1

EFS 2015 / 2016

Buildings: Energy, Environment and Health

Manuel C. Gameiro da SilvaReseach Group in Energy, Environment and ComfortADAI-LAETA, Department of Mechanical EngineeringUniversity of Coimbra

manuel.gameiro@dem.uc.pt

2

Energy Framework for Europe

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Energy Framework for Europe

0

200

400

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1990 1995 2000 2005 2006 2010 2011 2012

EU Energy Demand (Mtoe)

INDUSTRY TRANSPORTS HOUSEHOLDS SERVICES AGRICULTURE OTHER

INDUSTRY282,826%

TRANSPORTS351,732%

HOUSEHOLDS289,226%

SERVICES148,713%

AGRICULTURE252%

OTHER7,21%

EU 28 Energy Demand 2012 (Mtoe & %)

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Energy Framework for Europe

-60

-40

-20

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Aust

ria

Belg

ium

Bulg

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Cypr

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Czec

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Den

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Esto

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Finl

and

Fran

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Ger

man

y

Gre

ece

Hun

gary

Irela

nd

Italy

Latv

ia

Lith

uani

a

Luxe

mbo

u…

Mal

ta

Net

herla

nds

Pola

nd

Port

ugal

Rom

ania

Slov

ak …

Slov

enia

Spai

n

Swed

en

Uni

ted …

E-27

Energy Import Dependency 2006 (%)

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Energy Framework for Europe

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Ener

gy D

eman

d in

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6 (M

toe)

SERVICES

AGRICULTURE

HOUSEHOLDS

TRANSPORTS

INDUSTRY

Total Energy Demand (Mtoe & %) for the countries of EU-27 (2006)

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Buildings in Europe

Germany32,360,215

France24,270,161

United Kingdom17,870,119

Italy15,140,101

Spain9,270,062

Poland6,570,044

Netherlands7,830,052

Belgium4,460,030

Sweden4,1

0,027

Austria3,140,021

Finland2,73

0,018

Czech Republic3,39

0,023

Romania2,770,018

Greece2,070,014

Portugal2,19

0,015

Hungary3,21

0,021

Denmark2,040,014

Ireland1,6

0,011

Slovak Republic

1,880,013 Bulgaria

0,940,006

Slovenia0,460,003

Lithuania0,620,004

Luxembourg0,110,001

Latvia0,63

0,004

Estonia0,39

0,003

Cyprus0,19

0,001Malta0,06

0,000

Energy Demand in Services (Mtoe & %) for the countries of EU-27(2006)

7

Buildings in Europe

Energy Demand in Households (Mtoe & %) for the countries of EU-27(2006)

Germany69,120,227

France44,640,146

United Kingdom42,140,138

Italy29,920,098

Spain15,190,050

Poland19,180,063

Netherlands10,010,033

Belgium8,93

0,029

Sweden7

0,023

Austria6,630,022

Finland4,95

0,016

Czech Republic

6,510,021

Romania7,840,026

Greece5,490,018

Portugal3,2

0,010

Hungary6,18

0,020

Denmark4,420,014

Ireland3,06

0,010Slovak

Republic2,32

0,008

Bulgaria2,18

0,007Slovenia

1,160,004 Lithuania

1,430,005

Luxembourg0,610,002

Latvia1,49

0,005

Estonia0,88

0,003

Cyprus0,35

0,001 Malta0,080,000

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Buildings in Europe

The size of building stock in Europe (adapted from M. Economidou et al (2011))

47 m2/person

81 m2/person

26 m2/person

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Buildings in Europe

Breakdown of European building stock (adapted from M. Economidou et al (2011))

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Climate Zones

ECOFYS Climate zones suitable for ranking of technology options and comparison of building performance

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Heating and Cooling Days

The best indicators to synthesize in a quantified way the greater or lesser harshness of weather conditions, respectively in situations of cold and heat, are heating degree days (HDD) and cooling degree days (CDD)

Are defined as the annual sum of daily differences between the mean outside temperature of the day and a reference temperature at which it would be not necessary to use systems either heating or cooling to maintain comfort conditions inside a building.

Normally, reference temperatures are not the same for HDD and CDD

12

Heating and Cooling Days

Heating and Cooling degrees-days for the European countries (Tref = 17ºC)Source: Heating and Cooling Degree Days, Kevin Baumert and Mindy Selman, World Resources Institute, 2003

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1000

2000

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4000

5000

6000Fi

nlan

dEs

toni

aSw

eden

Latv

iaLi

thua

nia

Pola

ndCz

ech

Rep

Den

mar

kSl

ovak

iaAu

stria

Luxe

mbo

urg

Slov

enia

Rom

ania

Ger

man

yH

unga

ryBe

lgiu

mN

ethe

rland

sBu

lgar

iaIre

land U

KFr

ance

Italy

Gre

ece

Spai

nCy

prus

Mal

taPo

rtug

al

degr

ees-

days

cooling degrees-days

heating degrees-days

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Total Energy Demand vs HDD+CDD

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Finl

and

Esto

nia

Swed

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Latv

ia

Lith

uani

a

Pola

nd

Czec

h Re

p

Den

mar

k

Slov

akia

Aust

ria

Luxe

mbo

urg

Slov

enia

Rom

ania

Ger

man

y

Hun

gary

Belg

ium

Net

herla

nds

Bulg

aria

Irela

nd UK

Fran

ce

Italy

Gre

ece

Spai

n

Cypr

us

Mal

ta

Port

ugal

kgoe

/per

son

degr

ee-d

ays

heating+cooling degree-daysTotal energy demand per capita in service buildings

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7000

Finl

and

Esto

nia

Swed

en

Latv

ia

Lithu

ania

Pola

nd

Czec

h Re

p

Denm

ark

Slov

akia

Aust

ria

Luxe

mbo

urg

Slov

enia

Rom

ania

Germ

any

Hung

ary

Belg

ium

Neth

erla

nds

Bulg

aria

Irela

nd UK

Fran

ce

Italy

Gree

ce

Spai

n

Cypr

us

Mal

ta

Port

ugal

kgoe

/per

son

degr

ee-s

ays

heating+cooling degree-days

Energy demand per capita in households

Total Energy Demand vs HDD+CDD

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Energy Intensity of EU

Energy Intensity of the Economies of the

EU-27 countries (2006)

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Climate Zones (USA)

  IECC Climate ZoneMiami 1AHouston 2APhoenix 2BAtlanta 3ALos Angeles 3BLas Vegas 3BSan Francisco 3CBaltimore 4AAlbuquerque 4BSeattle 4CChicago 5ABoulder 5BMinneapolis 6AHelena 6BDuluth 7Fairbanks 8

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Energy Demand (USA)

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50

100

150

200

250

300

350

400

450

500

Heating

Cooling

Ventilation

Water Heating

Lighting

Equipment

Retail Buildings (kWh/(m2.year)

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Energy Fluxes in a Building

Electricity

Gas, Oil, Coal, Wood, ...

Ventilation, Heating and

Cooling Systems

inc.cogeneration

District Heating and Cooling

Photovoltaic, Local Wind Turb

Solar Thermal

Dis

trib

utio

n an

d tr

ansp

ort

Electrical Devices

Lighting

Ventilation

Warm Water

Cooling

Heating

Kitchens

Electricity

Heat

Sent

Received

BUILDING

SystemsConsumptions

Renewables

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NZEB concept

Directive 2010/31/EU (EPBD recast) defines NZEB as a building that has a very high energy performance

The nearly zero or very low amount of energy required should be covered to a very significant extent by energy from renewable sources

The energy performance of a building shall be expressed in a transparent manner and shall include an energy performance indicator and a numeric indicator of primary energy use, based on primary energy factors per energy carrier

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NZEB Concept

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NZEB Concept

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System Boundaries of a NZEB

Definition of the system boundary for the case of on-site renewable production. Adapted from Rehva (2013)

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Definition of the system boundary for the case of on-site renewable production. Adapted from Rehva (2013)

System Boundaries of a NZEB

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Cost-Optimal Concept

Cost-Optimal Concept

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The Path to NZEBs

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1.º Changing/Reducing traditional requirements

2.º Energy Efficiency

3.º Renewables

4.º Energy monitoring

The Path to NZEBs

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Domestic Hot Water (DHW) Example.Existing DHW system serving showers in a gymnasium, using a gas boiler to

produce DHW

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Domestic Hot Water (DHW) Example.

Energy Efficiency Changing requirements

Renewables

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Relevant Parameters

Energy Supply

Thermal Lossesand/or Gains

Indoor Environmental Quality (IEQ):

Thermal, Noise, Air Quality, Light

(Physical/ Sensorial)

Environmental Impacts

Façade Characterization:

Pressure Fields, Noise Field, Light Distribution,

Thermal Losses

Sent Energy

InternalGains

Thermal Inertia

Local Production

Outdoor Conditions:Weather, Air Quality,

Noise, Sunshine, Lighting, …

3030

Metabolic Heat Production (M)

Conduction to or from clothing (K)

Convection Exchanges with air Layers (C)

Wet and Dry Heat Exchanges in Respiration (Res)

oo oo

Radiation Exchanges with Surroundings (R)

External Mechanical Work (W)

Evaporation Losses in Sweating and Perspiration (E)

S = M - W + R + C + K - E + Res

Heat Balance of the Human Body

Thermal Comfort Requirements

3131

Human Body Thermal Regulation

ENVIRONMENT

Temperature

Air Velocity

Mean Rad Temp

Rel Humidity.

Convection

Evaporation

Radiation

SKIN

HUMAN BODY

TISSUES

Central Nervous System

Hipotalamus

CLO

TH

ING

Breathing

Sweating

Skin Heat Flux

Deep Body temperature

Shievering

Conduction

Blood Flux

Thermal Comfort Requirements

3232

Thermal Environment Indices

Air Temperature (ºC)

22.3

Air Velocity (m/s)

0.47

Radiant Temperature (ºC)

17.1

Relative Humidity (%)

65.4

?

Equivalent Temperature (ºC))

18.0 @ 1 clo

3333

Operative Temperatura (to)Uniform temperature of a black imaginary enclosure where the occupant exchanges the same amount of heat, by convection and radiation, as in the real one.

Equivalent Temperature (te)Uniform temperature of an imaginary enclosure , with null air velocity, where the occupant exchanges the same amount of sensible heat as in the real one.

Efective Temperature (ET*)Uniform temperature of an imaginary enclosure with a 50% relative humidity, where the occupant exchanges the same amount of heat aby radiation, convection and evaporation as in the real one

Thermal Environment Indices

3434

PMV = (0,303e-0,036*M + 0,028)*[(M-W) - H - Ec - Cres – Eres ]

+3 Hot

+2 Warm+1 Slightly Warm

0 Neutral

-

-

-

- +3

- +2- +1

-

- -1 Slightly Cool

-2 Cool

-3 Cold

-

-

Fanger’s Model (PMV and PPD, ISO 7730:2005 )

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Fanger’s Model (PMV and PPD, ISO 7730:2005 )

PMV = (0,303e-0,036*M + 0,028)*[(M-W) - H - Ec - Cres – Eres ]

PMV = (0,303e-2,100*M + 0,028)*[(M-W)

- 3,96*10-8*fcl*[(tcl+273)4 - (tr+273) 4] - fcl*hc*(tcl-ta)

- 3,05*10-3*[5733 – 6,99*(M-W)-pa] -0,42*[(M-W)-58,15]

- 0,0014*M*(34 - ta) – 1,7*10-5*M*(5867-pa)]

Human vote model

Heat Generation

H2: Convection

Ec2: Sweating

Breathing (sensible)

Ec1: Perspiration

H1: Radiation

Breathing (latent)

3636

Calculation Tool (PMV and PPD, ISO 7730:2005 )

3737

Breakdown of human body energy losses (PMV and PPD, ISO 7730:2005 )

convection35%

radiation38%

sweating6%

perspiration13%

breathing (latent)6%

breathing (sensible)

2%

3838

PPD Index (Predicted Percentage of Dissatisfied)

4 2(0.03353 0.2179 )100 95 PMV PMVPPD e

PMV-index (Predicted Mean Vote) predicts the subjective ratings of the environment in a group of people.

PPD-index predicts the number of dissatisfied people.

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S = M - W + R + C + K - E + Res

Metabolic Heat Production

1 Met = 58.15 W/m2 0.8 Met

1 Met

8 Met

4 Met

Activity Metabolic Rates [M]

Reclining 46 W/m2 0.8 Met

Seated relaxed 58 W/m2 1.0 Met

Clock and watch repairer 65 W/m2 1.1 Met

Standing relaxed 70 W/m2 1.2 Met

Car driving 80 W/m2 1.4 Met

Standing, light activity (shopping) 93 W/m2 1.6 Met

Walking on the level, 2 km/h 110 W/m2 1.9 Met

Standing, medium activity (domestic work) 116 W/m2 2.0 Met

Washing dishes standing 145 W/m2 2.5 Met

Walking on the level, 5 km/h 200 W/m2 3.4 Met

Building industry 275 W/m2 4.7 Met

Sports - running at 15 km/h 550 W/m2 9.5 Met

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Insulation of Clothing

1 0155 2Clo m C W . º /

0,15 Clo

0.5 Clo

1.0 Clo1.2 Clo

Clothing Clo m2ºC/W

Jacket 0.35 0.054

Coat 0.70 0.109

Trousers 0.25 0.039

Skirt 0.18 0.028

Short skirt 0.10 0.016

Shirt 0.25 0.039

Light shoes 0.02 0.003

Boots 0.10 0.016

4141

Insulation of Clothing

4242

Thermal Comfort of the Human Body as a Whole – ISO 7730:2005

4343

Thermal Comfort of the Human Body as a Whole – ISO 7730:2005

-1.0 -0.8 -0.6 -0.4 -0.2 0.0 0.2 0.4 0.6 0.8 1.00

5

10

15

20

25

30

PMV

PP

D (

%)

Category A

Category B

Category C

Discomfortable

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Yearly distribution of comfort categories for a classroom - occupation period

Diferent ventilation strategies

4545

Adaptive Models

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Mean outdoor effective temperature (ET*ODM) [°C]In

do

or

op

era

tive

te

mp

era

ture

[°C

] Comfort temperature in HVAC = 22,6 + 0,04 ET*ODM

90% sat. occ.

80% sat. occ.

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22

24

26

28

30

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-5 0 5 10 15 20 25 30 35

Mean outdoor effective temperature (ET*ODM) [°C]

Indo

or o

pera

tive

tem

pera

ture

[°C

] Comfort temperature in NV = 18,9 + 0,255 ET*ODM

90% sat. occ.

80% sat. occ.

Acceptability ranges for 90% and 80% satisfied occupants for fully mechanically controlled (HVAC) and for naturally ventilated (NV) environments

Adaptive Models

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1617181920212223242526272829303132

-5 0 5 10 15 20 25 30 35

Monthly mean outdoor temperature [°C]

Ind

oo

r o

per

ativ

e te

mp

erat

ure

[°C

]

90% sat 80% sat

Adaptive thermal comfort diagram for naturally ventilated environments, adopted into ASHRAE Standard 55/2004

Adaptive Models

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20

22

24

26

28

30

32

34

5 10 15 20 25 30

Outdoor mean running temperature [°C]

Indo

or o

pera

tive

tem

pera

ture

[°C

]

I

II

III

III

III

t ORM(n) = (1 – α) ( t OMD(n-1) + α t OMD(n-2) + α2 t OMD(n-3) + ….)

t ORM(n) running mean temperature in the day n

t ODM(n) outdoor daily mean temperature in the day n

Indoor operative temperature vs outdoor mean running temperature for buildings without mechanical cooling systems

Adaptive Models

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Indoor Air Quality

An indicator of the types and amounts of pollutants in the air that might cause discomfort or risk of adverse effects on human or animal health, or damage to vegetation

Air quality is usually referenced to the concentration in air of one or more pollutants. For many pollutants, air quality is expressed as an average concentration over a certain period of time, e.g., μg/m3 averaged over 8 hours

(In ISIAQ Glossary of Indoor Air Sciences, 1st ed, 2006)

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IAQ Concentrations

of Pollutants

Effects in Health and Comfort

Generation of Pollutants

Air Processing

IAQ Triangle

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Variation of Concentration

Emitted Pollutants

Pollutants entering

Pollutants leaving

Poluentes deposited or absorpted

Removed pollutants

acac

dvextv CV

Q

V

SvtCC

V

G

dt

dC )(

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Charging Fase

C0

C0

Cequi

Cequi

Decay Fase

Q

GCC extequi

CCV

G

dt

dCext

t

equi

equi eCC

C)t(C

0

Basic Equations

53

Cequi

Cavg

Parameter Condition Method

Fresh Air Flow Rate or

Air Exchange Rate

Cequi < Cref Prescriptive

Cavg < Cref Analytical

Definition of Ventilation Requirements

54

Basis of the Prescriptive Methods

))(( tCCV

G

dt

dCextv

0dt

dC)(0 equiextv CC

V

G

vextequi V

GCC

V

Qv

Q

GCC extequi

)( extequi CC

GQ

as

C0 = Cext

Cequi

55

0 10 20 30 40 50 600

500

1000

1500

2000

2500

3000

Q [m3/(h.person)]

Co

nc.

CO

2 (

pp

m)

NOTE: Curve for the CO2 generation of CO2 of a standard person (P50%) with 1.2 met matabolic rate

Clim <1000 ppm

Q > 30 m3/(h.person)

)( extequi CC

GQ

Basis of the Prescriptive Methods

56

Example of a Prescriptive Method

G[CO2 ]= 30833 [(mg/h) / met] x M [met]

1 person percentil 50 (70kg, 1,7m)

Cext = 680mg/m3

Minimum Fresh Air Flow Rate

57

Example of a Prescriptive Method

Type of activity Metabolic Rate- M (met) Type of Space Fresh Air Flow Rate

[m3/(hora.person)]

Sleeping 0,8 Bedrooms, Dormitories, etc. 16

Resting 1 Resting rooms, Waiting Rooms, Conferene Rooms, Auditoriums 20

Sedentary 1,2 Offices, Libraries, Schools 24

Moderate 1,75 (1,4 a 2,0) Laboratories Ateliers, Drawing Rooms, Cafés, Bars, 35

Slightly High 2,5 ( 2,0 a 3,0) Dance Floors, Gymnasium rooms, Ballet rooms 49

High 5,0 ( 3,0 a 9,0) Bodybuilder rooms, Sport facilities, etc 98

)(20)]./([ 3 metMpersonhmQ

58

CategoryDaily Average Concentrations

CO2

Special Req 1600 mg/m3 900 ppm

Normal 2250 mg/m3 1250 ppm

It is performed a simulation of the time evolution of the concentration during the occupancy period, using a finite diferences equation, to calculate the dose at which occupants are exposed.

Analytical Method

tCCV

GC vextv

CC

V

G

dt

dCext

CCC ii 1

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Analytical MethodSoftware Tool version with Percentage of Occuppancy Input

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Software Tool version with Table Input Data

Analytical Method

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Monitoring Buildings. Why

"If you don't measure it, you can't manage it"

Buildings and Building Systems are too much complicated to understand with simple one-shot measurements, on account of the large number of relevant parameters with strong time and space variability.

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Case Study

A Business Park in the

municipality of Oeiras, at

the metropolitan area of

Lisbon, Portugal, 3 Km

away from the sea coast.

The building has three

floors for offices (7000 m2)

and three underground

floors for parking (8000 m2)

63

Studied Office building

Wireless network with

49 counters for

electrical energy, 15

indoor environmental

quality monitoring

stations (concentration

of CO2, air temperature,

relative humidity, VOCs

level) and one outdoor

weather station

64

Metering System

Data Reduction & Analysis

Web Server

Data Base

Sensors

Router

Structured Knowledge

Techn Management

BUILDING

Monitoring and Consulting Services

Web Based Monitoring Solution Concept

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Web Tool - Dashboard

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Web Software Tool – CO2 Data

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CO2 and Wind Speed Time Series

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1

2

3

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8

Win

d ve

loci

ty (m

/s)

ln (C

-Cex

t) (

ppm

)

Time (dd-mm-yy hh:mm)

Sunday Monday Tuesday Wednesday Thursday Friday Saturday

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Data analysis

( M o n t h m a p o f C O 2 C o n c e n t r a t i o n )

69

( M o n t h m a p s o f A i r t e m p e r a t u r e a n d Re l . H u m i d i t y )

Data analysis

70

Electrical Energy Data (week graph)

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Electrical Energy Data (24 h data)

7272

7373

7474

75

Greening Buildings

Change of control routines, Management of Solar Gains through Shadowing Solutions

Smart Management of Lighting (conjugation of natural and artificial lighting, low consumption lamps, occupancy sensors, etc.)

Controlled Ventilation (DCV, e. g. with CO2 sensors or time programmed)

Improvement of Wall Insulation and Characteristics of Glazing Areas

Use of solar thermal collectors for domestic hot water and indoor environment heating

Improvement of performance of HVAC systems. Energy recovery solutions

Photovoltaics for electrical energy Production, Thermal Energy Storage Solutions

Night free cooling, Tunning of Infiltration, Hybrid and Natural Ventilation

Management of active and idle periods of electric devices. Reduction of stand-by consumptions

Change of occupants habits, Redefinition of set points of indoor target conditions