Arbeitsdefinitionen

Zukunftsquartier

Absolute Endenergiebilanz

$ EE = f_{prod}A_{plot} - f_{cons}A_{GCF}$

$f_{prod}: $ Specific power production per Plot Area $[kWh/m²_{Plot}]$

$f_{cons}: $ Specific power consumption per Conditioned Gross Floor Area $[kWh/m²_{GCF}]$

$ FSI: $ Floor Space index $= \frac{A_{GCF}}{A_{plot}}$

Division of first formula by $A_{GCF}$ makes it Specific, and yields the FSI:

$ EE/A_{GCF} = (f_{prod}A_{plot} - f_{cons}A_{GCF})/A_{GCF}$

$ EE/A_{GCF} = f_{prod}\frac{A_{plot}}{A_{GCF}} - f_{cons}$

with $\frac{A_{plot}}{A_{GCF}} = \frac{1}{FSI}$

$ EE(FSI) = \frac{f_{prod}}{FSI} - f_{cons}$

$ PE(FSI) = (\frac{f_{prod}}{FSI} - f_{cons}) * f_{PE}$

import numpy as np

GFZ = np.linspace(0.1, 7, 70) #min, max, steps
A = 37.
dy = 9.2
dx = 0.085
EUI=38.34
NGFtoBGF=0.8
PE_strom = 1.63 #kWh PE / kWh EE

def target(GFZ, A=A,dy=dy,dx=dx,EUI=EUI,fPE=PE_strom, NGFtoBGF=NGFtoBGF):
    return (( dy + A/(dx + GFZ) - EUI )* fPE) * NGFtoBGF

target(GFZ)

import pandas as pd

t = pd.DataFrame({"PE Target":target(GFZ)}, index=GFZ)

from matplotlib.figure import Figure

%matplotlib inline

df = pd.DataFrame({"PE Target":target(GFZ),
                           "":np.zeros(len(GFZ))}, index=GFZ)

def mpl_plot(df, rng):
    fig = Figure()
    ax = fig.add_subplot()

    df.plot(ax=ax, color=["red","green","darkred"])
    ax.set(xlabel="FSI", ylabel="PE-Target $[kWh/m²_{GCF}]$")
    ax.grid(color='grey', linestyle='-', linewidth=0.5)
    ax.set_ylim(-50,200)
    ax.set_xlim(0,rng[-1])
    return fig

mpl_plot(df, GFZ)

def wraps(GFZ=GFZ, A=A, dx=dx, dy=dy, EUI=EUI, view_fn=mpl_plot):
    t_orig = target(GFZ)
    t = target(GFZ, A=A, dx=dx, dy=dy, EUI=EUI)
    df = pd.DataFrame({"PE Target":t_orig,
                       "Dynamic":t,
                           "":np.zeros(len(GFZ))}, index=GFZ)
    return view_fn(df, GFZ)

import panel as pn

dashboard = pn.interact(wraps)
text = """<br>\n# Primary Energy\n
Current formula:\n"""
dasboard = pn.Column(text, dashboard)
# formula = f"$ PE(FSI) = (\frac{f_{prod}}{FSI} - f_{cons}) * f_{PE}$"""

dashboard.show()

Launching server at http://localhost:60201





<bokeh.server.server.Server at 0x1f5e22ed3c8>

Aspern Klimafit

Andere Ansätze

UAP Richt- und Zielwerte

Richt- und Zielwerte des Projekts UrbanAreasParameters für Wohn-, Büro- und Schulgebäude (Mair am Tinkhof, 2017)

!jupyter nbconvert --to markdown index.ipynb

[NbConvertApp] Converting notebook index.ipynb to markdown
[NbConvertApp] Writing 3517 bytes to index.md

!jupyter nbconvert index.ipynb –to slides –reveal-prefix slides.js