1. Methodology
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Constructing a synthetic city for estimating spatially disaggregated heat demand

  1. M. Esteban Muñoz H.  Is a corresponding author
  2. Ivan Dochev  Is a corresponding author
  3. Hannes Seller  Is a corresponding author
  4. Irene Peters  Is a corresponding author
  1. Technical Urban Infrastructure Systems Group, HafenCity University, Germany
Research article
Volume 9(3) Winter 2016
Cite this article as: M. Esteban Muñoz H., I. Dochev, H. Seller, I. Peters; 2016; Constructing a synthetic city for estimating spatially disaggregated heat demand; International Journal of Microsimulation; 9(3); 66-88. doi: 10.34196/ijm.00143
4 figures and 4 tables

Figures

Figure 1
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(a) Distribution of PTAE and (b) difference between estimated and simulated population.
Figure 2
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Mean heating consumption per dwelling unit.
Figure 3
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Simulated heat demand for Germany at a NUTS-3 level as per capita heat demand in kWh/cap.
Figure 4
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Simulated heat demand for selected regions of Germany.

Tables

Table 1

Used benchmarks from the 2011 Census and corresponding micro census attributes.

MC Code* Census Code Unit** Description
EF1 / / Federal State (NUTS 2)
EF952 / Person Weight
EF44 ALTER_KURZ Person Age (five classes of years)
EF49 FAMSTND_AUSF Person Marital status (in detail)
EF46 GESCHLECHT Person Sex
EF20 HHGROESS_KLASS Person Size of private household
EF368 STAATSANGE_KURZ Person Citizenship
EF492 WOHNFLAECHE_20S Dwelling Floor area of the dwelling (20m2 intervals)
EF494 BAUJAHR_MZ Building Year of construction (microcensus classes)
EF635 ZAHLWOHNGN_HHG Building Number of dwellings in a building
  1. *

    Micro Census Code

  2. **

    Refers only to Census

Table 2

IWU-de building typology matrix for Germany.

<1859 1860–1918 1919–1948 1949–1957 1958–1968 1969–1978 1979–1983 1984–1994 1995–2001 2002–2009
EFHa 183 180 164 181 146 155 118 132 110 88
RH 153 137 156 106 127 127 98 78 86
KMH 190 143 168 156 129 134 118 122 92 79
GMH 127 144 142 131 117
HH 114 113

  1. source: (Loga et al., 2011) (a) Speci..c Heat demand (spez. Wärmebedarfskennzahl) [kWh/m2a] (EFH) Single family house “Einfamilienhaus”; (RH) Terrace house “Reihenhaus”; (KMH) Apartment house “Mehrfamilienhaus”; (GMH) Large apartment house “Großes Mehrfamilienhaus”; (HH) High-rise “Hochhaus”;

Table 3

Categories of benchmarks from the 2011 Census and categories of the micro census 2010.

MC Code [S] Code [B] Categories
EF44 0–99 (integers)
ALTER_01JS* (1) Under 18, (2) 18–29, (3) 30–49, (4) 50–64, (5) 65 and over,
S1=∑i=017Si;S2=∑i=1829Si;S3=∑i=3049Si;S4=∑i=5064Si;S5=∑i=65nSi
EF49 (1) Single, (2) Married, (3) Widowed, (4) Divorced, (5) Party to a civil union, (6) Civil partner deceased, (7) Civil union annulled
FAMSTND_AUSF (1) Single, (2) Married, (3) Widowed, (4) Divorced, (5) Party to a civil union, (6) Civil partner deceased, (7) Civil union annulled, (8) No data
B′i=Bi+1 if rand()<Bi÷∑i=17Bi ∀i=1…7 until ∑i=18Bi=∑i=17B′i
EF46 (1)Male, (2) Female
GESCHLECHT (1)Male, (2) Female
EF20 1–62 (integers)
HHGROESS_KLASS (1) 1 person, (2) 2 persons, (3) 3 persons, (4) 4 persons, (5) 5 persons, (6) 6 or more people
S′6=∑i=662Si
EF368 (1) Only German, (2) German and a second citizenship, (3) Abroad
STAATSANGE_KURZ (1) Germany, (2) Abroad
S′1=S1+S2; S′2=S3
EF492 (-1/-5) not applicable
WOHNFLAECHE_20S (1) Under 40, (2) 40–59, (3) 60–79, (4) 80–99, (5) 100–119, (6) 120–139, (7) 140–159, (8) 160–179, (9) 180–199, (10) 200 and more
EF494 (1) Pre–1919, (2) 1919–1948, (3) 1949–1978, (4) 1979–1986, (5) 1987–1990, (6) 1991–2000, (7) 2001–2004, (8) 2005–2008, (9) 2009 and later, (99) no response, (-1/-5) not applicable
BAUJAHR_MZ (1) Pre–1919, (2) 1919–1948, (3) 1949–1978, (4) 1979–1986, (5) 1987–1990, (6) 1991–1995, (7) 1996–2000, (8) 2001–2004, (9) 2005–2008, (10) 2009 and later
B′6=B6+B7
EF635 (1) 1 dwelling, (2) 2 dwellings, (3) 3 dwellings, (4) 4 dwellings, (5) 5 dwellings, (6) 6 dwellings, (7) 7–12 dwellings, (8) 13–20, (9) 21 or more dwellings, (-1/-5) not applicable
ZAHLWOHNGN_HHG (1) 1 dwelling, (2) 2 dwellings, (3) 3—6 dwellings, (4) 7—12 dwellings, (5) 13 or more dwellings
S′3=S3+S4+S5+S6S′4=S7S′5=S8+S9
  1. *

    See Table 1 for a description of the code names

  2. **

    Sum is not equal to total population, an extra category is added to match the total population

Table 4

Defined rules to classify individuals into building typologies.

BJA # DU SQM BTYP
bja = 1 du = 1 sqm < 600 Btyp03
bja = 1 du > 1 sqm < 600 Btyp04
bja = 1 du > 1 4000 < sqm > 600 Btyp05
bja = 1 du > 1 10000 < sqm < 4000 Btyp06
bja = 2 du = 1 sqm < 600 Btyp07
bja = 2 du > 1 sqm < 600 Btyp08
bja = 2 du > 1 4000 < sqm > 600 Btyp09
bja = 2 du > 1 10000 < sqm < 4000 Btyp10
bja = 3 du = 1 sqm < 600 Btyp15
bja = 3 du > 1 sqm < 600 Btyp16
bja = 3 du > 1 4000 < sqm > 600 Btyp17
bja = 3 du > 1 10000 < sqm < 4000 Btyp18
bja = 3 du > 1 sqm > 10000 Btyp19
bja = 4 du = 1 sqm < 600 Btyp25
bja = 4 du > 1 sqm < 600 Btyp26
bja = 4 du > 1 4000 < sqm > 600 Btyp27
bja = 5 du = 1 sqm < 600 Btyp28
bja = 5 du > 1 sqm < 600 Btyp29
bja = 5 du > 1 4000 < sqm > 600 Btyp30
bja = 6 du = 1 sqm < 600 Btyp31
bja = 6 du > 1 sqm < 600 Btyp32
bja = 6 du > 1 4000 < sqm > 600 Btyp33
bja = 7 du = 1 sqm < 600 Btyp34
bja = 7 du > 1 sqm < 600 Btyp35
bja = 7 du > 1 4000 < sqm > 600 Btyp36

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