gis -based energy consumption of the buildings in scharnhauser...

Warsaw Summer School SUSTAINABLE URBAN ENERGY CONCEPT S 31 August - 4 September 2009

The prelegentThe prelegent’’s s logologo

GISGIS--based Energy based Energy Consumption of the Buildings Consumption of the Buildings

in Scharnhauser Parkin Scharnhauser Park

Strzalka AnetaStrzalka Aneta

Zafh.netZafh.net



Scharnhauser ParkScharnhauser ParkTotal building area: 178.000 m²

1

2 3

• A former military area

• Low energy building standards

• Optimisation of new biomass plant (combined heat and electrcity power)



District heating networkDistrict heating network

District heating network – 13,5 km



Target Target Applicability of GIS technology

for improving the Energy Management of Scharnhauser Park

Contribution to the improvement of sustainable urban development

GeoMedia software family - products



Methodology Methodology

GIS

DataAcquisition

DataProcessing

Visualisation



Data acquisition Data acquisition Energy data

(Excel and paper sheets)

Database (Access)Building

related data

TABLE:

BUILDINGS

TABLE:

ENERGY METERS

TABLE:

ENERGY

CONSUMPTION



Building geometries Building geometries

Text

object category

layer name – „buildings“



Laser scanner data Laser scanner data

3519022.85 5397002.97 312.18

3519046.79 5397002.64 309.09

3519060.79 5397002.39 308.89

3519018.01 5397004.26 316.83

3519024.38 5397003.64 310.47

(…)

x

yzLaser scanner data – Airbone LIDAR Sensoren (Light Detection And Ranging)



Geoinformation system Geoinformation system Spatial data (DXF – file)

Database (Access)

Spatial data

Energy data(Excel and paper sheets)

Database (Access)

Building data

Laser scanner data

GeoWorkspace(GWS)



Visualization of building Visualization of building attributesattributes



Energy consumption visualizationEnergy consumption visualization

Individual buildings



POLYCITY SPECIFICATION :56 kWh/m²

POLYCITY SPECIFICATION :28 kWh/m²

Residential buildings Residential buildings –– heating and electricity consumptionheating and electricity consumption



Analysis of row housesAnalysis of row housesVisualization

AVERAGE VALUEof the energy consumption for each of the building type



Types of row housesTypes of row houses

0

10

20

30

40

50

60

70

80

90

A B C D E F G H I J K L M N O P R S T A-T

Building type

Hea

t con

sum

ptio

n in

kW

h/m

²a

Average value Standard deviation

Standard deviation of the average value up to 40%



MultiMulti--family house (12 apartments)family house (12 apartments)

1 – partially heated

2 – heated

3 – not heated Gross heating area:

1906 m²



Heating energy consumption of the residential build ing Siedlungswerk

0

2

4

6

8

10

12

14

16

18

20

Jan

06F

eb 0

6M

rz 0

6A

pr 0

6M

ai 0

6Ju

n 06

Jul 0

6A

ugS

ep 0

6O

kt 0

6N

ov 0

6D

ez 0

6Ja

n 07

Feb

07

Mrz

07

Apr

07

Mai

07

Jun

07Ju

l 07

Aug

Sep

07

Okt

07

Nov

07

Dez

07

Jan

08F

eb 0

8M

rz 0

8A

pr 0

8M

ai 0

8Ju

n 08

Jul 0

8A

ugS

ep 0

8O

kt 0

8N

ov 0

8D

ez 0

8Ja

n 09

Month

Hea

ting

ener

gy c

onsu

mpt

ion

kWh/

m²a

Heating energy consumption Heating energy consumption correction

Static heating energy consumptionStatic heating energy consumption

Monthly heating energy consumption data

Annual heating energy consumption - MfH Bettin-von- Arnim-Str. 17-21/2

0

10

20

30

40

50

60

70

80

90

2006 2007 2008

Time period

Wär

mev

erbr

auch

kW

h/m

²a

Annual heating energy consumption Weather correction POLYCITY_Value

POLYCITY: 56 kWh/m²a



Building counter

Heating counter per flat

M-Bus metering

Multi family house

Monitoring conceptMonitoring concept



Manual data acquisitionManual data acquisition



Building counter

Heating counter per flat

M-Bus metering

Multi family house

ModemZafh.Net

Data base

Simulationand analysis

Automatic monitoring conceptAutomatic monitoring concept

TIXI modem



Data transfer per EData transfer per E--mailmail



Statistical daily profile Statistical daily profile –– whole buildingwhole building



Daily profiles of each apartment of the multi-famil y house

0,0

0,5

1,0

1,5

2,0

2,5

3,0

3,5

01:00 02:00 03:00 04:00 05:00 06:00 07:00 08:00 09:00 10:00 11:00 12:00 13:00 14:00 15:00 16:00 17:00 18:00 19:00 20:00 21:00 22:00 23:00 00:00

Hour

Hea

ting

ener

gy c

onsu

mpt

ion

in k

Wh

179 180 181 182 183 185 186 187 188 190

Daily profiles Daily profiles –– heating energy consumptionheating energy consumption



Apartments (2 floor, 3 floor and 4 floor)

0

200

400

600

800

1000

1200

1400

1600

1800

2000

Apr 08 Mai 08 Jun 08 Jul 08 Aug 08 Sep 08 Okt 08 Nov 08 Dez 08 Jan 09

Monat

Hea

ting

ener

gy c

onsu

mpt

ion

kWh

Flat 181 Flat 182 Flat 183 Flat 185 Flat 188

Two comparable flats

0

10

20

30

40

50

60

70

80

1.1

2.1

3.1

4.1

5.1

6.1

7.1

8.1

9.1

10.1

11.1

12.1

13.1

14.1

15.1

16.1

17.1

18.1

19.1

20.1

21.1

22.1

23.1

24.1

25.1

26.1

27.1

28.1

29.1

30.1

31.1

Day

Hea

ting

ener

gy c

onsu

mpt

ion

/ kW

h

Flat 1 Flat 2

Influence of the user behaviorInfluence of the user behavior



HIGH POINTS GROUND POINTS

SECTIONAL VIEW inclined roof

flat roof

Types of the roofs in SHP Types of the roofs in SHP



ROOFS

FLAT ROOFS(79 %)

INCLINED ROOFS(21 %)

Min area value of 8m² South orientation of 145°-215°Roof inclination of 15°- 45°

Solar roof potential analysisSolar roof potential analysis



Detection of PV suitable roof areasDetection of PV suitable roof areasLaser scaner data and ALK map (buildings contours)

Calculation of the average of the vegetation points and its standard deviation for the respective building

Classification of the flat and inclined roofs on the basis of the distribution of the vegetation points

Aggregation: Total area of the flat roofs on the basis of the ALK – building contours

Aggregation of the laser scanner data for the respective building

Subtraction of the average of ground and vegetation points



Classification of roof areas in SHPClassification of roof areas in SHP



Y = η * F * H * fSystem efficiency:

0,11 – 0,12 Suitable roof area:

31.000 m²

Global radiation (by 40°):

1299 kWh/(m²a) (Year 2005)

Correction factor:

1,0

Over 4.000 MWh/a

Solar power potential Solar power potential



0 1000 2000 3000 4000 5000 6000 7000 8000 9000 10000 11000

12%

11%

Effi

cien

cy fa

ktor

of P

V in

%

Electricity in MWh/a

Electricity consumption MWh/a Solar potential MWh/a

40 % of electricity demand could be covered

PVPV--suitable roof areassuitable roof areas



Publication via InternetPublication via Internet

Laser scanner data

Web Map Service (WMS)

POLYCITY-Website

Publication

Spatial data (DXF – file)

GeoWorkspace(GWS)

Database (Access)

Spatial data

Energy data(Excel and paper sheets)

Database (Access)

Building data



GIS into POLYCITYGIS into POLYCITY--WebsiteWebsite

Implementation in the POLYCITY-Website



Pilot ApplicationPilot Application



Building info on the webBuilding info on the webPossibility to change the view

Information about the building attributes and building energy consumption



ConclusionsConclusions

•Example of using the GIS-technology for sustainable modernization and management of urban areas

•High potential for energy savings by changing the user‘s behaviour

•High photovoltaic potential of the building roofs

•Model for other similar communities to support the sustainable EM



Thank you for your attentionThank you for your attention

gis -based energy consumption of the buildings in scharnhauser...

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