pvlib-rust 0.1.6

A Rust port of pvlib-python: solar energy modeling toolkit
Documentation 
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139

/// Spectral Mismatch Modifier (SMM)
/// 
/// Applies a polynomial modifier based on Air Mass to account for spectral variations
/// in module efficiency compared to STC (AM 1.5).
/// 
/// # Arguments
/// * `airmass_absolute` - The absolute air mass.
/// * `coefficients` - 6 empirical polynomial coefficients [C0, C1, C2, C3, C4, C5].
/// 
/// # Returns
/// A unitless modifier to multiply against DC power or current.
#[inline]
pub fn spectral_mismatch_modifier(airmass_absolute: f64, coefficients: [f64; 6]) -> f64 {
    let x = airmass_absolute.max(1.0);
    
    let ans = coefficients[0]
        + coefficients[1] * x
        + coefficients[2] * x.powi(2)
        + coefficients[3] * x.powi(3)
        + coefficients[4] * x.powi(4)
        + coefficients[5] * x.powi(5);
        
    ans.max(0.0)
}

/// First Solar empirical spectral mismatch modifier.
/// 
/// Evaluates the impact of precipitable water and airmass on CdTe and generic silicon spectrums.
/// 
/// # References
/// Lee, M. et al., 2018. "A new empirical model for spectral correction of PV performance."
#[inline]
pub fn first_solar_spectral_correction(precipitable_water: f64, airmass_absolute: f64, coefficients: [f64; 6]) -> f64 {
    let pw = precipitable_water;
    let am = airmass_absolute;
    let m = coefficients[0] 
          + coefficients[1]*am 
          + coefficients[2]*pw 
          + coefficients[3]*am.sqrt()
          + coefficients[4]*pw.sqrt()
          + coefficients[5]*am/pw.sqrt();
          
    m.max(0.0)
}

/// SAPM spectral loss factor.
///
/// Fourth-order polynomial of absolute airmass: f1 = A0 + A1*AM + A2*AM^2 + A3*AM^3 + A4*AM^4.
///
/// # Arguments
/// * `airmass_absolute` - Absolute airmass. NaN values result in 0.
/// * `coefficients` - Array of 5 coefficients [A0, A1, A2, A3, A4].
///
/// # Returns
/// Spectral mismatch factor (unitless, non-negative).
#[inline]
pub fn spectral_factor_sapm(airmass_absolute: f64, coefficients: [f64; 5]) -> f64 {
    if airmass_absolute.is_nan() {
        return 0.0;
    }
    let am = airmass_absolute;
    let f1 = coefficients[0]
        + coefficients[1] * am
        + coefficients[2] * am.powi(2)
        + coefficients[3] * am.powi(3)
        + coefficients[4] * am.powi(4);
    f1.max(0.0)
}

/// Caballero (2018) spectral mismatch factor.
///
/// Estimates spectral modifier from airmass, AOD at 500nm, and precipitable water.
///
/// # Arguments
/// * `precipitable_water` - Atmospheric precipitable water in cm.
/// * `airmass_absolute` - Absolute airmass.
/// * `aod500` - Aerosol optical depth at 500 nm.
/// * `coefficients` - Array of 12 coefficients from Caballero (2018).
///
/// # Returns
/// Spectral mismatch modifier (unitless).
#[inline]
pub fn spectral_factor_caballero(
    precipitable_water: f64,
    airmass_absolute: f64,
    aod500: f64,
    coefficients: [f64; 12],
) -> f64 {
    let ama = airmass_absolute;
    let aod500_ref = 0.084;
    let pw_ref = 1.4164;

    let c = coefficients;

    // f_AM: 4th order polynomial in airmass
    let f_am = c[0] + c[1] * ama + c[2] * ama.powi(2) + c[3] * ama.powi(3) + c[4] * ama.powi(4);

    // f_AOD: Eq 6 with Table 1 selectors (c[10], c[11])
    let f_aod = (aod500 - aod500_ref)
        * (c[5] + c[10] * c[6] * ama + c[11] * c[6] * ama.ln() + c[7] * ama.powi(2));

    // f_PW: Eq 7 with Table 1
    let f_pw = (precipitable_water - pw_ref) * (c[8] + c[9] * ama.ln());

    f_am + f_aod + f_pw
}

/// Built-in Caballero coefficients for common module types.
#[inline]
pub fn caballero_coefficients(module_type: &str) -> Option<[f64; 12]> {
    match module_type {
        "cdte" => Some([
            1.0044, 0.0095, -0.0037, 0.0002, 0.0000, -0.0046, -0.0182, 0.0, 0.0095, 0.0068,
            0.0, 1.0,
        ]),
        "monosi" => Some([
            0.9706, 0.0377, -0.0123, 0.0025, -0.0002, 0.0159, -0.0165, 0.0, -0.0016, -0.0027,
            1.0, 0.0,
        ]),
        "multisi" => Some([
            0.9836, 0.0254, -0.0085, 0.0016, -0.0001, 0.0094, -0.0132, 0.0, -0.0002, -0.0011,
            1.0, 0.0,
        ]),
        "cigs" => Some([
            0.9801, 0.0283, -0.0092, 0.0019, -0.0001, 0.0117, -0.0126, 0.0, -0.0011, -0.0019,
            1.0, 0.0,
        ]),
        "asi" => Some([
            1.1060, -0.0848, 0.0302, -0.0076, 0.0006, -0.1283, 0.0986, -0.0254, 0.0156, 0.0146,
            1.0, 0.0,
        ]),
        "perovskite" => Some([
            1.0637, -0.0491, 0.0180, -0.0047, 0.0004, -0.0773, 0.0583, -0.0159, 0.01251,
            0.0109, 1.0, 0.0,
        ]),
        _ => None,
    }
}