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Weitere Berechnungen

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Moritz Utcke
2025-01-10 10:30:04 +07:00
parent 9426e17af0
commit f16fb41db0
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src/lib/Berechnungen/BedarfsausweisWohnen/funktionMonatlicherBelastungsgrad.ts
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@@ -1,154 +1,105 @@
// Funktion zur Berechnung des monatlichen Belastungsgrades aus Tabelle 9 EFH (Januar, Zeitkonstante 90)
import { nevillePolynomialInterpolation, lagrangeInterpolation } from "js-interpolate";
import { nevillePolynomialInterpolation } from "js-interpolate";
// Funktion zur Berechnung des monatlichen Belastungsgrades aus Tabelle 9 EFH (Zeitkonstante 90,130)
type MonthData = {
month: string;
values: number[];
};
const datasetZeitkonstante90: MonthData[] = [
{
month: "Januar",
values: [0.562, 0.559, 0.555, 0.548, 0.541, 0.538, 0.536, 0.535, 0.535],
},
{
month: "Februar",
values: [0.536, 0.532, 0.529, 0.522, 0.515, 0.512, 0.51, 0.51, 0.509],
},
{
month: "März",
values: [0.453, 0.45, 0.447, 0.441, 0.436, 0.433, 0.431, 0.431, 0.43],
},
{
month: "April",
values: [0.32, 0.318, 0.316, 0.311, 0.307, 0.306, 0.305, 0.304, 0.304],
},
{
month: "Mai",
values: [0.175, 0.173, 0.172, 0.17, 0.168, 0.167, 0.166, 0.166, 0.166],
},
{
month: "Juni",
values: [0.098, 0.097, 0.096, 0.095, 0.094, 0.093, 0.093, 0.093, 0.093],
},
{
month: "Juli",
values: [0.03, 0.029, 0.029, 0.029, 0.028, 0.028, 0.028, 0.028, 0.028],
},
{
month: "August",
values: [0.041, 0.041, 0.041, 0.04, 0.04, 0.04, 0.039, 0.039, 0.039],
},
{
month: "September",
values: [0.169, 0.168, 0.167, 0.164, 0.162, 0.161, 0.161, 0.161, 0.16],
},
{
month: "Oktober",
values: [0.311, 0.309, 0.307, 0.303, 0.299, 0.297, 0.296, 0.296, 0.295],
},
{
month: "November",
values: [0.471, 0.467, 0.465, 0.459, 0.453, 0.45, 0.448, 0.448, 0.447],
},
{
month: "Dezember",
values: [0.565, 0.562, 0.558, 0.551, 0.544, 0.54, 0.539, 0.538, 0.537],
},
];
const datasetZeitkonstante130: MonthData[] = [
{
month: "Januar",
values: [0.567, 0.563, 0.56, 0.553, 0.545, 0.542, 0.54, 0.539, 0.539],
},
{
month: "Februar",
values: [0.54, 0.537, 0.533, 0.526, 0.52, 0.516, 0.515, 0.514, 0.513],
},
{
month: "März",
values: [0.457, 0.454, 0.451, 0.445, 0.439, 0.435, 0.435, 0.434, 0.434],
},
{
month: "April",
values: [0.322, 0.32, 0.318, 0.314, 0.31, 0.308, 0.307, 0.307, 0.306],
},
{
month: "Mai",
values: [0.176, 0.175, 0.174, 0.172, 0.169, 0.168, 0.168, 0.168, 0.167],
},
{
month: "Juni",
values: [0.098, 0.097, 0.096, 0.095, 0.094, 0.094, 0.094, 0.094, 0.094],
},
{
month: "Juli",
values: [0.03, 0.03, 0.029, 0.029, 0.028, 0.028, 0.028, 0.028, 0.028],
},
{
month: "August",
values: [0.042, 0.041, 0.041, 0.04, 0.04, 0.04, 0.04, 0.04, 0.04],
},
{
month: "September",
values: [0.17, 0.169, 0.168, 0.166, 0.164, 0.163, 0.162, 0.162, 0.162],
},
{
month: "Oktober",
values: [0.313, 0.311, 0.309, 0.305, 0.301, 0.3, 0.299, 0.298, 0.298],
},
{
month: "November",
values: [0.474, 0.471, 0.469, 0.462, 0.456, 0.454, 0.453, 0.451, 0.451],
},
{
month: "Dezember",
values: [0.57, 0.566, 0.563, 0.555, 0.548, 0.545, 0.543, 0.542, 0.542],
},
];
const dataset = {
Januar: {
50: [ 0.557, 0.554, 0.55, 0.543, 0.536, 0.533, 0.531, 0.53, 0.53 ],
90: [ 0.562, 0.559, 0.555, 0.548, 0.541, 0.538, 0.536, 0.535, 0.535 ],
130: [ 0.567, 0.563, 0.56, 0.553, 0.545, 0.542, 0.54, 0.539, 0.539 ],
},
Februar: {
50: [ 0.531, 0.527, 0.524, 0.517, 0.51, 0.507, 0.505, 0.504, 0.505 ],
90: [ 0.536, 0.532, 0.529, 0.522, 0.515, 0.512, 0.51, 0.51, 0.509 ],
130: [ 0.54, 0.537, 0.533, 0.526, 0.52, 0.516, 0.515, 0.514, 0.513 ],
},
"März": {
50: [ 0.448, 0.445, 0.443, 0.437, 0.431, 0.427, 0.427, 0.426, 0.426 ],
90: [ 0.453, 0.45, 0.447, 0.441, 0.436, 0.433, 0.431, 0.431, 0.43 ],
130: [ 0.457, 0.454, 0.451, 0.445, 0.439, 0.435, 0.435, 0.434, 0.434 ],
},
April: {
50: [ 0.317, 0.314, 0.313, 0.308, 0.305, 0.303, 0.302, 0.301, 0.301 ],
90: [ 0.32, 0.318, 0.316, 0.311, 0.307, 0.306, 0.305, 0.304, 0.304 ],
130: [ 0.322, 0.32, 0.318, 0.314, 0.31, 0.308, 0.307, 0.307, 0.306 ],
},
Mai: {
50: [ 0.173, 0.172, 0.171, 0.169, 0.166, 0.165, 0.165, 0.165, 0.164 ],
90: [ 0.175, 0.173, 0.172, 0.17, 0.168, 0.167, 0.166, 0.166, 0.166 ],
130: [ 0.176, 0.175, 0.174, 0.172, 0.169, 0.168, 0.168, 0.168, 0.167 ],
},
Juni: {
50: [ 0.097, 0.096, 0.096, 0.094, 0.093, 0.092, 0.092, 0.092, 0.092 ],
90: [ 0.098, 0.097, 0.096, 0.095, 0.094, 0.093, 0.093, 0.093, 0.093 ],
130: [ 0.098, 0.097, 0.096, 0.095, 0.094, 0.094, 0.094, 0.094, 0.094 ],
},
Juli: {
50: [ 0.029, 0.029, 0.029, 0.029, 0.028, 0.028, 0.028, 0.028, 0.028 ],
90: [ 0.03, 0.029, 0.029, 0.029, 0.028, 0.028, 0.028, 0.028, 0.028 ],
130: [ 0.03, 0.03, 0.029, 0.029, 0.028, 0.028, 0.028, 0.028, 0.028 ],
},
August: {
50: [ 0.041, 0.041, 0.041, 0.04, 0.04, 0.04, 0.039, 0.039, 0.039 ],
90: [ 0.041, 0.041, 0.041, 0.04, 0.04, 0.04, 0.039, 0.039, 0.039 ],
130: [ 0.042, 0.041, 0.041, 0.04, 0.04, 0.04, 0.04, 0.04, 0.04 ],
},
September: {
50: [ 0.167, 0.166, 0.165, 0.163, 0.161, 0.16, 0.159, 0.159, 0.159 ],
90: [ 0.169, 0.168, 0.167, 0.164, 0.162, 0.161, 0.161, 0.161, 0.16 ],
130: [ 0.17, 0.169, 0.168, 0.166, 0.164, 0.163, 0.162, 0.162, 0.162 ],
},
Oktober: {
50: [ 0.308, 0.306, 0.304, 0.3, 0.296, 0.294, 0.293, 0.293, 0.293 ],
90: [ 0.311, 0.309, 0.307, 0.303, 0.299, 0.297, 0.296, 0.296, 0.295 ],
130: [ 0.313, 0.311, 0.309, 0.305, 0.301, 0.3, 0.299, 0.298, 0.298 ],
},
November: {
50: [ 0.466, 0.463, 0.46, 0.454, 0.448, 0.445, 0.444, 0.443, 0.443 ],
90: [ 0.471, 0.467, 0.465, 0.459, 0.453, 0.45, 0.448, 0.448, 0.447 ],
130: [ 0.474, 0.471, 0.469, 0.462, 0.456, 0.454, 0.453, 0.451, 0.451 ],
},
Dezember: {
50: [ 0.56, 0.557, 0.553, 0.546, 0.539, 0.536, 0.534, 0.533, 0.533 ],
90: [ 0.565, 0.562, 0.558, 0.551, 0.544, 0.54, 0.539, 0.538, 0.537 ],
130: [ 0.57, 0.566, 0.563, 0.555, 0.548, 0.545, 0.543, 0.542, 0.542 ],
},
}
// Für "Ohne Teilbeheizung" habe ich hier einfach 0 eingesetzt:
const HeizLast = [0, 5, 10, 25, 50, 75, 100, 125, 150];
// Um über die beiden Tabellen zu interpolieren können wir einfach zuerst über
// jede einzeln interpolieren und dann zwischen den Tabellen interpolieren.
// Falls wir also den Wert an Stelle Heizlast: 120, Zeitkonstante 100, Monat:
// Januar haben wollen:
function crossInterpolate(heizlast: number, zeitkonstane: number, monat: keyof typeof dataset) {
const data = dataset[monat]
const interpolations: number[] = []
// Um über die beiden Tabellen zu interpolieren können wir einfach zuerst über jede einzeln interpolieren und dann zwischen den Tabellen interpolieren.
// Falls wir also den Wert an Stelle Heizlast: 120, Zeitkonstante 100, Monat: Januar haben wollen:
for (const key in data) {
const values = data[key as unknown as keyof typeof data]
function crossInterpolate(heizlast: number, zeitkonstane: number, monat: string) {
const interpolatedValuesZeitkonstante90 = datasetZeitkonstante90.filter(data => data.month === monat).map((data) => {
const interpolate = nevillePolynomialInterpolation(
data.values.map((value, i) => ({ x: HeizLast[i], y: value })),
data.values.length
);
return interpolate(heizlast)
});
const interpolatedValuesZeitkonstante130 = datasetZeitkonstante130.filter(data => data.month === monat).map((data) => {
const interpolate = nevillePolynomialInterpolation(
data.values.map((value, i) => ({ x: HeizLast[i], y: value })),
data.values.length
);
return interpolate(heizlast)
});
values.map((value, i) => ({ x: HeizLast[i], y: value })),
values.length
)
interpolations.push(interpolate(heizlast))
}
const interpolate = nevillePolynomialInterpolation(
[{
x: 90,
y: interpolatedValuesZeitkonstante90
}, {
x: 130,
y: interpolatedValuesZeitkonstante130
}],
2
interpolations.map((interpolation, i) => {
return {
x: Object.keys(data)[i],
y: interpolation
}
}),
interpolations.length
)
return interpolate(zeitkonstane)
}
console.log(crossInterpolate(0, 100, "Januar"));
console.log(crossInterpolate(120, 100, "Januar"));