tutorial/Austrian_energy_system/R_austria.ipynb

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    "# Austrian energy system Tutorial Part 1: Building an Energy Model (in R)\n",
    "\n",
    "For information on how to install *MESSAGEix*, please refer to the [Installation page](https://docs.messageix.org/en/stable/#getting-started), and for getting the *MESSAGEix* tutorials, please follow the steps mentioned in [Tutorials](https://docs.messageix.org/en/stable/tutorials.html).\n",
    "\n",
    "Please refer to the [user guidelines](https://docs.messageix.org/en/stable/notice.html) for additional information on using *MESSAGEix*, including the recommended citation and how to name new models.\n",
    "\n",
    "**Pre-requisites**\n",
    "- You have the *MESSAGEix* framework installed and working\n",
    "\n",
    "**Structure of these tutorials.** After having run this baseline tutorial, you are able to start with any of the other tutorials, but we recommend to follow the order below for going through the information step-wise:\n",
    "\n",
    "1. Prepare the base model version (Python: ``austria.ipynb``, R: ``R_austria.ipynb``)\n",
    "2. Plot the results of the baseline runs (Python: ``austria_load_scenario.ipynb``, R: ``R_austria_load_scenario.ipynb``)\n",
    "\n",
    "Currently only available in Python:\n",
    "3. Run a single policy scenario (``austria_single_policy.ipynb``)\n",
    "4. Run multiple policy scenarios. This tutorial has two notebooks: an introduction with some exercises and completed code for the exercises (exercises: ``austria_multiple_policies.ipynb``, answers: ``austria_multiple_policies-answers.ipynb``)\n",
    "\n",
    "**Introduction**\n",
    "\n",
    "In this notebook, we will build a model of the Austrian energy system from scratch. The process will involve defining our model's time horizon and spatial extent, and then populating the model with data associated with model parameters. Once we have a baseline model, we will then move on to investigating policy scenarios.\n",
    "\n",
    "We will be populating different kinds of parameters including:\n",
    "\n",
    "### Economic Parameters\n",
    "\n",
    "- `interestrate`\n",
    "- `demand`\n",
    "\n",
    "### Technology Parameters\n",
    "\n",
    "#### Engineering Parameters\n",
    "\n",
    "- `input`\n",
    "- `output`\n",
    "- `technical_lifetime`\n",
    "- `capacity_factor`\n",
    "\n",
    "\n",
    "#### Technoeconomic Parameters\n",
    "\n",
    "- `inv_cost`\n",
    "- `fix_cost`\n",
    "- `var_cost`\n",
    "\n",
    "### Dynamic Behavior Parameters\n",
    "\n",
    "- `bound_activity_up`\n",
    "- `bound_activity_lo`\n",
    "- `bound_new_capacity_up`\n",
    "- `initial_activity_up`\n",
    "- `growth_activity_up`\n",
    "\n",
    "### Emissions\n",
    "\n",
    "- `emission_factor`\n",
    "\n",
    "A full list of parameters can be found on the (internal) [MESSAGEix documentation website](http://ienecat.iiasa.ac.at:8787/message_ix_doc). This website can be built in the future from the repository that you are using. \n",
    "\n",
    "## The Final Product\n",
    "\n",
    "At the completion of this exercise, we will have developed an energy model that is comprised of the below Reference Energy System (RES):\n",
    "\n",
    "![title](austria.png)\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Setup\n",
    "\n",
    "We begin by loading the ``rmessageix`` package.\n",
    "We also load the common R package ``dplyr``, which will be used for some data manipulation."
   ]
  },
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   "source": [
    "# Load dplyr, used for data manipulation in R\n",
    "library(dplyr)\n",
    "\n",
    "# Load reticulate, used to access the Python API from R\n",
    "library(reticulate)\n",
    "\n",
    "# Import ixmp and message_ix, just as in Python\n",
    "ixmp <- import(\"ixmp\")\n",
    "message_ix <- import(\"message_ix\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "These two objects named ``ixmp`` and ``message_ix`` can now be used to access all the features of the API (application programming interface) provided by the Python packages."
   ]
  },
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   "source": [
    "# launch the IX modeling platform using the local default database\n",
    "mp <- ixmp$Platform()"
   ]
  },
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   "source": [
    "model <- \"Austrian energy model\"\n",
    "scen <- \"baseline\"\n",
    "annot <- \"developing a stylized energy system model for illustration and testing\" \n",
    "\n",
    "scenario <- message_ix$Scenario(mp, model, scen, version='new', annotation=annot)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Time and Spatial Detail\n",
    "\n",
    "The model includes the time periods 2010, 2020, 2030 and 2040."
   ]
  },
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   "source": [
    "horizon = as.integer(seq(2010, 2040, 10))\n",
    "firstyear = as.integer(horizon[1])"
   ]
  },
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   "cell_type": "code",
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   "source": [
    "scenario$add_set(\"year\", horizon)\n",
    "scenario$add_set(\"cat_year\", c(\"firstmodelyear\", firstyear) )"
   ]
  },
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   "source": [
    "country = \"Austria\"\n",
    "scenario$add_set(\"node\", country)\n",
    "scenario$add_set(\"lvl_spatial\", \"country\")\n",
    "scenario$add_set(\"map_spatial_hierarchy\", c(\"country\", country, \"World\"))\n",
    "scenario$add_set(\"mode\", \"standard\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "source": [
    "scenario$add_set(\"commodity\", c(\"electricity\", \"light\", \"other_electricity\") )\n",
    "scenario$add_set(\"level\", c(\"secondary\", \"final\", \"useful\") )"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Economic Parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
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   "source": [
    "scenario$add_par(\"interestrate\", horizon, value=0.05, unit='-')"
   ]
  },
  {
   "cell_type": "code",
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   "source": [
    "beta = 0.7 \n",
    "gdp = c(1., 1.21631, 1.4108, 1.63746)\n",
    "demand = gdp ** beta"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Technologies"
   ]
  },
  {
   "cell_type": "code",
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   "source": [
    "plants = c(    \"coal_ppl\", \n",
    "    \"gas_ppl\", \n",
    "    \"oil_ppl\", \n",
    "    \"bio_ppl\", \n",
    "    \"hydro_ppl\",\n",
    "    \"wind_ppl\", \n",
    "    \"solar_pv_ppl\" # actually primary -> final\n",
    ")\n",
    "secondary_energy_techs = c(plants,'import')\n",
    "\n",
    "final_energy_techs = c('electricity_grid')\n",
    "\n",
    "lights = c(\n",
    "    \"bulb\", \n",
    "    \"cfl\" \n",
    ")\n",
    "useful_energy_techs = c(lights ,'appliances')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
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   "source": [
    "technologies = c(secondary_energy_techs, final_energy_techs,  useful_energy_techs)\n",
    "scenario$add_set(\"technology\", technologies)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
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   "source": [
    "demand_per_year = 55209. / 8760 # from IEA statistics\n",
    "elec_demand = data.frame(\n",
    "    node = rep(country,4),\n",
    "    commodity = rep('other_electricity',4),\n",
    "    level = rep('useful',4),\n",
    "    year = horizon,\n",
    "    time = rep('year',4),\n",
    "    value = demand_per_year * demand,\n",
    "    unit = rep('GWa',4),\n",
    "    row.names = horizon\n",
    ")\n",
    "scenario$add_par(\"demand\", elec_demand)\n",
    "\n",
    "demand_per_year = 6134. / 8760 # from IEA statistics\n",
    "light_demand = data.frame(\n",
    "    node = country,\n",
    "    commodity = 'light',\n",
    "    level = 'useful',\n",
    "    year = horizon,\n",
    "    time = 'year',\n",
    "    value = demand_per_year * demand,\n",
    "    unit = 'GWa'\n",
    ")\n",
    "scenario$add_par(\"demand\", light_demand)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "### Engineering Parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
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   "source": [
    "year_pairs = as.matrix(expand.grid(horizon,horizon) %>%\n",
    "                         rowwise() %>%\n",
    "                         filter(Var2 >= Var1) %>%\n",
    "                         arrange(Var1))\n",
    "vintage_years <- year_pairs[,1]\n",
    "act_years <- year_pairs[,1]"
   ]
  },
  {
   "cell_type": "code",
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   "source": [
    "base_input = data.frame(\n",
    "    node_loc = country,\n",
    "    year_vtg = vintage_years,\n",
    "    year_act = act_years,\n",
    "    mode = 'standard',\n",
    "    node_origin = country,\n",
    "    commodity = 'electricity',\n",
    "    time = 'year',\n",
    "    time_origin = 'year'\n",
    ")\n",
    "\n",
    "grid = data.frame(base_input,data.frame(\n",
    "        technology = 'electricity_grid',\n",
    "        level = 'secondary',\n",
    "        value = 1.0,\n",
    "        unit = '%'\n",
    "        ))\n",
    "scenario$add_par(\"input\", grid)\n",
    "\n",
    "bulb = data.frame(base_input,data.frame(\n",
    "        technology = 'bulb',\n",
    "        level = 'final',\n",
    "        value = 1.0,\n",
    "        unit = '%'\n",
    "        ))\n",
    "scenario$add_par(\"input\", bulb)\n",
    "\n",
    "cfl = data.frame(base_input,data.frame(\n",
    "        technology = 'cfl',\n",
    "        level = 'final',\n",
    "        value = 0.3, \n",
    "        unit = '%'\n",
    "        ))\n",
    "scenario$add_par(\"input\", cfl)\n",
    "\n",
    "app = data.frame(base_input,data.frame(\n",
    "        technology = 'appliances',\n",
    "        level = 'final',\n",
    "        value = 1.0,\n",
    "        unit = '%'\n",
    "        ))\n",
    "scenario$add_par(\"input\", app)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
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   "source": [
    "base_output = data.frame(\n",
    "    node_loc = country,\n",
    "    year_vtg = vintage_years,\n",
    "    year_act = act_years,\n",
    "    mode = 'standard',\n",
    "    node_dest = country,\n",
    "    time = 'year',\n",
    "    time_dest = 'year', \n",
    "    unit = '%'\n",
    ")\n",
    "\n",
    "imports = data.frame(base_output,data.frame( technology='import', commodity='electricity', \n",
    "                  level='secondary', value=1.))\n",
    "scenario$add_par('output', imports)\n",
    "\n",
    "grid = data.frame(base_output,data.frame( technology='electricity_grid', commodity='electricity', \n",
    "               level='final', value=0.873))\n",
    "scenario$add_par('output', grid)\n",
    "\n",
    "bulb = data.frame(base_output,data.frame( technology='bulb', commodity='light', \n",
    "               level='useful', value=1.))\n",
    "scenario$add_par('output', bulb)\n",
    "\n",
    "cfl = data.frame(base_output,data.frame( technology='cfl', commodity='light', \n",
    "              level='useful', value=1.))\n",
    "scenario$add_par('output', cfl)\n",
    "\n",
    "app = data.frame(base_output,data.frame( technology='appliances', commodity='other_electricity', \n",
    "              level='useful', value=1.))\n",
    "scenario$add_par('output', app)\n",
    "\n",
    "coal = data.frame(base_output,data.frame( technology='coal_ppl', commodity='electricity', \n",
    "               level='secondary', value=1.))\n",
    "scenario$add_par('output', coal)\n",
    "\n",
    "gas = data.frame(base_output,data.frame( technology='gas_ppl', commodity='electricity', \n",
    "              level='secondary', value=1.))\n",
    "scenario$add_par('output', gas)\n",
    "\n",
    "oil = data.frame(base_output,data.frame( technology='oil_ppl', commodity='electricity', \n",
    "              level='secondary', value=1.))\n",
    "scenario$add_par('output', oil)\n",
    "\n",
    "bio = data.frame(base_output,data.frame( technology='bio_ppl', commodity='electricity', \n",
    "              level='secondary', value=1.))\n",
    "scenario$add_par('output', bio)\n",
    "\n",
    "hydro = data.frame(base_output,data.frame( technology='hydro_ppl', commodity='electricity', \n",
    "                level='secondary', value=1.))\n",
    "scenario$add_par('output', hydro)\n",
    "\n",
    "wind = data.frame(base_output,data.frame( technology='wind_ppl', commodity='electricity', \n",
    "               level='secondary', value=1.))\n",
    "scenario$add_par('output', wind)\n",
    "\n",
    "solar_pv = data.frame(base_output,data.frame( technology='solar_pv_ppl', commodity='electricity', \n",
    "                   level='final', value=1.))\n",
    "scenario$add_par('output', solar_pv)"
   ]
  },
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   "execution_count": null,
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   "source": [
    "# NB this and the following cell can be modified to a syntax like the above\n",
    "\n",
    "base_technical_lifetime = data.frame(\n",
    "    node_loc = country,\n",
    "    year_vtg = horizon,\n",
    "    unit = 'y'\n",
    ")\n",
    "\n",
    "lifetimes = list(\n",
    "    coal_ppl = 40,\n",
    "    gas_ppl =  30,\n",
    "    oil_ppl = 30,\n",
    "    bio_ppl =  30,\n",
    "    hydro_ppl = 60,\n",
    "    wind_ppl = 20,\n",
    "    solar_pv_ppl = 20,\n",
    "    bulb = 1,\n",
    "    cfl = 10\n",
    ")\n",
    "base_technical_lifetime\n",
    "\n",
    "for (i in seq_along(lifetimes)){\n",
    "    df = data.frame(base_technical_lifetime, technology=names(lifetimes[i]), value=lifetimes[[i]])\n",
    "    scenario$add_par('technical_lifetime', df)\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [],
   "source": [
    "base_capacity_factor = data.frame(\n",
    "    node_loc = country,\n",
    "    year_vtg = vintage_years,\n",
    "    year_act = act_years,\n",
    "    time = 'year',\n",
    "    unit = '%'\n",
    ")\n",
    "\n",
    "capacity_factor = list(\n",
    "    coal_ppl = 0.85,\n",
    "    gas_ppl =  0.75,\n",
    "    oil_ppl = 0.75,\n",
    "    bio_ppl = 0.75,\n",
    "    hydro_ppl = 0.5,\n",
    "    wind_ppl = 0.2,\n",
    "    solar_pv_ppl = 0.15,\n",
    "    bulb = 0.1, \n",
    "    cfl =  0.1\n",
    ")\n",
    "    \n",
    "for (i in seq_along(capacity_factor)){\n",
    "    df = data.frame(base_capacity_factor, technology=names(capacity_factor[i]), value=capacity_factor[[i]])\n",
    "    scenario$add_par('capacity_factor', df)\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Technoeconomic Parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [],
   "source": [
    "base_inv_cost = data.frame(\n",
    "    node_loc = country,\n",
    "    year_vtg = horizon,\n",
    "    unit = 'USD/GWa'\n",
    ")\n",
    "\n",
    "# in $ / kW\n",
    "costs = list(\n",
    "    coal_ppl = 1500,\n",
    "    gas_ppl =   870,\n",
    "    oil_ppl =  950,\n",
    "    hydro_ppl = 3000,\n",
    "    bio_ppl =  1600,\n",
    "    wind_ppl = 1100,\n",
    "    solar_pv_ppl = 4000,\n",
    "    bulb = 5,\n",
    "    cfl =  900\n",
    ")\n",
    "\n",
    "for (i in seq_along(costs)){\n",
    "    df = data.frame(base_inv_cost, technology=names(costs[i]), value=costs[[i]] * 1e6)\n",
    "    scenario$add_par('inv_cost', df)\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [],
   "source": [
    "base_fix_cost = data.frame(\n",
    "    node_loc = country,\n",
    "    year_vtg = vintage_years,\n",
    "    year_act = act_years,\n",
    "    unit = 'USD/GWa'\n",
    ")\n",
    "\n",
    "# in $ / kW\n",
    "costs = list(\n",
    "    coal_ppl = 40,\n",
    "    gas_ppl =   25,\n",
    "    oil_ppl =  25,\n",
    "    hydro_ppl = 60,\n",
    "    bio_ppl =  30,\n",
    "    wind_ppl = 40,\n",
    "    solar_pv_ppl = 25\n",
    ")\n",
    "\n",
    "for (i in seq_along(costs)){\n",
    "    df = data.frame(base_fix_cost, technology=names(costs[i]), value=costs[[i]] * 1e6)\n",
    "    scenario$add_par('fix_cost', df)\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [],
   "source": [
    "base_var_cost = data.frame(\n",
    "    node_loc = country,\n",
    "    year_vtg = vintage_years,\n",
    "    year_act = act_years,\n",
    "    mode = 'standard',\n",
    "    time = 'year',\n",
    "    unit = 'USD/GWa'\n",
    ")\n",
    "\n",
    "# in $ / MWh\n",
    "costs = list(\n",
    "    coal_ppl = 24.4,\n",
    "    gas_ppl =   42.4,\n",
    "    oil_ppl =   77.8,\n",
    "    bio_ppl =  48.2,\n",
    "    electricity_grid = 47.8\n",
    ")\n",
    "    \n",
    "for (i in seq_along(costs)){\n",
    "    df = data.frame(base_var_cost, technology=names(costs[i]), value=costs[[i]] * 8760 * 1e3)\n",
    "    scenario$add_par('var_cost', df)\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Dynamic Behavior Parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
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   "outputs": [],
   "source": [
    "base_growth = data.frame(\n",
    "    node_loc = country,\n",
    "    year_act = horizon[-1],\n",
    "    value = 0.05,\n",
    "    time = 'year',\n",
    "    unit = '%'\n",
    ")\n",
    "\n",
    "growth_technologies = c(\n",
    "    \"coal_ppl\", \n",
    "    \"gas_ppl\", \n",
    "    \"oil_ppl\", \n",
    "    \"bio_ppl\", \n",
    "    \"hydro_ppl\",\n",
    "    \"wind_ppl\", \n",
    "    \"solar_pv_ppl\", \n",
    "    \"cfl\",\n",
    "    \"bulb\"\n",
    ")\n",
    "\n",
    "for (tec in (growth_technologies)){\n",
    "    df = data.frame(base_growth, technology= tec)\n",
    "    scenario$add_par('growth_activity_up', df)\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [],
   "source": [
    "base_initial = data.frame(\n",
    "    node_loc = country,\n",
    "    year_act = horizon[-1],\n",
    "    time = 'year',\n",
    "    unit = '%'\n",
    ")\n",
    "\n",
    "for (tec in (lights)){\n",
    "    df = data.frame(base_initial, technology= tec, value = 0.01 *light_demand$value[light_demand$year %in% c(2020,2030,2040)])\n",
    "    scenario$add_par('initial_activity_up', df)\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [],
   "source": [
    "base_activity = data.frame(\n",
    "    node_loc = country,\n",
    "    year_act = as.integer(2010),\n",
    "    mode = 'standard',\n",
    "    time = 'year',\n",
    "    unit = 'GWa'\n",
    ")\n",
    "\n",
    "# in GWh - from IEA Electricity Output\n",
    "activity = list(\n",
    "    coal_ppl = 7184,\n",
    "    gas_ppl =  14346,\n",
    "    oil_ppl =  1275,\n",
    "    hydro_ppl = 38406,\n",
    "    bio_ppl =  4554,\n",
    "    wind_ppl = 2064,\n",
    "    solar_pv_ppl = 89,\n",
    "    import = 2340,\n",
    "    cfl = 0\n",
    ")\n",
    "\n",
    "for (i in seq_along(activity)){\n",
    "    df = data.frame(base_activity, technology=names(activity[i]), value=activity[[i]]/8760)\n",
    "    scenario$add_par('bound_activity_up', df)\n",
    "    scenario$add_par('bound_activity_lo', df)\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [],
   "source": [
    "base_capacity = data.frame(\n",
    "    node_loc = country,\n",
    "    year_vtg = as.integer(2010),\n",
    "    unit = 'GWa'\n",
    ")\n",
    "\n",
    "a = as.data.frame(t(as.data.frame(activity))) %>% rename(act = V1)\n",
    "b = as.data.frame(t(as.data.frame(capacity_factor)))%>% rename(cf = V1) \n",
    "capacity = left_join(\n",
    "    a%>% mutate(technology = row.names(a)),\n",
    "    b%>% mutate(technology = row.names(b))) %>% \n",
    "  mutate(value = (act / 8760 / cf)) %>% \n",
    "  filter(!is.na(value))\n",
    "\n",
    "df = data.frame(base_capacity,capacity)\n",
    "scenario$add_par('bound_new_capacity_up', df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [],
   "source": [
    "base_activity = data.frame(\n",
    "    node_loc = country,\n",
    "    year_act = horizon[-1],\n",
    "    mode = 'standard',\n",
    "    time = 'year',\n",
    "    unit = 'GWa'\n",
    ")\n",
    "\n",
    "# in GWh - base value from IEA Electricity Output\n",
    "keep_activity = list(\n",
    "    hydro_ppl = 38406,\n",
    "    bio_ppl =  4554,\n",
    "    import = 2340\n",
    ")\n",
    "    \n",
    "for (i in seq_along(keep_activity)){\n",
    "    df = data.frame(base_activity, technology=names(keep_activity[i]), value=keep_activity[[i]])\n",
    "    scenario$add_par('bound_activity_up', df)\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Emissions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [],
   "source": [
    "scenario$add_set(\"emission\", \"CO2\")\n",
    "scenario$add_cat('emission', 'GHGs', 'CO2')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [],
   "source": [
    "base_emissions = data.frame(\n",
    "    node_loc = country,\n",
    "    year_vtg = vintage_years,\n",
    "    year_act = act_years,\n",
    "    mode = 'standard',\n",
    "    unit = 'kg/kWa' # actually is tCO2/GWa\n",
    ")\n",
    "\n",
    "# units: tCO2/MWh\n",
    "emissions = list(\n",
    "    coal_ppl =  c('CO2', 0.854),\n",
    "    gas_ppl =   c('CO2', 0.339),\n",
    "    oil_ppl =   c('CO2', 0.57)\n",
    ")\n",
    "    \n",
    "for (i in seq_along(emissions)){\n",
    "    df = data.frame(base_emissions, technology=names(emissions[i]),emission = emissions[[i]][1], value = (as.numeric(emissions[[i]][2])* 8760. * 1000) )\n",
    "    scenario$add_par('emission_factor', df)\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Commit the datastructure and solve the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [],
   "source": [
    "comment = 'initial commit for Austria model'\n",
    "scenario$commit(comment)\n",
    "scenario$set_as_default()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [],
   "source": [
    "scenario$solve('MESSAGE')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [],
   "source": [
    "scenario$var('OBJ')['lvl']"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true,
    "vscode": {
     "languageId": "r"
    }
   },
   "outputs": [],
   "source": [
    "mp$close_db()"
   ]
  }
 ],
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