages\\oemof\\solph\\_energy_system.py:139: SuspiciousUsageWarning: Ensure that your timeindex and timeincrement are consistent.\n",
      "If you are not considering non-equidistant timeindices, consider only specifying a timeindex.\n",
      "  warnings.warn(msg, debugging.SuspiciousUsageWarning)\n",
      "C:\\mambaforge-data\\envs\\multi_period_oemof\\lib\\site-packages\\oemof\\solph\\_energy_system.py:170: SuspiciousUsageWarning: CAUTION! You specified the 'periods' attribute for your energy system.\n",
      " This will lead to creating a multi-period optimization modeling which can be used e.g. for long-term investment modeling.\n",
      "Please be aware that the feature is experimental as of now. If you find anything suspicious or any bugs, please report them.\n",
      "  warnings.warn(msg, debugging.SuspiciousUsageWarning)\n"
     ]
    }
   ],
   "source": [
    "es = solph.EnergySystem(\n",
    "    timeindex=timeindex,\n",
    "    timeincrement=[1] * len(timeindex),\n",
    "    periods=periods,\n",
    "    infer_last_interval=False,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "07e3e6a6-531c-4142-89e6-ab67fb45eb31",
   "metadata": {},
   "source": [
    "## Define components\n",
    "Now, let's equip our energy system with some components."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "eb16f652-0751-4203-846b-7949054c20b5",
   "metadata": {},
   "source": [
    "### Buses\n",
    "Defining buses is nothing special, it is exactly what you are used to.<br>\n",
    "For our example, we use the following buses:\n",
    "\n",
    "| bus | explanation |\n",
    "|---|---|\n",
    "| `bus_lignite` | commodity bus for fuel lignite |\n",
    "| `bus_hardcoal` | commodity bus for fuel hard coal |\n",
    "| `bus_natgas` | commodity bus for fuel natural gas |\n",
    "| `bus_el` | electricity bus for Germany |\n",
    "| `bus_FR` | electricity bus for France |"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "7e0158b9-23ad-45a8-8a62-4e2308c176e7",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create buses\n",
    "bus_lignite = solph.buses.Bus(label=\"DE_bus_lignite\", balanced=True)\n",
    "bus_hardcoal = solph.buses.Bus(label=\"DE_bus_hardcoal\", balanced=True)\n",
    "bus_natgas = solph.buses.Bus(label=\"DE_bus_natgas\", balanced=True)\n",
    "bus_el = solph.buses.Bus(label=\"DE_bus_el\", balanced=True)\n",
    "bus_el_FR = solph.buses.Bus(label=\"FR_bus_el\", balanced=True)\n",
    "\n",
    "# Add them to the energy system\n",
    "es.add(\n",
    "    bus_lignite,\n",
    "    bus_hardcoal,\n",
    "    bus_natgas,\n",
    "    bus_el,\n",
    "    bus_el_FR,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a329deac-46e4-4534-90d3-06c06b21194b",
   "metadata": {},
   "source": [
    "### Sources and Sinks\n",
    "Defining sources and sinks again is nothing special, it is exactly what you are used to.<br>\n",
    "For our example, we use the following sources and sinks:\n",
    "\n",
    "| component | explanation | type | region |\n",
    "|---|---|---|---|\n",
    "| `source_lignite` | commodity source for fuel lignite | Source | Germany |\n",
    "| `source_hardcoal` | commodity source for fuel hard coal | Source | Germany |\n",
    "| `source_natgas` | commodity source for fuel natural gas | Source | Germany |\n",
    "| `source_wind` | wind generation source | Source | Germany |\n",
    "| `source_shortage` | artifical shortage source | Source | Germany |\n",
    "| `source_wind_FR` | wind generation source | Source | France |\n",
    "| `source_shortage_FR` | artifical shortage source | Source | France |\n",
    "| `sink_el` | electricity consumption | Sink | Germany |\n",
    "| `sink_excess` | excess electricity sink | Sink | Germany |\n",
    "| `sink_el_FR` | electricity consumption | Sink | France |\n",
    "| `sink_excess_FR` | excess electricity sink | Sink | France | \n",
    "\n",
    "> Tips and hints:\n",
    "> 1. Note that the \"wind\" sources are somewhat generic and don't really show a typical wind output profile.\n",
    "> 2. My tip is to always include shortage sources and excess sinks to ensure model feasibility."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "1a0fc3c4-ab07-42cf-826f-f0bf7051a365",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create sources\n",
    "source_lignite = solph.components.Source(\n",
    "    label=\"DE_source_lignite\",\n",
    "    outputs={bus_lignite: solph.flows.Flow(variable_costs=5)},\n",
    ")\n",
    "source_hardcoal = solph.components.Source(\n",
    "    label=\"DE_source_hardcoal\",\n",
    "    outputs={bus_hardcoal: solph.flows.Flow(variable_costs=10)},\n",
    ")\n",
    "source_natgas = solph.components.Source(\n",
    "    label=\"DE_source_natgas\",\n",
    "    outputs={bus_natgas: solph.flows.Flow(variable_costs=20)},\n",
    ")\n",
    "source_wind = solph.components.Source(\n",
    "    label=\"DE_source_wind\",\n",
    "    outputs={\n",
    "        bus_el: solph.flows.Flow(\n",
    "            variable_costs=0,\n",
    "            fix=[110] + [70] * (len(timeindex) - 1),\n",
    "            nominal_value=1,\n",
    "        )\n",
    "    },\n",
    ")\n",
    "source_shortage = solph.components.Source(\n",
    "    label=\"DE_source_shortage\",\n",
    "    outputs={\n",
    "        bus_el: solph.flows.Flow(variable_costs=1e10, nominal_value=1e10)\n",
    "    },\n",
    ")\n",
    "source_wind_FR = solph.components.Source(\n",
    "    label=\"FR_source_wind\",\n",
    "    outputs={\n",
    "        bus_el_FR: solph.flows.Flow(\n",
    "            variable_costs=0,\n",
    "            fix=[45] * len(timeindex),\n",
    "            nominal_value=1,\n",
    "        )\n",
    "    },\n",
    ")\n",
    "source_shortage_FR = solph.components.Source(\n",
    "    label=\"FR_source_shortage\",\n",
    "    outputs={\n",
    "        bus_el_FR: solph.flows.Flow(variable_costs=1e10, nominal_value=1e10)\n",
    "    },\n",
    ")\n",
    "\n",
    "# Create sinks\n",
    "sink_el = solph.components.Sink(\n",
    "    label=\"DE_sink_el\",\n",
    "    inputs={\n",
    "        bus_el: solph.flows.Flow(fix=[80] * len(timeindex), nominal_value=1)\n",
    "    },\n",
    ")\n",
    "sink_excess = solph.components.Sink(\n",
    "    label=\"DE_sink_excess\",\n",
    "    inputs={\n",
    "        bus_el: solph.flows.Flow(variable_costs=1e10, nominal_value=1e10)\n",
    "    },\n",
    ")\n",
    "sink_el_FR = solph.components.Sink(\n",
    "    label=\"FR_sink_el\",\n",
    "    inputs={\n",
    "        bus_el_FR: solph.flows.Flow(\n",
    "            fix=[50] * len(timeindex), nominal_value=1\n",
    "        )\n",
    "    },\n",
    ")\n",
    "sink_excess_FR = solph.components.Sink(\n",
    "    label=\"FR_sink_excess\",\n",
    "    inputs={\n",
    "        bus_el_FR: solph.flows.Flow(variable_costs=1e3, nominal_value=1e10)\n",
    "    },\n",
    ")\n",
    "\n",
    "# Add sources and sinks to the energy system\n",
    "es.add(\n",
    "    source_lignite,\n",
    "    source_hardcoal,\n",
    "    source_natgas,\n",
    "    source_wind,\n",
    "    source_shortage,\n",
    "    source_wind_FR,\n",
    "    source_shortage_FR,\n",
    "    sink_el,\n",
    "    sink_excess,\n",
    "    sink_el_FR,\n",
    "    sink_excess_FR,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6d9a3de1-33cd-4544-8c7f-3e1cd7d8d8cd",
   "metadata": {},
   "source": [
    "### Generators (Transformers)\n",
    "Now we add some generators to our example.<br>\n",
    "Note that this is the first place, where we have differences compared to a standard model:\n",
    "* the `Investment` option now comes with some additional attributes:\n",
    "  * `age`: initial age of our plant (in years)\n",
    "  * `lifetime`: technical lifetime of our plant (in years)\n",
    "  * `interest_rate`: required interest rate for the investment; applying a weighted average costs of capital (WACC) approach.\n",
    "  * `fixed_costs`: the fixed costs that are applied over the plants lifetime. Values per period can be given.\n",
    "  * `ep_costs`: differs compared to the usage in the standard model: Includes the nominal or real investment expenses. Values per period can be given.\n",
    "  * `maximum`: is now the maximum that can be installed per period.\n",
    "* Besides the investment option, in our example the remainder is the same.\n",
    "\n",
    "The following generators are defined:\n",
    "\n",
    "| component | explanation | fuel | technology | region |\n",
    "|---|---|---|---|---|\n",
    "| `pp_lignite` | lignite power plant | lignite | steam turbine | Germany |\n",
    "| `pp_hardcoal` | hard coal power plant | hard coal | steam turbine | Germany |\n",
    "| `pp_natgas_CCGT` | combined cycle natural gas power plant | natural gas | combined cycle gas turbine | Germany |\n",
    "| `pp_natgas_GT` | natural gas power plant | natural gas | gas turbine | Germany |\n",
    "\n",
    "> Note:\n",
    "> * We could have defined plants that have no `Investment` option, i.e. that are \"dispatch-only\" plants already in the system.\n",
    "> * We could have attributed these with an `age` and a `lifetime`. If we don't provide this, they remain in the system \"forever\".\n",
    "> * You are also allowed to use the `fixed_costs` attribute for these plants."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "ba17863f-b83f-4852-888b-842f7412d168",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create transformers\n",
    "pp_lignite = solph.components.Transformer(\n",
    "    label=\"DE_pp_lignite\",\n",
    "    inputs={bus_lignite: solph.flows.Flow()},\n",
    "    outputs={\n",
    "        bus_el: solph.flows.Flow(\n",
    "            investment=solph.Investment(\n",
    "                maximum=1000,\n",
    "                ep_costs=2e6,\n",
    "                existing=0,\n",
    "                lifetime=20,\n",
    "                age=0,\n",
    "                interest_rate=0.02,\n",
    "            ),\n",
    "            variable_costs=1,\n",
    "        )\n",
    "    },\n",
    "    conversion_factors={bus_el: 0.38},\n",
    ")\n",
    "\n",
    "pp_hardcoal = solph.components.Transformer(\n",
    "    label=\"DE_pp_hardcoal\",\n",
    "    inputs={bus_hardcoal: solph.flows.Flow()},\n",
    "    outputs={\n",
    "        bus_el: solph.flows.Flow(\n",
    "            investment=solph.Investment(\n",
    "                maximum=1000,\n",
    "                ep_costs=1.6e6,\n",
    "                existing=0,\n",
    "                lifetime=20,\n",
    "                age=0,\n",
    "                interest_rate=0.02,\n",
    "            ),\n",
    "            variable_costs=2,\n",
    "        )\n",
    "    },\n",
    "    conversion_factors={bus_el: 0.45},\n",
    ")\n",
    "\n",
    "pp_natgas_CCGT = solph.components.Transformer(\n",
    "    label=\"DE_pp_natgas_CCGT\",\n",
    "    inputs={bus_natgas: solph.flows.Flow()},\n",
    "    outputs={\n",
    "        bus_el: solph.flows.Flow(\n",
    "            investment=solph.Investment(\n",
    "                maximum=1000,\n",
    "                ep_costs=1e6,\n",
    "                existing=0,\n",
    "                lifetime=20,\n",
    "                age=0,\n",
    "                interest_rate=0.02,\n",
    "            ),\n",
    "            variable_costs=3,\n",
    "        )\n",
    "    },\n",
    "    conversion_factors={bus_el: 0.6},\n",
    ")\n",
    "\n",
    "pp_natgas_GT = solph.components.Transformer(\n",
    "    label=\"DE_pp_natgas_GT\",\n",
    "    inputs={bus_natgas: solph.flows.Flow()},\n",
    "    outputs={\n",
    "        bus_el: solph.flows.Flow(\n",
    "            investment=solph.Investment(\n",
    "                maximum=1000,\n",
    "                ep_costs=[0.6e6, 0.5e6, 0.4e6],\n",
    "                existing=0,\n",
    "                lifetime=20,\n",
    "                age=0,\n",
    "                interest_rate=0.02,\n",
    "                fixed_costs=1000,\n",
    "            ),\n",
    "            variable_costs=4,\n",
    "        )\n",
    "    },\n",
    "    conversion_factors={bus_el: 0.4},\n",
    ")\n",
    "\n",
    "# Add them to the energy system\n",
    "es.add(\n",
    "    pp_lignite,\n",
    "    pp_hardcoal,\n",
    "    pp_natgas_CCGT,\n",
    "    pp_natgas_GT,\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3a44484b-5e8b-4e40-9e66-50f1f8c6f289",
   "metadata": {},
   "source": [
    "### Storage\n",
    "To spice it up a little, we also add a storage unit.<br>\n",
    "We add a single rather generic storage that is available for the market area Germany."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "8416af27-97b6-4b73-8e85-60599419a121",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a strorage unit\n",
    "storage_el = solph.components.GenericStorage(\n",
    "    label=\"DE_storage_el\",\n",
    "    inputs={\n",
    "        bus_el: solph.flows.Flow(\n",
    "            variable_costs=0,\n",
    "            max=1,\n",
    "            investment=solph.Investment(\n",
    "                maximum=20,\n",
    "                ep_costs=1000,\n",
    "                existing=2,\n",
    "                lifetime=10,\n",
    "                age=1,\n",
    "                interest_rate=0.02,\n",
    "            ),\n",
    "        )\n",
    "    },\n",
    "    outputs={\n",
    "        bus_el: solph.flows.Flow(\n",
    "            variable_costs=0,\n",
    "            max=1,\n",
    "            investment=solph.Investment(\n",
    "                maximum=20,\n",
    "                ep_costs=1000,\n",
    "                existing=2,\n",
    "                lifetime=10,\n",
    "                age=1,\n",
    "                interest_rate=0.02,\n",
    "            ),\n",
    "        )\n",
    "    },\n",
    "    loss_rate=0,\n",
    "    initial_storage_level=0,\n",
    "    max_storage_level=1,\n",
    "    min_storage_level=0,\n",
    "    inflow_conversion_factor=0.9,\n",
    "    outflow_conversion_factor=0.9,\n",
    "    balanced=True,\n",
    "    invest_relation_input_output=1,\n",
    "    invest_relation_input_capacity=1/5,\n",
    "    invest_relation_output_capacity=None,\n",
    "    fixed_costs=10,\n",
    "    investment=solph.Investment(\n",
    "        maximum=20,\n",
    "        ep_costs=1000,\n",
    "        existing=2,\n",
    "        lifetime=10,\n",
    "        age=1,\n",
    "        interest_rate=0.02,\n",
    "        fixed_costs=10,\n",
    "    ),\n",
    ")\n",
    "\n",
    "# Add it to the energy system\n",
    "es.add(storage_el)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "a22d8da2-05a6-4287-9a53-8fc855b4ddfa",
   "metadata": {},
   "source": [
    "### Link\n",
    "Now we need to connect our two market areas Germany and France.<br>\n",
    "In this example, e use the experimental `Link` component for that that can operate in both ways.\n",
    "\n",
    "> Note:\n",
    "> * We could have used two transformers, one for each direction ending up in the same result.\n",
    "> * We introduce conversion factors slightly below 1. The reason is that then, the model is not agnostic where to put the energy. Also, we would see some transmission losses in reality, right?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a24c812c-88a5-4ce6-bea8-0902541721c5",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Create a link\n",
    "link_DE_FR = solph.components.experimental.Link(\n",
    "    label=\"link_DE_FR\",\n",
    "    inputs={\n",
    "        bus_el: solph.flows.Flow(\n",
    "            nominal_value=10,\n",
    "        ),\n",
    "        bus_el_FR: solph.flows.Flow(\n",
    "            nominal_value=10,\n",
    "        ),\n",
    "    },\n",
    "    outputs={bus_el_FR: solph.flows.Flow(), bus_el: solph.flows.Flow()},\n",
    "    conversion_factors={\n",
    "        (bus_el, bus_el_FR): 0.999999,\n",
    "        (bus_el_FR, bus_el): 0.999999,\n",
    "    },\n",
    ")\n",
    "\n",
    "# Add it to the energy system\n",
    "es.add(link_DE_FR)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9c4996a7-b896-4e29-a405-e21d0041f9ec",
   "metadata": {},
   "source": [
    "# Set up and solve the model\n",
    "You need to specify a `discount_rate` for your model:\n",
    "* If you provide nothing, a default of `0.02` will be used.\n",
    "* If you want to use costs in real terms throughout, discounting is not necessary. You can achieve that by setting `disount_rate=0`\n",
    "\n",
    "Solve the model with your favourite solver, defined at the very beginning."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "acbeceb6-8dcc-46cf-bb2e-170cc497cf0b",
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\mambaforge-data\\envs\\multi_period_oemof\\lib\\site-packages\\oemof\\solph\\components\\_generic_storage.py:1026: SuspiciousUsageWarning: For a multi-period model, initial_storage_level is not supported.\n",
      "It is suggested to remove that parameter since it has no effect.\n",
      "storage_content will be zero, until there is some usable storage  capacity installed.\n",
      "  warn(warning, debugging.SuspiciousUsageWarning)\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Welcome to the CBC MILP Solver \n",
      "Version: 2.10.10 \n",
      "Build Date: Apr 18 2023 \n",
      "\n",
      "command line - C:\\Users\\koch_j0\\Cbc-releases.2.10.10-i686-w64-mingw32-dbg\\bin\\cbc.exe -printingOptions all -import C:\\Users\\koch_j0\\AppData\\Local\\Temp\\tmpo14k13jo.pyomo.lp -stat=1 -solve -solu C:\\Users\\koch_j0\\AppData\\Local\\Temp\\tmpo14k13jo.pyomo.soln (default strategy 1)\n",
      "Option for printingOptions changed from normal to all\n",
      "Presolve 89 (-172) rows, 132 (-172) columns and 308 (-345) elements\n",
      "Statistics for presolved model\n",
      "\n",
      "\n",
      "Problem has 89 rows, 132 columns (87 with objective) and 308 elements\n",
      "There are 36 singletons with objective \n",
      "Column breakdown:\n",
      "63 of type 0.0->inf, 68 of type 0.0->up, 0 of type lo->inf, \n",
      "1 of type lo->up, 0 of type free, 0 of type fixed, \n",
      "0 of type -inf->0.0, 0 of type -inf->up, 0 of type 0.0->1.0 \n",
      "Row breakdown:\n",
      "8 of type E 0.0, 0 of type E 1.0, 0 of type E -1.0, \n",
      "18 of type E other, 0 of type G 0.0, 0 of type G 1.0, \n",
      "0 of type G other, 63 of type L 0.0, 0 of type L 1.0, \n",
      "0 of type L other, 0 of type Range 0.0->1.0, 0 of type Range other, \n",
      "0 of type Free \n",
      "Presolve 89 (-172) rows, 132 (-172) columns and 308 (-345) elements\n",
      "0  Obj 9805.6108 Primal inf 212.50311 (18)\n",
      "51  Obj 37221.606 Primal inf 266.31118 (17)\n",
      "85  Obj 1.5601259e+11\n",
      "Optimal - objective value 1.5601259e+11\n",
      "After Postsolve, objective 1.5601259e+11, infeasibilities - dual 1.0512936e-06 (1), primal 0 (0)\n",
      "Presolved model was optimal, full model needs cleaning up\n",
      "0  Obj 1.5601259e+11\n",
      "Optimal - objective value 1.5601259e+11\n",
      "Optimal objective 1.560125869e+11 - 85 iterations time 0.002, Presolve 0.00\n",
      "Total time (CPU seconds):       0.02   (Wallclock seconds):       0.02\n",
      "\n"
     ]
    }
   ],
   "source": [
    "# Build the mathematical optimization model\n",
    "om = solph.Model(es, discount_rate=0.02)\n",
    "# Solve the model and show solver log (note: this may differ dependent on the solver you use)\n",
    "_ = om.solve(solver=solver, solve_kwargs={\"tee\": True})"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7a45433b-9ab0-4e6f-9ba0-92cc36db313d",
   "metadata": {},
   "source": [
    "# Obtain model results\n",
    "We want to look at the dispatch results for the German electricity bus and the investments.<br>\n",
    "* Note that we have to extract the storage capacity investments separately.\n",
    "* Also note that we apply some post-processing in order to get nicer shaped results that we can visualize afterwards."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "a53e4f42-2363-4b9f-a197-9aab39de9330",
   "metadata": {},
   "outputs": [],
   "source": [
    "model_results = solph.processing.results(om)\n",
    "model_results = solph.processing.convert_keys_to_strings(model_results)\n",
    "\n",
    "# investment results for Germany\n",
    "investment_results = solph.views.node(model_results, \"DE_bus_el\")[\"period_scalars\"]\n",
    "buses_el_views = [\"DE_bus_el\", \"FR_bus_el\"]\n",
    "\n",
    "# dispatch results for Germany\n",
    "dispatch_results = solph.views.node(model_results, \"DE_bus_el\")[\"sequences\"]\n",
    "\n",
    "# Extract storage capacity investments\n",
    "storage_investment_results = solph.views.node(model_results, \"DE_storage_el\")[\"period_scalars\"]\n",
    "capacity_idx = [idx for idx in storage_investment_results.index if idx[0][1] == \"None\"]\n",
    "storage_investment_results = storage_investment_results.loc[capacity_idx]\n",
    "\n",
    "# Do some postprocessing for plotting in the following\n",
    "investment_results = prepare_results(investment_results)\n",
    "storage_investment_results = prepare_results(storage_investment_results)\n",
    "dispatch_results = prepare_results(dispatch_results.T).reset_index(level=1, drop=True).T"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "85533738-53c2-4d36-a146-1a584fdb5be0",
   "metadata": {},
   "source": [
    "# Show the model results\n",
    "\n",
    "## Investment results\n",
    "Draw the following plots\n",
    "* new investments made per period\n",
    "* decommissionings made per period\n",
    "* total installed capacity per period"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "1ff15d5e-a43c-4362-8021-6c45adb63457",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1200x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1200x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Show the newly invested capacity\n",
    "plot_single_investment_variable_multiple_dfs(\n",
    "    [investment_results, storage_investment_results],\n",
    "    \"invest\",\n",
    "    ylim=[0, 30]\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "c094e66b-90ba-4539-9144-830f0b627eca",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1200x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Show the decommissioned capacity\n",
    "plot_single_investment_variable_multiple_dfs(\n",
    "    [investment_results, storage_investment_results],\n",
    "    \"old\",\n",
    "    ylim=[0, 30]\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "4e11c1b8-4fc0-4dbd-995f-e6c76c9c851b",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1200x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<Figure size 1200x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Show the total installed capacity\n",
    "plot_single_investment_variable_multiple_dfs(\n",
    "    [investment_results, storage_investment_results],\n",
    "    \"total\",\n",
    "    ylim=[0, 30]\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "d6cdde4f-ab86-4702-9c9e-182c6cd2e0d4",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>variable_name</th>\n",
       "      <th>invest</th>\n",
       "      <th>old</th>\n",
       "      <th>old_end</th>\n",
       "      <th>old_exo</th>\n",
       "      <th>total</th>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>label</th>\n",
       "      <th>year</th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "      <th></th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">DE_bus_el,DE_storage_el</th>\n",
       "      <th>2020</th>\n",
       "      <td>2.400000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2030</th>\n",
       "      <td>2.666667</td>\n",
       "      <td>4.400000</td>\n",
       "      <td>2.400000</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2040</th>\n",
       "      <td>4.000000</td>\n",
       "      <td>2.666667</td>\n",
       "      <td>2.666667</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">DE_pp_hardcoal,DE_bus_el</th>\n",
       "      <th>2020</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2030</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2040</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">DE_pp_lignite,DE_bus_el</th>\n",
       "      <th>2020</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2030</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2040</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">DE_pp_natgas_CCGT,DE_bus_el</th>\n",
       "      <th>2020</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2030</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2040</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">DE_pp_natgas_GT,DE_bus_el</th>\n",
       "      <th>2020</th>\n",
       "      <td>10.600005</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>10.600005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2030</th>\n",
       "      <td>4.811523</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>15.411528</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2040</th>\n",
       "      <td>6.188482</td>\n",
       "      <td>10.600005</td>\n",
       "      <td>10.600005</td>\n",
       "      <td>0.0</td>\n",
       "      <td>11.000005</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">DE_storage_el,DE_bus_el</th>\n",
       "      <th>2020</th>\n",
       "      <td>2.400000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.400000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2030</th>\n",
       "      <td>2.666667</td>\n",
       "      <td>4.400000</td>\n",
       "      <td>2.400000</td>\n",
       "      <td>2.0</td>\n",
       "      <td>2.666667</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2040</th>\n",
       "      <td>4.000000</td>\n",
       "      <td>2.666667</td>\n",
       "      <td>2.666667</td>\n",
       "      <td>0.0</td>\n",
       "      <td>4.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th rowspan=\"3\" valign=\"top\">DE_storage_el,None</th>\n",
       "      <th>2020</th>\n",
       "      <td>20.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.0</td>\n",
       "      <td>22.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2030</th>\n",
       "      <td>13.333333</td>\n",
       "      <td>22.000000</td>\n",
       "      <td>20.000000</td>\n",
       "      <td>2.0</td>\n",
       "      <td>13.333333</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2040</th>\n",
       "      <td>20.000000</td>\n",
       "      <td>13.333333</td>\n",
       "      <td>13.333333</td>\n",
       "      <td>0.0</td>\n",
       "      <td>20.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "variable_name                        invest        old    old_end  old_exo   \n",
       "label                       year                                             \n",
       "DE_bus_el,DE_storage_el     2020   2.400000   0.000000   0.000000      0.0  \\\n",
       "                            2030   2.666667   4.400000   2.400000      2.0   \n",
       "                            2040   4.000000   2.666667   2.666667      0.0   \n",
       "DE_pp_hardcoal,DE_bus_el    2020   0.000000   0.000000   0.000000      0.0   \n",
       "                            2030   0.000000   0.000000   0.000000      0.0   \n",
       "                            2040   0.000000   0.000000   0.000000      0.0   \n",
       "DE_pp_lignite,DE_bus_el     2020   0.000000   0.000000   0.000000      0.0   \n",
       "                            2030   0.000000   0.000000   0.000000      0.0   \n",
       "                            2040   0.000000   0.000000   0.000000      0.0   \n",
       "DE_pp_natgas_CCGT,DE_bus_el 2020   0.000000   0.000000   0.000000      0.0   \n",
       "                            2030   0.000000   0.000000   0.000000      0.0   \n",
       "                            2040   0.000000   0.000000   0.000000      0.0   \n",
       "DE_pp_natgas_GT,DE_bus_el   2020  10.600005   0.000000   0.000000      0.0   \n",
       "                            2030   4.811523   0.000000   0.000000      0.0   \n",
       "                            2040   6.188482  10.600005  10.600005      0.0   \n",
       "DE_storage_el,DE_bus_el     2020   2.400000   0.000000   0.000000      0.0   \n",
       "                            2030   2.666667   4.400000   2.400000      2.0   \n",
       "                            2040   4.000000   2.666667   2.666667      0.0   \n",
       "DE_storage_el,None          2020  20.000000   0.000000   0.000000      0.0   \n",
       "                            2030  13.333333  22.000000  20.000000      2.0   \n",
       "                            2040  20.000000  13.333333  13.333333      0.0   \n",
       "\n",
       "variable_name                         total  \n",
       "label                       year             \n",
       "DE_bus_el,DE_storage_el     2020   4.400000  \n",
       "                            2030   2.666667  \n",
       "                            2040   4.000000  \n",
       "DE_pp_hardcoal,DE_bus_el    2020   0.000000  \n",
       "                            2030   0.000000  \n",
       "                            2040   0.000000  \n",
       "DE_pp_lignite,DE_bus_el     2020   0.000000  \n",
       "                            2030   0.000000  \n",
       "                            2040   0.000000  \n",
       "DE_pp_natgas_CCGT,DE_bus_el 2020   0.000000  \n",
       "                            2030   0.000000  \n",
       "                            2040   0.000000  \n",
       "DE_pp_natgas_GT,DE_bus_el   2020  10.600005  \n",
       "                            2030  15.411528  \n",
       "                            2040  11.000005  \n",
       "DE_storage_el,DE_bus_el     2020   4.400000  \n",
       "                            2030   2.666667  \n",
       "                            2040   4.000000  \n",
       "DE_storage_el,None          2020  22.000000  \n",
       "                            2030  13.333333  \n",
       "                            2040  20.000000  "
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Show the data frames containing all the infos we visualized above.\n",
    "display(pd.concat([investment_results, storage_investment_results]))"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "da2cd314-0594-4b96-aea7-a6b6b69d698c",
   "metadata": {},
   "source": [
    "## Dispatch results\n",
    "Filter and show some dispatch results.<br>\n",
    "The following plots are created:\n",
    "* "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "206968b4-bca8-436a-ac6f-5331962883bf",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Filter the respective results\n",
    "filter_values = {\n",
    "    \"demand\": [\n",
    "        col for col in dispatch_results.columns if \"sink\" in col\n",
    "    ],\n",
    "    \"generation\": [\n",
    "        col for col in dispatch_results.columns \n",
    "        if \"source\" in col or \"pp\" in col\n",
    "    ],\n",
    "    \"storage_inflow\": [\"DE_bus_el,DE_storage_el\"],\n",
    "    \"storage_outflow\": [\"DE_storage_el,DE_bus_el\"],\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "4ff2275d-7247-424d-b601-9a510eefb1d4",
   "metadata": {},
   "outputs": [
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Demand\n",
    "fig, ax = plt.subplots(figsize=(10,5))\n",
    "dispatch_results[filter_values[\"demand\"]].plot(kind=\"bar\", stacked=True, ax=ax)\n",
    "plt.ylabel(\"Comsumption in MWh/h\")\n",
    "plt.xlabel(\"Time step\")\n",
    "plt.legend(loc=\"lower right\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "b877f276-a14e-4705-8aa9-c9316e6a0f5d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Generation\n",
    "fig, ax = plt.subplots(figsize=(10,5))\n",
    "dispatch_results[filter_values[\"generation\"]].plot(kind=\"bar\", stacked=True, ax=ax)\n",
    "plt.ylabel(\"Generation in MWh/h\")\n",
    "plt.xlabel(\"Time step\")\n",
    "plt.legend(loc=\"lower right\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "9b5c0429-a008-46bd-8b5d-4b7ab518be87",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x500 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Storages\n",
    "fig, ax = plt.subplots(figsize=(10,5))\n",
    "dispatch_results[filter_values[\"storage_outflow\"]].plot(kind=\"bar\", ax=ax)\n",
    "dispatch_results[filter_values[\"storage_inflow\"]].mul(-1).plot(kind=\"bar\", ax=ax)\n",
    "plt.axhline(y=0, color='k', linestyle='-')\n",
    "plt.ylabel(\"Storage operation in MWh/h (pos: out, neg: in)\")\n",
    "plt.xlabel(\"Time step\")\n",
    "plt.legend(loc=\"lower right\")\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "7e45959c-6096-4903-a0fc-170328dd493c",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "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": "3.9.16"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}