Smart Infrastructures for a Sustainable City: Stockholm Case Studies

Karl H. Johansson

ACCESS Linnaeus Center & Electrical Engineering

Royal Institute of Technology, Stockholm, Sweden

Future Cities Conference, Porto, Jan 28, 2014

Stockholm Challenge

CO2 equivalent

Population

Regional GNP

Year

From a brown field area to a sustainable city district

Stockholm Royal Seaport

• F

From a brown field area to a sustainable city district

Stockholm Royal Seaport

• F

Project Goals• CO2 emissions <1.5 tons per person by 2020 (today 4.5)• Fossil fuel-free by 2030

Energy Consumption and Enabling Technologies

Energy consumption in Europe

• 40% of total energy use is in buildings

• 76% of building energy is for comfort

SMART 2020: Enabling the low carbon economy in the information age, The Climate Group, Report, 2008

Buildings;

2,4

Transport;

2,2

Power; 2,1

Industry;

1,1

Energy efficiency requirements in building codes, International Energy Agency, Report, 2008

Enabling Information and Communication Infrastructure

• Total energy savings of up to 15% by 2020

• Buildings can save 2.4 GtCO2e

• Enormous potential for control and optimization

How to Achieve Energy Efficiency?

Load

Time of the day

Load reduction

Load

Time of the day

Load shifting

Load

Time of the day

Peak shaving

Optimizedbuilding climate

Smart appliancesfor load shifting

Electrical andthermal storage

Local power and heat generation

Emerging Technologies for Energy Efficiency

Local renewablepower generation

KTH Building Automation Testbed

KTH Campus

Optimized Building Climate

Optimal control problemMinimize energy use While keeping indoor temperature and

air quality within comfort range

Parisio et al., 2013

Integrated technologiesNew sensors• Wireless temp, CO2

• People counter• Weather station• Occupancy schedulesData collection and

analytics:• Historical data• hvac.ee.kth.seAdvanced control

0 5 10 15 20 250.4

0.5

0.6

0.7

0.8

0.9

1

1.1

Ele

ctric

ity p

rice

(SE

K/(

kW*h

))

hour0 5 10 15 20 25

180

200

220

240

260

280

300

320

CO

2 co

st (

g/(k

W*h

))

Smart Home Appliances Scheduling

basic

home

gateway

smart

home

gateway

smart

appliance

Decision: when to run? How to run?

Optimal power profile scheduling for smart appliances

Tariff (

SE

K/k

Wh)

Hour

CO

2 inte

nsity (

g/k

Wh)

cheap

green

Sou et al., 2013

Cyber-Physical Systems Roadmap, German National Academy of Science and Engineering, 2011

From Smart Infrastructure to Integrated City Goods Transportation

Collaborative road transportationReal-time traffic information

Koutsopoulos et al, 2010

• Coordinate city goods delivery• More efficient use of road network • Based on real-time traffic data• Novel price models and vehicles

Summary• Buildings and transportations are large energy consumers

• New sensor, communication, control and cloud technologies enable innovations and shift in mind set– Buildings as dynamic storage and controllable resource for city-wide adaptation

– Optimize climate and appliances using weather, occupancy, price information

– Collaborative goods transportation

• Multi-disciplinary challenges requiring strong fundamental research together with industry collaborations

people.kth.se/~kallejFinland’s, Sweden’s, and Denmark’s Prime Ministers visiting the “Active House” in the Stockholm Royal Seaport 2013