Initial commit of LCOE calculator

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.python-version

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+3.11

main.py

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+from typing import Annotated
+from fastapi import FastAPI, Query
+from schema import SolarPVAssumptions
+from model import calculate_cashflow_for_renewable_project, calculate_lcoe
+
+app = FastAPI()
+
+@app.get("/solarpv/")
+def get_lcoe(pv_assumptions: Annotated[SolarPVAssumptions, Query()]):
+    return calculate_lcoe(pv_assumptions)

model.py

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+
+import numpy as np
+import polars as pl
+from pyxirr import irr, npv
+from functools import partial
+from scipy.optimize import fsolve
+
+from schema import SolarPVAssumptions
+
+def calculate_cashflow_for_renewable_project(assumptions, tariff, return_model=False):
+    # Create a dataframe, starting with the period
+    model = pl.DataFrame(
+        {
+            "Period": [i for i in range(assumptions.project_lifetime_years + 1)],
+        }
+    )
+
+    model = model.with_columns(
+        Capacity_MW = pl.when(pl.col("Period") > 0).then(assumptions.capacity_mw).otherwise(0),
+        Capacity_Factor = pl.when(pl.col("Period") > 0).then(assumptions.capacity_factor).otherwise(0),
+        Tariff_per_MWh = pl.when(pl.col("Period") > 0).then(tariff).otherwise(0),
+    ).with_columns(
+        Total_Generation_MWh = pl.col("Capacity_MW") * pl.col("Capacity_Factor") * 8760,
+    ).with_columns(
+        Total_Revenues_mn = pl.col("Total_Generation_MWh") * pl.col("Tariff_per_MWh")/1000,
+        O_M_Costs_mn = pl.when(pl.col("Period") > 0).then(assumptions.capital_cost/1000 * assumptions.o_m_cost_pct_of_capital_cost).otherwise(0),
+    ).with_columns(
+        Total_Operating_Costs_mn = pl.col("O_M_Costs_mn"),
+    ).with_columns(
+        EBITDA_mn = pl.col("Total_Revenues_mn") - pl.col("Total_Operating_Costs_mn"),
+    ).with_columns(
+        CFADS_mn = pl.col("EBITDA_mn"),
+    ).with_columns(
+        Target_Debt_Service_mn = pl.when(pl.col("Period") == 0).then(0).otherwise(pl.col("CFADS_mn")/assumptions.dcsr),
+        Debt_Outstanding_EoP_mn = pl.when(pl.col("Period") == 0).then(assumptions.debt_pct_of_capital_cost * assumptions.capital_cost/1000).otherwise(0),
+    ).with_columns(
+        Interest_Expense_mn = pl.when(pl.col("Period") == 0).then(0).otherwise(pl.col("Debt_Outstanding_EoP_mn").shift(1) * assumptions.cost_of_debt),
+    ).with_columns(
+        Amortization_mn = pl.when(pl.col("Period") == 0).then(0).otherwise(pl.min_horizontal(pl.col("Target_Debt_Service_mn") - pl.col("Interest_Expense_mn"), pl.col("Debt_Outstanding_EoP_mn").shift(1))),
+    ).with_columns(
+        Debt_Outstanding_EoP_mn = pl.when(pl.col("Period") == 0).then(pl.col(
+                "Debt_Outstanding_EoP_mn"
+        )).otherwise(pl.col("Debt_Outstanding_EoP_mn").shift(1) - pl.col("Amortization_mn")
+    )).with_columns(
+        Debt_Outstanding_BoP_mn = pl.col("Debt_Outstanding_EoP_mn").shift(1),
+    ).to_pandas()
+
+    for period in model["Period"]:
+        if period > 1:
+            model.loc[period, "Interest_Expense_mn"] = model.loc[period, "Debt_Outstanding_BoP_mn"] * assumptions.cost_of_debt
+            model.loc[period, "Amortization_mn"] = min(
+                model.loc[period, "Target_Debt_Service_mn"] - model.loc[period, "Interest_Expense_mn"],
+                model.loc[period, "Debt_Outstanding_BoP_mn"]
+            )
+            model.loc[period, "Debt_Outstanding_EoP_mn"] = model.loc[period, "Debt_Outstanding_BoP_mn"] - model.loc[period, "Amortization_mn"]
+            if period < assumptions.project_lifetime_years:
+                model.loc[period + 1, "Debt_Outstanding_BoP_mn"] = model.loc[period, "Debt_Outstanding_EoP_mn"]
+
+    model = pl.DataFrame(model).with_columns(
+        # Straight line depreciation
+        Depreciation_mn = pl.when(pl.col("Period") > 0).then(assumptions.capital_cost/1000/assumptions.project_lifetime_years).otherwise(0),
+    ).with_columns(
+        Taxable_Income_mn = pl.col("EBITDA_mn") - pl.col("Depreciation_mn") - pl.col("Interest_Expense_mn"),
+    ).with_columns(
+        Tax_Liability_mn = pl.max_horizontal(0, assumptions.tax_rate * pl.col("Taxable_Income_mn"))
+    ).with_columns(
+        Post_Tax_Net_Equity_Cashflow_mn = pl.when(pl.col("Period") == 0).then(-assumptions.capital_cost/1000 * assumptions.equity_pct_of_capital_cost).otherwise(pl.col("EBITDA_mn") - pl.col("Target_Debt_Service_mn") - pl.col("Tax_Liability_mn"))
+    )
+
+    # Calculate Post-Tax Equity IRR
+    post_tax_equity_irr = irr(model["Post_Tax_Net_Equity_Cashflow_mn"].to_numpy())
+    if return_model:
+        return model, post_tax_equity_irr, tariff
+    return post_tax_equity_irr - assumptions.cost_of_equity
+
+def calculate_lcoe(assumptions: SolarPVAssumptions):
+    """The LCOE is the breakeven tariff that makes the project NPV zero"""
+    # Define the objective function
+    objective_function = partial(calculate_cashflow_for_renewable_project, assumptions)
+
+    # Solve for the LCOE
+    LCOE_guess = 30
+    lcoe = fsolve(objective_function, LCOE_guess)[0] + 0.0001
+    return lcoe

notebook.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "%load_ext autoreload\n",
+    "%autoreload 2"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 69,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import polars as pl\n",
+    "from pyxirr import irr, npv\n",
+    "from functools import partial\n",
+    "from scipy.optimize import fsolve"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "capacity_mw=30.0 capacity_factor=0.097 capital_expenditure_per_mw=670000.0 o_m_cost_pct_of_capital_cost=0.02 debt_pct_of_capital_cost=0.871 equity_pct_of_capital_cost=0.129 cost_of_debt=0.04 cost_of_equity=0.12 tax_rate=0.25 project_lifetime_years=20 dcsr=1.3 capital_cost=20100000.0 tax_adjusted_WACC=0.04161 wacc=0.050320000000000004\n"
+     ]
+    }
+   ],
+   "source": [
+    "\n",
+    "from schema import SolarPVAssumptions\n",
+    "# Example usage\n",
+    "assumptions = SolarPVAssumptions(\n",
+    "    capacity_mw=30,\n",
+    "    capital_expenditure_per_mw=670_000,\n",
+    "    o_m_cost_pct_of_capital_cost=0.02,\n",
+    "    capacity_factor=0.097,\n",
+    "    project_lifetime_years=20,\n",
+    "    debt_pct_of_capital_cost=0.871,\n",
+    "    equity_pct_of_capital_cost=0.129,\n",
+    "    cost_of_debt=0.04,\n",
+    "    cost_of_equity=0.12,\n",
+    "    tax_rate=0.25,\n",
+    "    dcsr=1.3\n",
+    ")\n",
+    "\n",
+    "print(assumptions)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "## Pro Forma\n",
+    "\n",
+    "# Starting LCOE\n",
+    "LCOE_guess = 81.44\n",
+    "\n",
+    "def calculate_cashflow(assumptions, LCOE_guess, return_model=False):\n",
+    "    # Create a dataframe, starting with the period\n",
+    "    model = pl.DataFrame(\n",
+    "        {\n",
+    "            \"Period\": [i for i in range(assumptions.project_lifetime_years + 1)],\n",
+    "        }\n",
+    "    )\n",
+    "\n",
+    "    model = model.with_columns(\n",
+    "        Capacity_MW = pl.when(pl.col(\"Period\") > 0).then(assumptions.capacity_mw).otherwise(0),\n",
+    "        Capacity_Factor = pl.when(pl.col(\"Period\") > 0).then(assumptions.capacity_factor).otherwise(0),\n",
+    "        LCOE = pl.when(pl.col(\"Period\") > 0).then(LCOE_guess).otherwise(0),\n",
+    "    ).with_columns(\n",
+    "        Total_Generation_MWh = pl.col(\"Capacity_MW\") * pl.col(\"Capacity_Factor\") * 8760,\n",
+    "    ).with_columns(\n",
+    "        Total_Revenues_mn = pl.col(\"Total_Generation_MWh\") * pl.col(\"LCOE\")/1000,\n",
+    "        O_M_Costs_mn = pl.when(pl.col(\"Period\") > 0).then(assumptions.capital_cost/1000 * assumptions.o_m_cost_pct_of_capital_cost).otherwise(0),\n",
+    "    ).with_columns(\n",
+    "        Total_Operating_Costs_mn = pl.col(\"O_M_Costs_mn\"),\n",
+    "    ).with_columns(\n",
+    "        EBITDA_mn = pl.col(\"Total_Revenues_mn\") - pl.col(\"Total_Operating_Costs_mn\"),\n",
+    "    ).with_columns(\n",
+    "        CFADS_mn = pl.col(\"EBITDA_mn\"),\n",
+    "    ).with_columns(\n",
+    "        Target_Debt_Service_mn = pl.when(pl.col(\"Period\") == 0).then(0).otherwise(pl.col(\"CFADS_mn\")/assumptions.dcsr),\n",
+    "        Debt_Outstanding_EoP_mn = pl.when(pl.col(\"Period\") == 0).then(assumptions.debt_pct_of_capital_cost * assumptions.capital_cost/1000).otherwise(0),\n",
+    "    ).with_columns(\n",
+    "        Interest_Expense_mn = pl.when(pl.col(\"Period\") == 0).then(0).otherwise(pl.col(\"Debt_Outstanding_EoP_mn\").shift(1) * assumptions.cost_of_debt),\n",
+    "    ).with_columns(\n",
+    "        Amortization_mn = pl.when(pl.col(\"Period\") == 0).then(0).otherwise(pl.min_horizontal(pl.col(\"Target_Debt_Service_mn\") - pl.col(\"Interest_Expense_mn\"), pl.col(\"Debt_Outstanding_EoP_mn\").shift(1))),\n",
+    "    ).with_columns(\n",
+    "        Debt_Outstanding_EoP_mn = pl.when(pl.col(\"Period\") == 0).then(pl.col(\n",
+    "                \"Debt_Outstanding_EoP_mn\"\n",
+    "        )).otherwise(pl.col(\"Debt_Outstanding_EoP_mn\").shift(1) - pl.col(\"Amortization_mn\")\n",
+    "    )).with_columns(\n",
+    "        Debt_Outstanding_BoP_mn = pl.col(\"Debt_Outstanding_EoP_mn\").shift(1),\n",
+    "    ).to_pandas()\n",
+    "\n",
+    "    for period in model[\"Period\"]:\n",
+    "        if period > 1:\n",
+    "            model.loc[period, \"Interest_Expense_mn\"] = model.loc[period, \"Debt_Outstanding_BoP_mn\"] * assumptions.cost_of_debt\n",
+    "            model.loc[period, \"Amortization_mn\"] = min(\n",
+    "                model.loc[period, \"Target_Debt_Service_mn\"] - model.loc[period, \"Interest_Expense_mn\"],\n",
+    "                model.loc[period, \"Debt_Outstanding_BoP_mn\"]\n",
+    "            )\n",
+    "            model.loc[period, \"Debt_Outstanding_EoP_mn\"] = model.loc[period, \"Debt_Outstanding_BoP_mn\"] - model.loc[period, \"Amortization_mn\"]\n",
+    "            if period < assumptions.project_lifetime_years:\n",
+    "                model.loc[period + 1, \"Debt_Outstanding_BoP_mn\"] = model.loc[period, \"Debt_Outstanding_EoP_mn\"]\n",
+    "\n",
+    "    model = pl.DataFrame(model).with_columns(\n",
+    "        # Straight line depreciation\n",
+    "        Depreciation_mn = pl.when(pl.col(\"Period\") > 0).then(assumptions.capital_cost/1000/assumptions.project_lifetime_years).otherwise(0),\n",
+    "    ).with_columns(\n",
+    "        Taxable_Income_mn = pl.col(\"EBITDA_mn\") - pl.col(\"Depreciation_mn\") - pl.col(\"Interest_Expense_mn\"),\n",
+    "    ).with_columns(\n",
+    "        Tax_Liability_mn = pl.max_horizontal(0, assumptions.tax_rate * pl.col(\"Taxable_Income_mn\"))\n",
+    "    ).with_columns(\n",
+    "        Post_Tax_Net_Equity_Cashflow_mn = pl.when(pl.col(\"Period\") == 0).then(-assumptions.capital_cost/1000 * assumptions.equity_pct_of_capital_cost).otherwise(pl.col(\"EBITDA_mn\") - pl.col(\"Target_Debt_Service_mn\") - pl.col(\"Tax_Liability_mn\"))\n",
+    "    )\n",
+    "\n",
+    "    # Calculate Post-Tax Equity IRR\n",
+    "    post_tax_equity_irr = irr(model[\"Post_Tax_Net_Equity_Cashflow_mn\"].to_numpy())\n",
+    "    if return_model:\n",
+    "        return model, post_tax_equity_irr\n",
+    "    return post_tax_equity_irr - assumptions.cost_of_equity"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 99,
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(shape: (21, 19)\n",
+       " ┌────────┬────────────┬────────────┬───────────┬───┬───────────┬───────────┬───────────┬───────────┐\n",
+       " │ Period ┆ Capacity_M ┆ Capacity_F ┆ LCOE      ┆ … ┆ Depreciat ┆ Taxable_I ┆ Tax_Liabi ┆ Post_Tax_ │\n",
+       " │ ---    ┆ W          ┆ actor      ┆ ---       ┆   ┆ ion_mn    ┆ ncome_mn  ┆ lity_mn   ┆ Net_Equit │\n",
+       " │ i64    ┆ ---        ┆ ---        ┆ f64       ┆   ┆ ---       ┆ ---       ┆ ---       ┆ y_Cashflo │\n",
+       " │        ┆ f64        ┆ f64        ┆           ┆   ┆ f64       ┆ f64       ┆ f64       ┆ w_m…      │\n",
+       " │        ┆            ┆            ┆           ┆   ┆           ┆           ┆           ┆ ---       │\n",
+       " │        ┆            ┆            ┆           ┆   ┆           ┆           ┆           ┆ f64       │\n",
+       " ╞════════╪════════════╪════════════╪═══════════╪═══╪═══════════╪═══════════╪═══════════╪═══════════╡\n",
+       " │ 0      ┆ 0.0        ┆ 0.0        ┆ 0.0       ┆ … ┆ 0.0       ┆ 0.0       ┆ 0.0       ┆ -2592.9   │\n",
+       " │ 1      ┆ 30.0       ┆ 0.097      ┆ 77.609918 ┆ … ┆ 1005.0    ┆ -128.8830 ┆ 0.0       ┆ 363.78484 │\n",
+       " │        ┆            ┆            ┆           ┆   ┆           ┆ 02        ┆           ┆ 6         │\n",
+       " │ 2      ┆ 30.0       ┆ 0.097      ┆ 77.609918 ┆ … ┆ 1005.0    ┆ -108.3897 ┆ 0.0       ┆ 363.78484 │\n",
+       " │        ┆            ┆            ┆           ┆   ┆           ┆ 16        ┆           ┆ 6         │\n",
+       " │ 3      ┆ 30.0       ┆ 0.097      ┆ 77.609918 ┆ … ┆ 1005.0    ┆ -87.07669 ┆ 0.0       ┆ 363.78484 │\n",
+       " │        ┆            ┆            ┆           ┆   ┆           ┆ 9         ┆           ┆ 6         │\n",
+       " │ 4      ┆ 30.0       ┆ 0.097      ┆ 77.609918 ┆ … ┆ 1005.0    ┆ -64.91116 ┆ 0.0       ┆ 363.78484 │\n",
+       " │        ┆            ┆            ┆           ┆   ┆           ┆           ┆           ┆ 6         │\n",
+       " │ …      ┆ …          ┆ …          ┆ …         ┆ … ┆ …         ┆ …         ┆ …         ┆ …         │\n",
+       " │ 16     ┆ 30.0       ┆ 0.097      ┆ 77.609918 ┆ … ┆ 1005.0    ┆ 281.46610 ┆ 70.366527 ┆ 293.41831 │\n",
+       " │        ┆            ┆            ┆           ┆   ┆           ┆ 8         ┆           ┆ 9         │\n",
+       " │ 17     ┆ 30.0       ┆ 0.097      ┆ 77.609918 ┆ … ┆ 1005.0    ┆ 318.37335 ┆ 79.59334  ┆ 284.19150 │\n",
+       " │        ┆            ┆            ┆           ┆   ┆           ┆ 8         ┆           ┆ 6         │\n",
+       " │ 18     ┆ 30.0       ┆ 0.097      ┆ 77.609918 ┆ … ┆ 1005.0    ┆ 356.75689 ┆ 89.189225 ┆ 274.59562 │\n",
+       " │        ┆            ┆            ┆           ┆   ┆           ┆ 9         ┆           ┆ 1         │\n",
+       " │ 19     ┆ 30.0       ┆ 0.097      ┆ 77.609918 ┆ … ┆ 1005.0    ┆ 396.67578 ┆ 99.168945 ┆ 264.6159  │\n",
+       " │        ┆            ┆            ┆           ┆   ┆           ┆ 1         ┆           ┆           │\n",
+       " │ 20     ┆ 30.0       ┆ 0.097      ┆ 77.609918 ┆ … ┆ 1005.0    ┆ 438.19141 ┆ 109.54785 ┆ 254.23699 │\n",
+       " │        ┆            ┆            ┆           ┆   ┆           ┆ 8         ┆ 5         ┆ 1         │\n",
+       " └────────┴────────────┴────────────┴───────────┴───┴───────────┴───────────┴───────────┴───────────┘,\n",
+       " 0.12000008866075423)"
+      ]
+     },
+     "execution_count": 99,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "breakeven_LCOE = fsolve(partial(calculate_cashflow, assumptions), 44)[0] + 0.0001\n",
+    "calculate_cashflow(assumptions, breakeven_LCOE, return_model=True)\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "renewable-lcoe",
+   "language": "python",
+   "name": "renewable-lcoe"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.11.5"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}

pyproject.toml

@@ -0,0 +1,23 @@
+[project]
+name = "renewable-lcoe-api"
+version = "0.1.0"
+description = "Add your description here"
+readme = "README.md"
+requires-python = ">=3.11"
+dependencies = [
+    "fastapi[standard]>=0.115.5",
+    "ipykernel>=6.29.5",
+    "pandas>=2.2.3",
+    "pip>=24.3.1",
+    "polars>=1.13.1",
+    "pyarrow>=18.0.0",
+    "pydantic>=2.9.2",
+    "pyxirr>=0.10.6",
+    "ruff>=0.7.4",
+    "scipy>=1.14.1",
+]
+
+[dependency-groups]
+dev = [
+    "ipykernel>=6.29.5",
+]

schema.py

@@ -0,0 +1,115 @@
+from typing import Annotated
+from pydantic import BaseModel, Field, computed_field, field_validator, model_validator
+
+
+class SolarPVAssumptions(BaseModel):
+    capacity_mw: Annotated[float, Field(ge=1, le=1000, title="Capacity (MW)")] = 30
+    capacity_factor: Annotated[
+        float,
+        Field(
+            ge=0,
+            le=0.6,
+            title="Capacity factor (%)",
+            description="Capacity factor as a decimal, e.g., 0.2 for 20%",
+        ),
+    ] = 0.10
+    capital_expenditure_per_mw: Annotated[
+        float, Field(ge=1e5, le=1e6, title="Capital expenditure per MW ($/MW)")
+    ] = 670_000
+    o_m_cost_pct_of_capital_cost: Annotated[
+        float,
+        Field(
+            ge=0,
+            le=0.5,
+            title="O&M Cost Percentage (%)",
+            description="O&M cost as a percentage of capital expenditure",
+        ),
+    ] = 0.02
+    debt_pct_of_capital_cost: Annotated[
+        float,
+        Field(
+            ge=0,
+            le=1,
+            title="Debt Percentage (%)",
+            description="Debt as a percentage of capital expenditure",
+        ),
+    ] = 0.8
+    equity_pct_of_capital_cost: Annotated[
+        float,
+        Field(
+            ge=0,
+            le=1,
+            title="Equity Percentage (%)",
+            description="Equity as a percentage of capital expenditure",
+        ),
+    ] = 0.2
+    cost_of_debt: Annotated[
+        float,
+        Field(
+            ge=0,
+            le=0.2,
+            title="Cost of Debt (%)",
+            description="Cost of debt (as a decimal, e.g., 0.05 for 5%)",
+        ),
+    ] = 0.05
+    cost_of_equity: Annotated[
+        float,
+        Field(
+            ge=0,
+            le=0.3,
+            title="Cost of Equity (%)",
+            description="Cost of equity (as a decimal, e.g., 0.1 for 10%)",
+        ),
+    ] = 0.10
+    tax_rate: Annotated[
+        float,
+        Field(
+            ge=0,
+            le=0.5,
+            title="Tax Rate (%)",
+            description="Tax rate (as a decimal, e.g., 0.3 for 30%)",
+        ),
+    ] = 0.30
+    project_lifetime_years: Annotated[
+        int,
+        Field(
+            ge=5,
+            le=50,
+            title="Project Lifetime (years)",
+            description="Project lifetime in years",
+        ),
+    ] = 25
+    dcsr: Annotated[
+        float,
+        Field(
+            ge=1,
+            le=2,
+            title="Debt Service Coverage Ratio",
+            description="Debt service coverage ratio",
+        ),
+    ] = 1.3
+
+    @model_validator(mode="after")
+    def check_sum_of_parts(self):
+        if self.debt_pct_of_capital_cost + self.equity_pct_of_capital_cost != 1:
+            raise ValueError("Debt and equity percentages must sum to 1")
+        return self
+
+    @computed_field
+    @property
+    def capital_cost(self) -> Annotated[float,
+                                        Field(title="Capital Cost ($)", description="Total capital cost")]:
+        return self.capacity_mw * self.capital_expenditure_per_mw
+
+    @computed_field
+    @property
+    def tax_adjusted_WACC(self) -> Annotated[float,
+                                             Field(title="Tax Adjusted WACC (%)",
+                                                   description="Tax adjusted weighted average cost of capital")]:
+        return (self.debt_pct_of_capital_cost * self.cost_of_debt * (1 - self.tax_rate) +
+                self.equity_pct_of_capital_cost * self.cost_of_equity)
+
+    @computed_field
+    @property
+    def wacc(self) -> Annotated[float, Field(title="WACC (%)", description="Weighted average cost of capital")]:
+        return self.debt_pct_of_capital_cost * self.cost_of_debt + self.equity_pct_of_capital_cost * self.cost_of_equity