inteligent buildings - vladimir vukovic

8/11/2019 Inteligent Buildings - Vladimir Vukovic

1/42

Information and CommunicationTechnologies for Increasing Building

Energy Efficiency

Sustainable Building TechnologiesEnergy Department

Austrian Institute of Technology

TECNOCONSTRUCCION 2012 - International Conference on Innovation and

Technological Construction Progress in Latin America, Cali, Colombia

November 14-17, 2012

Dr Vladimir Vukovic


2/42

2TECNOCONSTRUCCION 2012November 15, 2012

Overview

Background

Why ICT for Energy Efficiency in Buildings?

Project Examples

Concluding Remarks

Background


Project Examples

Concluding Remarks


3/42


The Origins

European Union 20/20/20 Goals

EU Energy supply is based on non-renewable resources: 37% oil, 24% gas

High import dependency of these resources: up to 84%

40% contribution of the building sector to primary energy consumption in EU

30% transport, 30% industry

Therefore:

20% reduction of green house gas emissions,

20% share of renewable energy sources,

20% increase in energy efficiency

By 2020, compared to 2005 levels (European Commission, 2008)

750 bil investment in power infrastructure over the next 30 years


4/42


Long term EU strategy

New EU R&D&I funding: Horizon 2020

Starting in 2014

Support for increasing building energy efficiency to energy neutralperformance

Horizon 2050

Energy positive buildings

2050 climate change mitigation requirements

Global GHG reductions 50%-80% (80%-95% developed countries)

ICT as the driving force and key enabling technology


5/42


ICT means Smart / Intelligent Systems

Smart or Intelligent

Refers to objects that can react correctly to unforeseen circumstancesby choosing amongst a set of possible actions and

can learn from the associated response.

Smart buildings

Can maximize the overall indoor environmental quality at the same timeminimizing the consumption of resources and the emissions due toconstruction, operation, maintenance and demolition processes

Integration of Building Automation System (BAS), Telecommunications

System (TS), Office Automation System (OAS) and Computer AidedFacility Management System (CAFMS).


6/42


Background


Project Examples

Concluding Remarks

Overview


7/42


Why Energy Efficiency?

Business-as-usual was on track to achieve only half of the 2020 efficiency

targets (SEC(2011)277)

To ensure 2020 efficiency targets are met, new policies are needed

EnergyEnvironmentEconomy Model for Europe (E3ME) estimatedbenefits of additional Energy Efficiency Directive measures

34 bil increase in GDP 400 000 new jobs

PRIMES model estimates

Increased energy efficiency investments 24 bil p.a.

Reduced power generation investments 6 bil p.a. Reduced fuel expenses 38 bil p.a.

20 bil p.a.profit


8/42


New EU Directives

Additional measures to ensure achievement of Energy efficiency targets

New Energy Efficiency Directive (to achieve 75% of the needed savings)(2011/0172 (COD))

2/3 of the 20% CO2 emissions reduction target to be achieve via EUEmissions Trading System

Adopted on September 11, 2012 Transport White Paper (to achieve 25% of the needed savings)

(SEC(2011)358)


9/42


EU ee Directive

Mandatory renovation of government buildings 3% of gross floor area

heated/cooled p.a. starting 1.1.2014. Mandatory annual new savings of 1.5% final energy customer sales, for

energy distributors and/or retailers

Long term strategy for national building stock

Statistical building stock overview

Identification of cost-effective renovation, w.r.t. climate

Policies and investment guidance

Estimation of expected energy savings

Public procurement of goods, services and buildings with high ee

All large enterprises required to carry out energy audits every 4 years Smart meters to provide customers energy consumption and time of use

Installation in new buildings and after major renovations

By 1.1.2017 in multi-apartment buildings served by district heating/cooling


10/42


Why ICT?

Technology is available, needs to be integrated to

Enable energy efficiency improvements

Monitoring and managing energy consumption can: save up to 17%of energy in buildings (EC DG INFSO, 2008), reduce by up to 27%carbon emissions in transport and storage (GeSI, 2008)

Energy efficient business models, working practices, lifestyles(eCommerce, teleworking, eGovernment) save energy and material

Innovative technologies (virtualization, cloud computing) reducesystem redundancies

Provide quantification basis for implementation and evaluation of energyefficient technologies

Smart metering can help reduce energy consumption by up to 10%

System level software tools can facilitate better configurations andoptimize energy performance


11/42


Why ICT?

Estimated ICT saving potentials

15% reduction in global carbon emissions (COM(2009) 111) energy consumption of residential buildings -35%, commercial buildings

-17%, industry -10% (EC DG INFSO, 2008)

Estimated market potentials

Worldwide market 126 bil Average payback less than 5 years (Siemens, 2010) Strong EU market growth

Supervisory control and data acquisition (SCADA): 1.3 bil in 2009 toreach 1.9 bil in 2016, +40% (+5% p.a.) (Frost & Sullivan, 2010)

Home automation: 132 mil in 2002, 307 mil in 2009 (>20% 2008/09)+13% p.a. 2011-2016

400+ mil smart home automation devices worldwide by 2017 (IMSResearch, 2012)


12/42


Why Buildings?

80% of the building life cycle costs occur after construction

80% of the building design fixed within the first 20% of the planning process

People spend 90% of lifetime within buildings: high investment visibility,societal benefits, behavioral adjustments (low/no cost measures)

Schierenbeck A, ICT in Buildings the Low Hanging Fruit for Energy Efficiency, Siemens AG (2010)Schierenbeck A, ICT in Buildings the Low Hanging Fruit for Energy Efficiency, Siemens AG (2010)


13/42


Why Buildings?

Majority of building energy

costs are related to heating,ventilation, air-conditioningand lighting (>60%)

Commercial buildings electricity usage in

the EU (EC JRC 2007)


14/42


Background


Project Examples

Concluding Remarks

Overview


15/42


History of Energy Saving Construction

Erhorn H and Erhorn-Kluttig H, The Path Towards 2020 Nearly Zero-Energy Buildings, REHVA Journal (2012)Erhorn H and Erhorn-Kluttig H, The Path Towards 2020 Nearly Zero-Energy Buildings, REHVA Journal (2012)


16/42


Areas of ICT development

ICT 4 E2B Forum FP7 project, D1.1.Classified Research Areas (2010)ICT 4 E2B Forum FP7 project, D1.1.Classified Research Areas (2010)

15%

15% 13%

37%20%

% of ICT research projects


17/42


Project example:Sounds for Energy Efficient Buildings (S4EeB) www.s4eeb.org

Knowing the exact occupancy and occupants activities (provided by sound

sensors) Energy saving strategies: Reduce lighting intensity

Lighting need depends on occupants location

Reduce ventilation flow rates reduce heating and cooling demand

Heating/cooling demand depends on the fresh air requirementsdirectly proportional to the number of occupants

Reducing ventilation rates also reduces fan energy ~ V3

Electricity usage CO2 emissions

Schedules

Demand controlled ventilation (DCV) Sensors: CO2, temperature, infrared presence detectors, video

Direct occupant counting shows much lower uncertainties (Dougan andDamiano, 2004; 2007)


18/42


Low cost acoustic sensing technology exists

Prototype power consumption: 33 W

Data interpretation and integration to BMSneeded ICT

Largest energy saving potential in buildings

and spaces of public use Oversized systems

High occupancy variability

Project example:Sounds for Energy Efficient Buildings (S4EeB) www.s4eeb.org

How much can be saved?

Transportation (Balaras et al. 2003) HVAC: 9.8%-38.5%, 25-87 kWh/m2/yr

Lighting: 2.4%-9.6%, 5-38 kWh/m2/yr

Retail spaces at most half of the savings in transportation facilities

Microphone array prototype


19/42


S4EeB preliminary results

40% accuracy of classification

with 6 occupancy levels 70% accuracy with 3 occupancy

levels


20/42


Existing HVACsystem

RefurbishmentNew building and/or

HVAC system

Model optimization

Modeling

Implementation of

optimized parameters

Optimal HVACsystem operation

Optimal refurbishedbuilding performance

Optimal building +HVAC design and

performance

Automated monitoring

Life-cycle validation Predictive controls

(weather, energyprices, occupancy, etc.)

Integrated modeling

environment Graphical user interface

Graphical systemperformance presentation

NEXT Generation Building Modeling and

Simulation Tools Goals:


21/42


Case study: ENERGYbase office building

Energy Information Administration (1995): Avg office building102 kWh/m2a (excluding office equipment, accounting for ~ 24%)

ENERGYbase measured electricity consumption

Ventilation TotalHeatingCoolingLighting

ENERGYbase showcase building (7,500 m2/ 80,000 ft2) Owner: Vienna Business Agency

Full scientific planing and support by Energy Dept. AIT

Total cost: 12.5 Mil

Financed by: Federal Ministry of Transportation,Innovation and Technology (BMVIT), City of Vienna,energy suppliers (Wienstrom, Verbund)

Passive house standard

Target: 80% reduction of primary energy consumptioncompared to typical office building


22/42


ENERGYbase: Office building of the future

energy efficiency - low energy use forheating, cooling, lighting and ventilation

use of renewable energy - 100%coverage of heating and cooling energy

demand with renewable energy(groundwater, solar energy)

wellness at work - exceptional indoorclimate and comfort at the workplace

form follows energy - close

connection between architecturalconcept and energy concept

Energy Sources: Ground water

Heating & Cooling Solar energy

Heating and cooling assistanceAir dehumidificationElectricity generation

Vegetation/PlantsHumidification

Electrical gridRemaining electricity demand


23/42


Heat pump delivers low temperature heat forthermally activated building component systemin winter

Free cooling mode in summer by direct groundwater usage also with thermally activatedbuilding component system

Combination of heat pump and solar plant inwinter for heating with 15,000 litres (4,000 gal)hot water storage

Heat pump Heat exchanger

ENERGYbase: Heat pump / ground water usage

TABS -Thermally activated building

component system Activation of storage mass for comfortable

radiant heating and cooling


24/42


a) b) c)

ENERGYbase: Renewable energy sources

100% coverage of heating and cooling demand by renewable energysources (ground water, solar energy)

a) ~ 400 m (4300 ft) photovoltaic panels

b) ~ 300 m (3230 ft) solar thermal flat plate collectors

c) use of groundwater for heating and cooling purposes


25/42


Supply Air

Return Air

Cooling distribution devices

- Thermal mass activation

Solar Collectors

HotWater

Storage

Well water

Desiccant cooling - system delivers air conditioned fresh air in summer

100% solar thermally driven solar cooling system

Usage of the desiccant system for humidityand heat recovery in winter

ENERGYbase: Solar Cooling

SW DesiccantWheel


26/42


Cyperus Alternifolius (Zyperngras)

Evaporation can be controlled through artificial lights

Ecological conditioning of the air during the heatingseason; a single plant can transfer 1 liter of water /day (0.25 gal/day)

Positive psychological aspect

ENERGYbase: Green rooms


27/42


South facade as a solargenerator

ENERGYbase: Form follows energy

Room Temperature [C]

Close integration of building andenergy concept

Optimized use of solar gains

Planning process supported bysimulation methods


28/42


Institut fr Wrmetechnik

TU Graz

ENERGYbase: Analysis of south faade (22nd July)

Solar radiation:Panels

Hor. surfaceVer. S surfaceVer. N surfaceGlazing


29/42


ENERGYbase: Yearly facade

performance

0 1000 2000 3000 4000 5000 6000 7000 8000

0

200

400

600

800

1000

1200

Stunde des Jahres

Solarstrahlung auf vertikale SdfassadeSolarstrahlung auf vertikale Nordfassade

W/m

0 1000 2000 3000 4000 5000 6000 7000 8000

0

200

400

600

800

1000

1200

Stunde des Jahres

Solarstrahlung auf PV PaneelSolarstrahlung auf Sdfassadenverglasung

W/m

hours/year

hours/year

solar radiation on vertical southsouthsouthsouth solar radiation on

vertical northnorthnorthnorth facade

solar radiation on PV panel

solar radiation on glazing

Active and passive components of solarradiation

Glazing picks up more solar radiation inwinter than in summer

In summer, Solar radiation on the Southglazed area is approximately equal to thevertical North facade


30/42


Air velocities [m/s], Cooling mode (12. Sept.)

CFD indoor comfort analyses

Air flow distribution

Building thermal loads

System design

Optimized building layout

Validation and monitoring

More building info at:http://www.energybase.at/eng/index.php

Building load profile (SW, SE; E, W office orientation)

EnergyBASE Detailed

Building Simulations


31/42


ENERGYbase: Design summary

Merging building design and energy performance

high potential of energy savings + high comfort

Use of natural sources for energy performance

Heating: ground water fossil fuels Cooling: solar power, ground water electrical chillers Distribution: building storage mass radiators, fan-coils Electricity: solar power traditional electricity generation Humidification: plants electricity driven humidifier

Predicted percentage dissatisfied [%] (thermal comfort)


32/42


Setpoint

tsupplyair

t supply air21

0

100

%

C

ENERGYbase: Optimization of operation

Identification of an initial ENERGYbase system to optimize

Overview of system components and available component models

Start from the simplest and proceed to the most difficult detailed

as built whole building simulation Solar thermal vs. Air handling system (components and available

simulation models)

Solar thermal system selected

ENERGYbase control sequencesof operation examined

Air-conditioning and ventilationsystem

Supply air temp control

Solar thermal system

Solar collector pump

Thermal storage pump

Variable frequency drive


33/42


ENERGYbase: Solar thermal system

modeling in Modelica Modeling of the solar thermal part of ENERGYbase HVAC systems

Model characterization and development

Pumps, heat exchanger, storage tank, solar thermal panels

ENERGYbase monitoring Siemens Desigo Insight, Advanced Data Processing database


34/42


ENERGYbase: Model validation

ENERGYbase solar thermal systemcomponents model validation Pump electricity consumption

(over the period of 1 month)

Solar collector field modeling GenOpt model calibration

3

21

0

-1

-2

-3

-4

-5

-6

-7

15 min moving average relative % error

Model, Monitoring collector field outlet tempMonitoring/Model collector field inlet temp

Fontanella et al. (2012)Fontanella et al. (2012)


35/42


ENERGYbase: Proklim - Feasibility studyof weather predictive control for a highlyinsulated building

Passivhausstandard

Negligible impact of ambienttemperature

Focus on solar radiation

How predictable is solar radiation? Impact of prediction uncertainty on

efficiency

Energy saving potential with respect

to comfort


36/42


ENERGYbase: Extensive monitoring

More than 500 sensors installed in the building

Portable IEQ monitoring


37/42


North

offices

ENERGYbase, corner room, 3rd floor: Investigation ofboundary conditions and additional data acquisition for

comparison with future CFD results Thermography / Ceiling temperature Volume flow measurements, flow visualization via

smoke experiment Additional 50 temperature and 19 velocity sensors

for three months Sensor data processing in MATLAB

kitchen and server room

meeting room

ENERGYbase: Indoor monitoring for CFDvalidation

North

offices


38/42


ENERGYbase: Towards energy positive performance

Integration of a wind turbine

Currently tested Monitoring

Waste heat recovery

Nearby wind tunnel

Feasibility study Energy positive building

construction planned -FUTUREbase


39/42


Background

Why ICT for Energy Efficiency in Buildings? Project Examples

Concluding Remarks

Overview


40/42


Integrated building simulations

Osterreicher and Vukovic (2010)Osterreicher and Vukovic (2010)


41/42


How the future may look like?

Companies already producing unmanned aircrafts

with thermal imaging systems Haringey Council (London) Interactive Heat Loss Map

http://www.seeit.co.uk/haringey/Map.cfm

Broadland District Council (Norfolk)

spent 30,000 (roughly 24,000) hiring a planewith a thermal imaging camera in order to trackhow much energy is being wasted in homes andbusinesses (Daily Mail, UK, 2009)

Council uses spy plane with thermal imagingcamera to snoop on homes wasting energy,Daily Mail, UK, March 24, 2009

UAV Unmanned Aircraft thermal imagingsystems, Barnard Microsystems Limited, 2012http://www.barnardmicrosystems.com/L4E_thermal_imaging.htm

Council uses spy plane with thermal imagingcamera to snoop on homes wasting energy,Daily Mail, UK, March 24, 2009

UAV Unmanned Aircraft thermal imagingsystems, Barnard Microsystems Limited, 2012http://www.barnardmicrosystems.com/L4E_thermal_imaging.htm


42/42


[email protected]

Austrian Institute of Technology

Energy DepartmentSustainable Building Technologies

www.ait.ac.at

Questions?

inteligent buildings - vladimir vukovic

Documents