SMART ENERGY CITIES Centre for IT-Intelligent Energy Systems in Cities (CITIES) Assoc. Prof. Alfred Heller Technical University of Denmark

10 March 2015 Arup University Presentation 2 (Al)Fred Heller

Source: ”Our Future Energy”, the Danish Parliament, Nov. 2011

ENERGY POLICIES – THE SOCIETAL MOTIVATION

100% share of RE in the heating sector by 2035

10 March 2015 Arup University Presentation 3 (Al)Fred Heller

The proposed solutions

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www.roennebaekskole.skoleintra.dk

• Energy efficiency and savings

& Renewables

The challenge

10 March 2015 Arup University Presentation 4 (Al)Fred Heller

SMART GRID

The smart grid cannot solve the challenge of fluctuating energy production and demand by itself

10 March 2015 Arup University Presentation 5 (Al)Fred Heller

The proposed solutions

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• Demand Side Management

• Fleksibility The ability to shift energy demands in time and space

10 March 2015 Arup University Presentation 6 (Al)Fred Heller

Data &

Modelling

Flexibility

Storage through

ESI

Energy Efficiency

Cross Energy Carrier

Electrification

Renewables

SMART ENERGY bowered by

10 March 2015 Arup University Presentation 7 (Al)Fred Heller

THE CONCEPT Integration based on ICT solutions leading to methods for operation and planning for future energy systems

10 March 2015 Arup University Presentation 8 (Al)Fred Heller

SOCIETAL OBJECTIVES

To establish methods and realistic scenarios for ultimately achieving independency from fossil fuels by harnessing the latent flexibility of energy systems in cities through intelligence, integration, and planning.

10 March 2015 Arup University Presentation 9 (Al)Fred Heller

SCIENTIFIC OBJECTIVES To establish methodologies and ICT solutions for design and operation of integrated electrical, thermal, fuel pathways at all scales

10 March 2015 Arup University Presentation 10 (Al)Fred Heller

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10 March 2015 Arup University Presentation 11 (Al)Fred Heller

Scientific Method – Data

Because we cannot do the modelling (yet)

• The data research cycle

Validation

System identification

Modellering Simulation

Dimensioning

Optimizing

Implementation Monitoring

Predicting

Control

Demand Side Management

10 March 2015 Arup University Presentation 12 (Al)Fred Heller

IMPACTS OF BUILDING Can Buildings have an active role in the future energy system? Can we store energy in the Building Mass? Tendency: Less than expected

10 March 2015 Arup University Presentation 13 (Al)Fred Heller

Design tendency – Activate the termal mass • Known technologies: Floor heating Next technologies (innovative potential)

– TABS and others

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• Solar Declathlon 2012 THE FOLD

• with cealing and floor “activated”

10 March 2015 Arup University Presentation 14 (Al)Fred Heller

Flexible sensoring – Smart Buildings (automation)

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• “Communcative sensors”

Remote controllable Internet of Things

Remote control

Apisseq, Sisimiut -Grønland

10 March 2015 Arup University Presentation 15 (Al)Fred Heller

Flexible sensoring – Smart Buildings (automation)

• …

Communication Integration:

GIS>BIM>Plan>Component>…

Visualization of Potentials

10 March 2015 Arup University Presentation 16 (Al)Fred Heller

Flexible sensoring – Smart Buildings (automation)

City level information (Big Data)

Building level information

10 March 2015 Arup University Presentation 17 (Al)Fred Heller

Copenhagen - Energy Lab Nordhavn The future energy system

• Eksempel EnergyLab Nordhavn (under planlægning)

• Research project (26 mill. €) – Monitoring of buildings, energy systems (el, heat, cooling, gas …)

• > 100.000 data points – Experiments

• Low temperature district heating • Cross eneryg carrier experiments

– Living Lab Experiments • User • Communities

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Kilde: http://www.byoghavn.dk/byudvikling/bydele/nordhavnen/landvindingsprojektet+i+nordhavnen.aspx

10 March 2015 Arup University Presentation 18 (Al)Fred Heller

Frederikssund - Vinge The smart grid city

• Eksempel Electicity – sole energy source – How do we get this smart grid stable?

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Source: da.henninglarsen.com

10 March 2015 Arup University Presentation 19 (Al)Fred Heller

Smart City Lyngby The university smart city

• Eksempel Big Data Campus Open Infrastructure ‘

(openness => intelligens & innovation)

• A train trassé defining the Hot Spots and developments

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