vre_stor_gens_breakdown.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np\n",
    "import os\n",
    "path = os.getcwd()\n",
    "from pathlib import Path\n",
    "import pathlib"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Inputs into function\n",
    "case_folder = \"/Users/aneesha/Dropbox (Personal)/ANEESHA/Princeton/Jenkins Research/VRE-STOR/vrestor-preprocessing/Paper1\"\n",
    "storage_type=\"Battery\"\n",
    "zero_out_storage_costs = False\n",
    "itc_stor = True\n",
    "colocated_on = True"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Constants\n",
    "\n",
    "fom_cost_allocation = {\n",
    "        \"pv\":0.87,\n",
    "        \"inverter\":0.13,\n",
    "        \"gcc\":0\n",
    "}\n",
    "\n",
    "pv_dc_ac_cost_ratio = 0.728\n",
    "stor_dc_ac_cost_ratio = 0.945\n",
    "\n",
    "# For IRA tax credits\n",
    "if itc_stor==True:\n",
    "        stor_itc = 0.649\n",
    "else:\n",
    "        stor_itc = 1\n",
    "\n",
    "### NEED TO CALCULATE OUTSIDE THIS SHEET: INVERTER AVERAGE COST OVER PLANNING PERIOD\n",
    "inv_cost_capex = 59746.66\n",
    "\n",
    "### STANDALONE STORAGE SPUR LINE COSTS\n",
    "stor_standalone_gcc = [5101, 5101, 2267, 2267, 2267, 5101, 2267, 2267, 2267, 2267, 2267, 2267, 2267, 5101]\n",
    "\n",
    "# Classify storage\n",
    "if storage_type == \"LDES\":\n",
    "        storage_tech_str = \"MetalAir\"\n",
    "        self_disch = 0\n",
    "        eff_up = 0.65\n",
    "        eff_down = 0.65\n",
    "        etainverter=0.96\n",
    "        power_to_energy_ratio = 1 / 200\n",
    "elif storage_type ==\"Battery\":\n",
    "    storage_tech_str = \"Battery\"\n",
    "    self_disch = 0.05\n",
    "    eff_up = 0.95\n",
    "    eff_down = 0.95\n",
    "    etainverter=0.96\n",
    "    power_to_energy_ratio = 1 / 4\n",
    "else:\n",
    "    raise ValueError(\"not a valid storage type\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Read in data\n",
    "if os.path.exists(case_folder + \"/Generators_data_before_vrestor.csv\"):\n",
    "        generators_data = pd.read_csv(case_folder + \"/Generators_data_before_vrestor.csv\")\n",
    "else:\n",
    "    generators_data = pd.read_csv(case_folder + \"/Generators_data.csv\")\n",
    "generators_data[\"R_ID\"] = generators_data.index + 1\n",
    "\n",
    "output = pd.DataFrame()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# DC costs for hybrid PV and storage plants\n",
    "\n",
    "pv_generators = generators_data[generators_data.technology.str.contains(\"UtilityPV\")].copy(deep=True)\n",
    "pv_inv_cost_ac = pv_generators.capex_mw\n",
    "pv_inv_cost_dc = pv_inv_cost_ac * pv_dc_ac_cost_ratio # DC dropped values for year\n",
    "\n",
    "storage_generators = generators_data[generators_data.technology.str.contains(storage_tech_str)].copy(deep=True)\n",
    "storage_capex_mwh_ac = storage_generators.capex_mwh.iloc[0] + storage_generators.capex_mw.iloc[0]/(1/power_to_energy_ratio)\n",
    "storage_capex_mwh_dc = storage_capex_mwh_ac * stor_dc_ac_cost_ratio\n",
    "storage_capex_mwh_dc_itc = storage_capex_mwh_dc * stor_itc\n",
    "\n",
    "# Create hybrid PV resources\n",
    "hybrid_pv = pv_generators[[\"region\",\"Resource\",\"technology\"]].copy(deep=True)\n",
    "hybrid_pv.technology = \"hybrid_pv\"\n",
    "storage_financial_parameters = storage_generators[[\"region\",\"wacc_real\",\"cap_recovery_years\",\"regional_cost_multiplier\"]].rename(columns={\n",
    "    \"wacc_real\":\"storage_wacc_real\",\n",
    "    \"cap_recovery_years\":\"storage_cap_recovery_years\",\n",
    "    \"regional_cost_multiplier\":\"storage_regional_cost_multiplier\"\n",
    "}) \n",
    "index_before = pv_generators.index\n",
    "pv_generators = pd.merge(pv_generators,storage_financial_parameters,on=\"region\")\n",
    "pv_generators.index = index_before\n",
    "\n",
    "crf = (\n",
    "    np.exp(pv_generators.wacc_real*pv_generators.cap_recovery_years)\n",
    "    *(np.exp(pv_generators.wacc_real)-1)\n",
    ")/(\n",
    "    np.exp(pv_generators.wacc_real*pv_generators.cap_recovery_years)-1\n",
    ")\n",
    "\n",
    "crf_storage = (\n",
    "    np.exp(pv_generators.storage_wacc_real*pv_generators.storage_cap_recovery_years)\n",
    "    *(np.exp(pv_generators.storage_wacc_real)-1)\n",
    ")/(\n",
    "    np.exp(pv_generators.storage_wacc_real*pv_generators.storage_cap_recovery_years)-1\n",
    ")\n",
    "\n",
    "hybrid_pv[\"Inv_Cost_per_MWyr\"] = pv_generators[\"interconnect_annuity\"]\n",
    "hybrid_pv[\"Inv_Cost_Solar_per_MWyr\"] = pv_inv_cost_dc * pv_generators[\"regional_cost_multiplier\"] * crf\n",
    "hybrid_pv[\"Inv_Cost_Inverter_per_MWyr\"] = inv_cost_capex * pv_generators[\"storage_regional_cost_multiplier\"] * crf_storage * stor_itc\n",
    "hybrid_pv[\"Inv_Cost_Wind_per_MWyr\"] = 0\n",
    "if zero_out_storage_costs:\n",
    "    hybrid_pv[\"Inv_Cost_per_MWhyr\"] = 0\n",
    "else:\n",
    "    hybrid_pv[\"Inv_Cost_per_MWhyr\"] = storage_capex_mwh_dc_itc * pv_generators[\"storage_regional_cost_multiplier\"] * crf_storage\n",
    "\n",
    "\n",
    "hybrid_pv[\"Fixed_OM_Cost_per_MWyr\"] = pv_generators[\"Fixed_OM_Cost_per_MWyr\"] * fom_cost_allocation[\"gcc\"]\n",
    "hybrid_pv[\"Fixed_OM_Solar_Cost_per_MWyr\"] = pv_generators[\"Fixed_OM_Cost_per_MWyr\"] * fom_cost_allocation[\"pv\"]\n",
    "hybrid_pv[\"Fixed_OM_Inverter_Cost_per_MWyr\"] = pv_generators[\"Fixed_OM_Cost_per_MWyr\"] * fom_cost_allocation[\"inverter\"]\n",
    "hybrid_pv[\"Fixed_OM_Wind_Cost_per_MWyr\"] = 0\n",
    "if zero_out_storage_costs:\n",
    "    hybrid_pv[\"Fixed_OM_Cost_per_MWhyr\"] = 0\n",
    "else:\n",
    "    hybrid_pv[\"Fixed_OM_Cost_per_MWhyr\"] = storage_capex_mwh_dc * 0.025\n",
    "\n",
    "output = pd.concat([output,hybrid_pv],axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Costs for hybrid wind and storage plants\n",
    "\n",
    "wind_generators = generators_data[generators_data.technology.str.contains(\"LandbasedWind\")].copy(deep=True)\n",
    "hybrid_wind = wind_generators[[\"region\",\"Resource\",\"technology\"]].copy(deep=True)\n",
    "hybrid_wind.technology = \"hybrid_wind\"\n",
    "storage_financial_parameters = storage_generators[[\"region\",\"wacc_real\",\"cap_recovery_years\",\"regional_cost_multiplier\"]].rename(columns={\n",
    "    \"wacc_real\":\"storage_wacc_real\",\n",
    "    \"cap_recovery_years\":\"storage_cap_recovery_years\",\n",
    "    \"regional_cost_multiplier\":\"storage_regional_cost_multiplier\"\n",
    "})\n",
    "index_before = wind_generators.index\n",
    "wind_generators = pd.merge(wind_generators,storage_financial_parameters,on=\"region\")\n",
    "wind_generators.index = index_before\n",
    "\n",
    "crf_storage = (\n",
    "    np.exp(wind_generators.storage_wacc_real*wind_generators.storage_cap_recovery_years)\n",
    "    *(np.exp(wind_generators.storage_wacc_real)-1)\n",
    ")/(\n",
    "    np.exp(wind_generators.storage_wacc_real*wind_generators.storage_cap_recovery_years)-1\n",
    ")\n",
    "\n",
    "hybrid_wind[\"Inv_Cost_per_MWyr\"] = wind_generators[\"interconnect_annuity\"]\n",
    "hybrid_wind[\"Inv_Cost_Wind_per_MWyr\"] = wind_generators[\"Inv_Cost_per_MWyr\"] - wind_generators[\"interconnect_annuity\"]\n",
    "hybrid_wind[\"Inv_Cost_Inverter_per_MWyr\"] = inv_cost_capex * wind_generators[\"storage_regional_cost_multiplier\"] * crf_storage * stor_itc\n",
    "hybrid_wind[\"Inv_Cost_Solar_per_MWyr\"] = 0\n",
    "if zero_out_storage_costs:\n",
    "    hybrid_wind[\"Inv_Cost_per_MWhyr\"] = 0\n",
    "else:\n",
    "    hybrid_wind[\"Inv_Cost_per_MWhyr\"] = storage_capex_mwh_dc_itc * wind_generators[\"storage_regional_cost_multiplier\"] * crf_storage\n",
    "\n",
    "hybrid_wind[\"Fixed_OM_Cost_per_MWyr\"] = hybrid_pv[\"Fixed_OM_Cost_per_MWyr\"].iloc[0]\n",
    "hybrid_wind[\"Fixed_OM_Inverter_Cost_per_MWyr\"] = hybrid_pv[\"Fixed_OM_Inverter_Cost_per_MWyr\"].iloc[0]\n",
    "hybrid_wind[\"Fixed_OM_Solar_Cost_per_MWyr\"] = 0\n",
    "hybrid_wind[\"Fixed_OM_Wind_Cost_per_MWyr\"] = wind_generators[\"Fixed_OM_Cost_per_MWyr\"] - hybrid_pv[\"Fixed_OM_Cost_per_MWyr\"].iloc[0]\n",
    "if zero_out_storage_costs:\n",
    "    hybrid_wind[\"Fixed_OM_Cost_per_MWhyr\"] = 0\n",
    "else:\n",
    "    hybrid_wind[\"Fixed_OM_Cost_per_MWhyr\"] = storage_capex_mwh_dc * 0.025\n",
    "\n",
    "output = pd.concat([output,hybrid_wind],axis=0)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "# make standalone storage resources\n",
    "standalone_storage = storage_generators[[\"region\",\"Resource\",\"technology\"]].copy(deep=True)\n",
    "standalone_storage.technology = \"standalone_storage\"\n",
    "\n",
    "crf = (\n",
    "    np.exp(storage_generators.wacc_real*storage_generators.cap_recovery_years)\n",
    "    *(np.exp(storage_generators.wacc_real)-1)\n",
    ")/(\n",
    "    np.exp(storage_generators.wacc_real*storage_generators.cap_recovery_years)-1\n",
    ")\n",
    "\n",
    "standalone_storage[\"Inv_Cost_per_MWyr\"] = stor_standalone_gcc\n",
    "standalone_storage[\"Inv_Cost_Inverter_per_MWyr\"] = inv_cost_capex * storage_generators[\"regional_cost_multiplier\"] * crf * stor_itc\n",
    "standalone_storage[\"Inv_Cost_Solar_per_MWyr\"] = 0\n",
    "standalone_storage[\"Inv_Cost_Wind_per_MWyr\"] = 0\n",
    "if zero_out_storage_costs:\n",
    "    standalone_storage[\"Inv_Cost_per_MWhyr\"] = 0\n",
    "else:\n",
    "    standalone_storage[\"Inv_Cost_per_MWhyr\"] = storage_capex_mwh_dc_itc * storage_generators[\"regional_cost_multiplier\"] * crf\n",
    "\n",
    "standalone_storage[\"Fixed_OM_Cost_per_MWyr\"] = hybrid_pv[\"Fixed_OM_Cost_per_MWyr\"].iloc[0]\n",
    "standalone_storage[\"Fixed_OM_Inverter_Cost_per_MWyr\"] = hybrid_pv[\"Fixed_OM_Inverter_Cost_per_MWyr\"].iloc[0]\n",
    "standalone_storage[\"Fixed_OM_Solar_Cost_per_MWyr\"] = 0\n",
    "standalone_storage[\"Fixed_OM_Wind_Cost_per_MWyr\"] = 0\n",
    "if zero_out_storage_costs:\n",
    "    standalone_storage[\"Fixed_OM_Cost_per_MWhyr\"] = 0\n",
    "else:\n",
    "    standalone_storage[\"Fixed_OM_Cost_per_MWhyr\"] = storage_capex_mwh_dc * 0.025\n",
    "\n",
    "cost_breakdown = pd.concat([output,standalone_storage],axis=0)\n",
    "\n",
    "cost_breakdown.rename(columns={\"technology\":\"Resource_Type\"},inplace=True)\n",
    "cost_breakdown.drop(columns=\"region\",inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "#### make Vre_stor_data.csv\n",
    "\n",
    "vrestor_data = pd.merge(\n",
    "    generators_data[generators_data.Resource.isin(cost_breakdown.Resource)].copy(deep=True),\n",
    "    cost_breakdown,\n",
    "    on=\"Resource\"\n",
    ")\n",
    "vrestor_data[\"SOLAR\"] = 0\n",
    "vrestor_data.loc[vrestor_data.Resource_Type==\"hybrid_pv\",\"SOLAR\"] = 1\n",
    "vrestor_data[\"WIND\"] = 0\n",
    "vrestor_data.loc[vrestor_data.Resource_Type==\"hybrid_wind\",\"WIND\"] = 1\n",
    "vrestor_data[\"STOR_DC_DISCHARGE\"] = 1\n",
    "vrestor_data[\"STOR_DC_CHARGE\"] = 1\n",
    "\n",
    "# transfer any active MinCap constraints to all VREStor resources. Currently assumes that the MinCap constraints are being applied to storage only.\n",
    "for mincap_column in vrestor_data.columns[vrestor_data.columns.str.contains(\"MinCap\")]:\n",
    "    new_mincap_column_name = \"MinCapTagStor\" + \"_\" + mincap_column.split(\"_\")[1]\n",
    "    regions_with_active_mincap = pd.unique(vrestor_data[vrestor_data[mincap_column]==1].region)\n",
    "    vrestor_data[new_mincap_column_name] = 0\n",
    "    vrestor_data.loc[vrestor_data.region.isin(regions_with_active_mincap),new_mincap_column_name] = 1\n",
    "    vrestor_data[mincap_column] = 0\n",
    "    vrestor_data[\"MinCapTagSolar\" + \"_\" + mincap_column.split(\"_\")[1]] = 0\n",
    "    vrestor_data[\"MinCapTagWind\" + \"_\" + mincap_column.split(\"_\")[1]] = 0\n",
    "\n",
    "# transfer any active MaxCap constraints to all VREStor resources. Currently sets the MaxCapTag_MWh_x column to 1 and the regular maxcap column to 0\n",
    "for maxcap_column in vrestor_data.columns[vrestor_data.columns.str.contains(\"MaxCap\")]:\n",
    "    new_maxcap_column_name = \"MaxCapTagStor\" + \"_\" + maxcap_column.split(\"_\")[1]\n",
    "    regions_with_active_maxcap = pd.unique(vrestor_data[vrestor_data[maxcap_column]==1].region)\n",
    "    vrestor_data[new_maxcap_column_name] = 0\n",
    "    vrestor_data.loc[vrestor_data.region.isin(regions_with_active_maxcap),new_maxcap_column_name] = 1\n",
    "    vrestor_data[maxcap_column] = 0\n",
    "    vrestor_data[\"MaxCapTagSolar\" + \"_\" + maxcap_column.split(\"_\")[1]] = 0\n",
    "    vrestor_data[\"MaxCapTagWind\" + \"_\" + maxcap_column.split(\"_\")[1]] = 0\n",
    "\n",
    "for col_name in [\"STOR_AC_DISCHARGE\",\"STOR_AC_CHARGE\",\"Existing_Cap_Inverter_MW\",\"Existing_Cap_Solar_MW\",\"Existing_Cap_Wind_MW\",\n",
    "                \"Existing_Cap_Charge_DC_MW\",\"Existing_Cap_Charge_AC_MW\",\"Existing_Cap_Discharge_DC_MW\",\"Existing_Cap_Discharge_AC_MW\",\n",
    "                \"Min_Cap_Inverter_MW\",\"Min_Cap_Charge_AC_MW\",\"Min_Cap_Discharge_AC_MW\",\"Min_Cap_Charge_DC_MW\",\"Min_Cap_Discharge_DC_MW\",\"Min_Cap_Solar_MW\",\"Min_Cap_Wind_MW\",\n",
    "                \"Inv_Cost_Discharge_DC_per_MWyr\",\"Inv_Cost_Charge_DC_per_MWyr\",\"Inv_Cost_Discharge_AC_per_MWyr\",\"Inv_Cost_Charge_AC_per_MWyr\",\n",
    "                \"Fixed_OM_Cost_Discharge_DC_per_MWyr\",\"Fixed_OM_Cost_Charge_DC_per_MWyr\",\"Fixed_OM_Cost_Discharge_AC_per_MWyr\",\"Fixed_OM_Cost_Charge_AC_per_MWyr\",\n",
    "                \"Var_OM_Cost_per_MWh_Solar\",\"Var_OM_Cost_per_MWh_Wind\",\"Var_OM_Cost_per_MWh_Charge_AC\",\"Var_OM_Cost_per_MWh_Discharge_AC\"]:\n",
    "    vrestor_data[col_name] = 0\n",
    "for col_name in [\"Max_Cap_Inverter_MW\",\"Max_Cap_Charge_AC_MW\",\"Max_Cap_Discharge_AC_MW\",\"Max_Cap_Charge_DC_MW\",\"Max_Cap_Discharge_DC_MW\",\n",
    "                \"Max_Cap_Solar_MW\",\"Max_Cap_Wind_MW\",\"Inverter_Ratio_Wind\",\"Inverter_Ratio_Solar\"]:\n",
    "    vrestor_data[col_name] = -1\n",
    "\n",
    "vrestor_data.loc[vrestor_data.Resource_Type==\"hybrid_pv\",\"Max_Cap_Solar_MW\"] = vrestor_data.loc[vrestor_data.Resource_Type==\"hybrid_pv\",\"Max_Cap_MW\"] * 1.3\n",
    "vrestor_data.loc[vrestor_data.Resource_Type==\"hybrid_wind\",\"Max_Cap_Wind_MW\"] = vrestor_data.loc[vrestor_data.Resource_Type==\"hybrid_wind\",\"Max_Cap_MW\"]\n",
    "\n",
    "vrestor_data.loc[vrestor_data.Resource_Type==\"hybrid_pv\",\"Var_OM_Cost_per_MWh_Solar\"] = vrestor_data.loc[vrestor_data.Resource_Type==\"hybrid_pv\",\"Var_OM_Cost_per_MWh\"]\n",
    "vrestor_data.loc[vrestor_data.Resource_Type==\"hybrid_wind\",\"Var_OM_Cost_per_MWh_Wind\"] = vrestor_data.loc[vrestor_data.Resource_Type==\"hybrid_wind\",\"Var_OM_Cost_per_MWh\"]\n",
    "\n",
    "vrestor_data[\"Var_OM_Cost_per_MWh_Charge_DC\"] = 0.15\n",
    "vrestor_data[\"Var_OM_Cost_per_MWh_Discharge_DC\"] = 0.15\n",
    "\n",
    "vrestor_data[\"Self_Disch\"] = self_disch\n",
    "vrestor_data[\"Eff_Up_DC\"] = eff_up\n",
    "vrestor_data[\"Eff_Down_DC\"] = eff_down\n",
    "vrestor_data[\"Eff_Up_AC\"] = eff_up\n",
    "vrestor_data[\"Eff_Down_AC\"] = eff_down\n",
    "\n",
    "vrestor_data[\"EtaInverter\"] = etainverter\n",
    "vrestor_data[\"Power_to_Energy_DC\"] = power_to_energy_ratio\n",
    "vrestor_data[\"Power_to_Energy_AC\"] = power_to_energy_ratio\n",
    "\n",
    "vrestor_data.rename(columns={\"LDS\":\"LDS_VRE_STOR\"},inplace=True)\n",
    "\n",
    "if storage_type == \"LDES\":\n",
    "    vrestor_data[\"LDS_VRE_STOR\"] = 1\n",
    "\n",
    "pv_and_wind_vrestor_resources = vrestor_data.Resource[vrestor_data.Resource_Type != \"standalone_storage\"]\n",
    "for capres_column in vrestor_data.columns[vrestor_data.columns.str.contains(\"CapRes\")]:\n",
    "    components = capres_column.split(\"_\")\n",
    "    new_name = components[0] + \"VreStor\" + \"_\" + components[1]\n",
    "    vrestor_data.loc[vrestor_data.Resource.isin(pv_and_wind_vrestor_resources),capres_column] =  vrestor_data.loc[vrestor_data.Resource.isin(pv_and_wind_vrestor_resources),capres_column] * (0.95/0.8)\n",
    "    vrestor_data.rename(columns={capres_column:new_name},inplace=True)\n",
    "\n",
    "for esr_column in vrestor_data.columns[vrestor_data.columns.str.contains(\"ESR\")]:\n",
    "    components = esr_column.split(\"_\")\n",
    "    new_name = components[0] + \"VreStor\" + \"_\" + components[1]\n",
    "    vrestor_data.rename(columns={esr_column:new_name},inplace=True)\n",
    "\n",
    "if not colocated_on:\n",
    "    vrestor_data.loc[vrestor_data.Resource_Type != \"standalone_storage\",\"STOR_DC_DISCHARGE\"] = 0\n",
    "    vrestor_data.loc[vrestor_data.Resource_Type != \"standalone_storage\",\"STOR_DC_CHARGE\"] = 0\n",
    "    vrestor_data.loc[vrestor_data.Resource_Type != \"standalone_storage\",\"LDS_VRE_STOR\"] = 0\n",
    "\n",
    "#### modify generators_data\n",
    "\n",
    "gendata_mod = generators_data.copy(deep=True)\n",
    "vrestor_resources = vrestor_data.Resource\n",
    "\n",
    "# reset relevant columns\n",
    "for capres_column in gendata_mod.columns[gendata_mod.columns.str.contains(\"CapRes\")]:\n",
    "    gendata_mod.loc[gendata_mod.Resource.isin(vrestor_resources),capres_column] = 0\n",
    "for mincap_column in gendata_mod.columns[gendata_mod.columns.str.contains(\"MinCap\")]:\n",
    "    gendata_mod.loc[gendata_mod.Resource.isin(vrestor_resources),mincap_column] = 0\n",
    "for maxcap_column in gendata_mod.columns[gendata_mod.columns.str.contains(\"MaxCap\")]:\n",
    "    gendata_mod.loc[gendata_mod.Resource.isin(vrestor_resources),maxcap_column] = 0\n",
    "for esr_column in gendata_mod.columns[gendata_mod.columns.str.contains(\"ESR\")]:\n",
    "    gendata_mod.loc[gendata_mod.Resource.isin(vrestor_resources),esr_column] = 0\n",
    "for col_name in [\"VRE\",\"STOR\",\"Var_OM_Cost_per_MWh_In\",\"Eff_Up\",\"Eff_Down\",\"Min_Duration\",\"Max_Duration\",\"Ramp_Up_Percentage\",\"Ramp_Dn_Percentage\",\"Num_VRE_Bins\",\"LDS\"]:\n",
    "    gendata_mod.loc[gendata_mod.Resource.isin(vrestor_resources),col_name] = 0\n",
    "for col_name in [\"Var_OM_Cost_per_MWh\"]:\n",
    "    gendata_mod.loc[gendata_mod.Resource.isin(vrestor_resources),col_name] = 0.15\n",
    "gendata_mod.loc[gendata_mod.Resource.isin(vrestor_resources),\"Max_Cap_MW\"] = -1\n",
    "gendata_mod.loc[gendata_mod.Resource.isin(vrestor_resources),\"Max_Cap_MWh\"] = -1\n",
    "if not colocated_on:\n",
    "    gendata_mod.loc[gendata_mod.Resource.isin(pv_and_wind_vrestor_resources),\"Max_Cap_MWh\"] = 0\n",
    "gendata_mod.loc[gendata_mod.Resource.isin(vrestor_resources),\"Self_Disch\"] = self_disch\n",
    "gendata_mod[\"VRE_STOR\"] = 0\n",
    "gendata_mod.loc[gendata_mod.Resource.isin(vrestor_resources),\"VRE_STOR\"] = 1\n",
    "\n",
    "# get costs from cost_breakdown\n",
    "gendata_mod.set_index(\"Resource\",inplace=True)\n",
    "for cost_category in [\"Inv_Cost_per_MWyr\",\"Fixed_OM_Cost_per_MWyr\",\"Inv_Cost_per_MWhyr\",\"Fixed_OM_Cost_per_MWhyr\"]:\n",
    "    costs = cost_breakdown.set_index(\"Resource\")[cost_category]\n",
    "    gendata_mod.loc[costs.index,cost_category] = costs\n",
    "\n",
    "# this is a hack to get the region and Resource columns back to the order they started in\n",
    "gendata_mod.reset_index(inplace=True)\n",
    "gendata_mod.set_index([\"region\",\"Resource\"],inplace=True)\n",
    "gendata_mod.reset_index(inplace=True)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Finished creating VREStor inputs.\n"
     ]
    }
   ],
   "source": [
    "#### export results\n",
    "\n",
    "vrestor_data = vrestor_data.drop(columns=[\"Num_VRE_Bins\", \"VRE\", \"THERM\", \"MUST_RUN\", \"STOR\", \"FLEX\", \"HYDRO\", \"VRE_STOR\", \"Min_Share\", \"Max_Share\", \"Existing_Cap_MWh\", \"Existing_Cap_MW\", \"Existing_Charge_Cap_MW\", \"num_units\", \"unmodified_existing_cap_mw\", \"New_Build\", \"Cap_Size\", \"Min_Cap_MW\", \"Max_Cap_MW\", \"Max_Cap_MWh\", \"Min_Cap_MWh\", \"Max_Charge_Cap_MW\", \"Min_Charge_Cap_MW\", \"Min_Share_percent\", \"Max_Share_percent\",\"capex_mw\", \"Inv_Cost_per_MWyr_x\", \"Inv_Cost_per_MWyr_y\", \"Fixed_OM_Cost_per_MWyr_x\", \"Fixed_OM_Cost_per_MWyr_y\", \"capex_mwh\", \"Inv_Cost_per_MWhyr_x\", \"Inv_Cost_per_MWhyr_y\", \"Fixed_OM_Cost_per_MWhyr_x\", \"Fixed_OM_Cost_per_MWhyr_y\",\"Var_OM_Cost_per_MWh\", \"Var_OM_Cost_per_MWh_In\", \"Inv_Cost_Charge_per_MWyr\", \"Fixed_OM_Cost_Charge_per_MWyr\",\"Start_Cost_per_MW\", \"Start_Fuel_MMBTU_per_MW\", \"Heat_Rate_MMBTU_per_MWh\", \"heat_rate_mmbtu_mwh_iqr\", \"heat_rate_mmbtu_mwh_std\", \"Fuel\", \"Min_Power\", \"Self_Disch\", \"Eff_Up\", \"Eff_Down\", \"Hydro_Energy_to_Power_Ratio\",\"Ratio_power_to_energy\", \"Min_Duration\", \"Max_Duration\", \"Max_Flexible_Demand_Delay\", \"Max_Flexible_Demand_Advance\", \"Flexible_Demand_Energy_Eff\", \"Ramp_Up_Percentage\", \"Ramp_Dn_Percentage\", \"Up_Time\", \"Down_Time\", \"NACC_Eff\", \"NACC_Peak_to_Base\", \"Reg_Max\", \"Rsv_Max\", \"Reg_Cost\", \"Rsv_Cost\", \"spur_miles\", \"spur_capex\", \"offshore_spur_miles\", \"offshore_spur_capex\", \"tx_miles\",\"tx_capex\", \"interconnect_annuity\", \"spur_inv_mwyr\", \"regional_cost_multiplier\", \"wacc_real\", \"investment_years\", \"lcoe\", \"cap_recovery_years\", \"cpa_id\", \"Commit\", \"Hydro_level\"])\n",
    "\n",
    "vrestor_data = vrestor_data.round({'Inv_Cost_Solar_per_MWyr': 0, 'Inv_Cost_Wind_per_MWyr': 0, 'Inv_Cost_Inverter_per_MWyr': 0,'Fixed_OM_Solar_Cost_per_MWyr':0, 'Fixed_OM_Wind_Cost_per_MWyr': 0, 'Fixed_OM_Inverter_Cost_per_MWyr':0})\n",
    "gendata_mod = gendata_mod.round({'Inv_Cost_per_MWyr': 0, 'Inv_Cost_per_MWhyr': 0, 'Fixed_OM_Cost_per_MWyr':0, 'Fixed_OM_Cost_per_MWhyr': 0})\n",
    "\n",
    "#generators_data.to_csv(case_folder + \".Generators_data_before_vrestor.csv\",index=False)\n",
    "vrestor_data.to_csv(case_folder + \"/Vre_and_stor_data.csv\",index=False)\n",
    "gendata_mod.to_csv(case_folder + \"/Generators_data.csv\",index=False)\n",
    "\n",
    "print(\"Finished creating VREStor inputs.\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "ename": "FileNotFoundError",
     "evalue": "[Errno 2] File /Users/aneesha/Dropbox (Personal)/ANEESHA/Princeton/Jenkins Research/VRE-STOR/vrestor-preprocessing/Paper1/Generators_variability.csv does not exist: '/Users/aneesha/Dropbox (Personal)/ANEESHA/Princeton/Jenkins Research/VRE-STOR/vrestor-preprocessing/Paper1/Generators_variability.csv'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mFileNotFoundError\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-10-596ee88f03b0>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;31m#### create variability data\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      2\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 3\u001b[0;31m \u001b[0mgenerators_variability\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mread_csv\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mcase_folder\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;34m\"/Generators_variability.csv\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mset_index\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m\"Time_Index\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      4\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0mhybrid_pv_resources\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mvrestor_data\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mloc\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mvrestor_data\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mResource_Type\u001b[0m\u001b[0;34m==\u001b[0m\u001b[0;34m\"hybrid_pv\"\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\"Resource\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/opt/anaconda3/lib/python3.8/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36mparser_f\u001b[0;34m(filepath_or_buffer, sep, delimiter, header, names, index_col, usecols, squeeze, prefix, mangle_dupe_cols, dtype, engine, converters, true_values, false_values, skipinitialspace, skiprows, skipfooter, nrows, na_values, keep_default_na, na_filter, verbose, skip_blank_lines, parse_dates, infer_datetime_format, keep_date_col, date_parser, dayfirst, cache_dates, iterator, chunksize, compression, thousands, decimal, lineterminator, quotechar, quoting, doublequote, escapechar, comment, encoding, dialect, error_bad_lines, warn_bad_lines, delim_whitespace, low_memory, memory_map, float_precision)\u001b[0m\n\u001b[1;32m    674\u001b[0m         )\n\u001b[1;32m    675\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 676\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0m_read\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfilepath_or_buffer\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    677\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    678\u001b[0m     \u001b[0mparser_f\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__name__\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/opt/anaconda3/lib/python3.8/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m_read\u001b[0;34m(filepath_or_buffer, kwds)\u001b[0m\n\u001b[1;32m    446\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    447\u001b[0m     \u001b[0;31m# Create the parser.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 448\u001b[0;31m     \u001b[0mparser\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mTextFileReader\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfp_or_buf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    449\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    450\u001b[0m     \u001b[0;32mif\u001b[0m \u001b[0mchunksize\u001b[0m \u001b[0;32mor\u001b[0m \u001b[0miterator\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/opt/anaconda3/lib/python3.8/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, f, engine, **kwds)\u001b[0m\n\u001b[1;32m    878\u001b[0m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moptions\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"has_index_names\"\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mkwds\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"has_index_names\"\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    879\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 880\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_make_engine\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mengine\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m    881\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    882\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0mclose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/opt/anaconda3/lib/python3.8/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m_make_engine\u001b[0;34m(self, engine)\u001b[0m\n\u001b[1;32m   1112\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m_make_engine\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mengine\u001b[0m\u001b[0;34m=\u001b[0m\u001b[0;34m\"c\"\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1113\u001b[0m         \u001b[0;32mif\u001b[0m \u001b[0mengine\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m\"c\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1114\u001b[0;31m             \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_engine\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mCParserWrapper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0moptions\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1115\u001b[0m         \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1116\u001b[0m             \u001b[0;32mif\u001b[0m \u001b[0mengine\u001b[0m \u001b[0;34m==\u001b[0m \u001b[0;34m\"python\"\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/opt/anaconda3/lib/python3.8/site-packages/pandas/io/parsers.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, src, **kwds)\u001b[0m\n\u001b[1;32m   1889\u001b[0m         \u001b[0mkwds\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m\"usecols\"\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0musecols\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1890\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1891\u001b[0;31m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_reader\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mparsers\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mTextReader\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msrc\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mkwds\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1892\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0munnamed_cols\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_reader\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0munnamed_cols\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1893\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader.__cinit__\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;32mpandas/_libs/parsers.pyx\u001b[0m in \u001b[0;36mpandas._libs.parsers.TextReader._setup_parser_source\u001b[0;34m()\u001b[0m\n",
      "\u001b[0;31mFileNotFoundError\u001b[0m: [Errno 2] File /Users/aneesha/Dropbox (Personal)/ANEESHA/Princeton/Jenkins Research/VRE-STOR/vrestor-preprocessing/Paper1/Generators_variability.csv does not exist: '/Users/aneesha/Dropbox (Personal)/ANEESHA/Princeton/Jenkins Research/VRE-STOR/vrestor-preprocessing/Paper1/Generators_variability.csv'"
     ]
    }
   ],
   "source": [
    "#### create variability data\n",
    "\n",
    "generators_variability = pd.read_csv(case_folder + \"/Generators_variability.csv\").set_index(\"Time_Index\")\n",
    "\n",
    "hybrid_pv_resources = vrestor_data.loc[vrestor_data.Resource_Type==\"hybrid_pv\",\"Resource\"]\n",
    "hybrid_wind_resources = vrestor_data.loc[vrestor_data.Resource_Type==\"hybrid_wind\",\"Resource\"]\n",
    "\n",
    "variability_pv = generators_variability[hybrid_pv_resources].reset_index()\n",
    "variability_wind = generators_variability[hybrid_wind_resources].reset_index()\n",
    "\n",
    "variability_pv.to_csv(case_folder + \"/Vre_and_stor_solar_variability.csv\",index=False)\n",
    "variability_wind.to_csv(case_folder + \"/Vre_and_stor_wind_variability.csv\",index=False)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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