''

pvlib · eccoope · Mar 6, 2023 · Mar 6, 2023 · Mar 6, 2023 · Mar 7, 2023
commit 49fd4e8a47e9322ff0295fb166bfdab5ce1765ed
diff --git a/pvlib/financial.py b/pvlib/financial.py
@@ -0,0 +1,116 @@
+import numpy as np
+
+def lcoe(production=None, cap_cost=None, fixed_om=None):
+        """
+        Levelized cost of electricity as described on pp.43 and 47-48 by [1]   
+        Parameters
+        ----------
+        production : np.array, or pd.Series, default None
+            Annual production [kWh/kW installed]
+        cap_cost : np.array, or pd.Series, default None
+            Initial and annual payments on capital costs [$/kW installed]
+        fixed_om : np.array, or pd.Series, default None
+            Annual payments on operations and maintenance costs [$/kW installed]
+
+        Returns
+        ----------
+        LCOE [cents/kWh]
+
+        References
+        ----------
+        .. [1] W. Short, D. J. Packey, and T. Holt, "A Manual for the Economic Evaluation of Energy Efficiency and Renewable Energy Technologies", NREL/TP-462-5173, 1995.
+        """        
+        if len(production)!=len(cap_cost) or len(cap_cost)!=len(fixed_om):
+            raise ValueError("Unequal input array lengths")      
+        cost = cap_cost + fixed_om            
+        return np.round(np.nansum(cost)*100/np.nansum(production),2)
+
+def crf(rate, n_years):
+    """
+    Capital recovery factor as described on pp. 23 by [1]    
+    Parameters
+    ----------
+    rate : float
+        Rate at which CRF is calculated
+    n_years: int
+        Number of years over which CRF is calculated
+
+    Returns
+    ----------
+    crf : float
+        Capital recovery factor
+    References
+    ----------
+    .. [1] W. Short, D. J. Packey, and T. Holt, "A Manual for the Economic Evaluation of Energy Efficiency and Renewable Energy Technologies", NREL/TP-462-5173, 1995.
+    """ 
+    return np.round((rate*(1+rate)**n_years)/((1+rate)**n_years-1),8)
+
+def nominal_to_real(nominal, rate):
+    """
+    Inflation-adjusted rate described on pp. 6 by [1]
+    Parameters
+    ----------
+    nominal : float
+        Nominal rate (does not include adjustments for inflation)
+    rate : float
+        Inflation rate
+
+    Returns
+    ----------
+    Real rate (includes adjustments for inflation)
+
+    References
+    ----------
+    .. [1] W. Short, D. J. Packey, and T. Holt, "A Manual for the Economic Evaluation of Energy Efficiency and Renewable Energy Technologies", NREL/TP-462-5173, 1995.
+    """ 
+    return np.round((1+nominal)/(1+rate)-1, 8)
+
+def real_to_nominal(real, rate):
+    """
+    Rate without adjusting for inflation as described on pp. 6 by [1]
+    Parameters
+    ----------
+    real : float
+        Real rate (includes adjustments for inflation)
+    rate : float
+        Inflation rate
+
+    Returns
+    ----------
+    Nominal rate (does not include adjustments for inflation)
+
+    References
+    ----------
+    .. [1] W. Short, D. J. Packey, and T. Holt, "A Manual for the Economic Evaluation of Energy Efficiency and Renewable Energy Technologies", NREL/TP-462-5173, 1995.
+    """ 
+
+    return np.round((real+1)*(1+rate)-1, 8)
+
+def wacc(loan_frac, rroi, rint, inflation_rate, tax_rate):
+    """        
+    Parameters
+    ----------
+    loan_frac : float
+        Fraction of capital cost paid for with a loan
+    rroi : float
+        Real internal rate of return on investment
+    rint : float
+        Real interest rate
+    inflation_rate : float
+        Effective inflation rate
+    tax_rate : float
+        Tax rate
+
+    Returns
+    ----------
+    wacc : float
+        Weighted average cost of capital
+
+    References
+    ----------
+    .. [1] S. Blumsack, "Weighted Average Cost of Capital", The Pennsylvania State University, Available: http://www.e-education.psu.edu/eme801/node/585
+    """ 
+    numerator = (1 + ((1 - loan_frac)*((1 + rroi)*(1 + inflation_rate)-1))
+                + loan_frac*((1 + rint)*(1 + inflation_rate) - 1)*(1 - tax_rate))
+    denominator = 1 + inflation_rate
+    return np.round(numerator/denominator -1, 8)
diff --git a/pvlib/tests/test_financial.py b/pvlib/tests/test_financial.py
@@ -0,0 +1,77 @@
+import pandas as pd
+import numpy as np
+import sys
+from pvlib import financial
+from numpy.testing import assert_allclose
+
+def test_lcoe_series():
+    n, cf = 20, 0.5
+    production = pd.Series(data=[cf*8670 for j in range(n)])
+    capex, loan_frac, my_crf, debt_tenor = 1000, 0.5, 0.05, n
+    cap_cost = pd.Series(data=[capex*loan_frac*my_crf for i in range(debt_tenor)] + [0 for j in range(debt_tenor, n)])
+    base_om = 25
+    fixed_om = pd.Series(data=[base_om for j in range(n)])
+
+    expected = 1.15
+    out = financial.lcoe(production=production, cap_cost=cap_cost, fixed_om=fixed_om)
+
+    assert_allclose(expected, out)
+
+def test_lcoe_arrays():
+    n, cf = 20, 0.5
+    production = np.full(n, cf*8670)
+    capex, loan_frac, my_crf, debt_tenor = 1000, 0.5, 0.05, n
+    cap_cost = np.array([capex*loan_frac*my_crf for i in range(debt_tenor)] + [0 for j in range(debt_tenor, n)])
+    base_om = 25
+    fixed_om = np.full(n, base_om)
+    expected = 1.15
+
+    out = financial.lcoe(production=production, cap_cost=cap_cost, fixed_om=fixed_om)
+    assert_allclose(expected, out)
+
+def test_lcoe_nans():
+    n, cf = 20, 0.5
+    production = np.full(n, cf*8670)
+    capex, loan_frac, my_crf, debt_tenor = 1000, 0.5, 0.05, n
+    cap_cost = np.array([capex*loan_frac*my_crf for i in range(debt_tenor)] + [0 for j in range(debt_tenor, n)])
+    base_om = 25.
+    fixed_om = np.full(n, base_om)
+    cap_cost[1] = np.nan
+    fixed_om[2] = np.nan
+    production[3] = np.nan
+    expected = 1.09
+
+    out = financial.lcoe(production=production, cap_cost=cap_cost, fixed_om=fixed_om)
+    assert_allclose(expected, out)
+
+def test_crf():
+    rate, n = 0.05, 20
+    expected = 0.08024259
+
+    out = financial.crf(rate, n)
+    assert_allclose(expected, out)
+
+def test_nominal_to_real():
+    nominal, rate = 0.04, 0.025
+    expected = 0.01463415
+
+    out = financial.nominal_to_real(nominal, rate)
+    assert_allclose(expected, out)
+
+def test_real_to_nominal():
+    real, rate = 0.04, 0.025
+    expected = 0.066
+
+    out = financial.real_to_nominal(real, rate)
+    assert_allclose(expected, out)
+
+def test_wacc():
+    loan_frac = 0.5
+    rroi = 0.12
+    rint = 0.04
+    inflation_rate = 0.025
+    tax_rate = 0.28
+    expected = 0.07098537
+
+    out = financial.wacc(loan_frac, rroi, rint, inflation_rate, tax_rate)
+    assert_allclose(expected, out)