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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
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Stockholm Challenge
CO2 equivalent
Population
Regional GNP
Year
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From a brown field area to a sustainable city district
Stockholm Royal Seaport
• F
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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
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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
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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
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Optimizedbuilding climate
Smart appliancesfor load shifting
Electrical andthermal storage
Local power and heat generation
Emerging Technologies for Energy Efficiency
Local renewablepower generation
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KTH Building Automation Testbed
KTH Campus
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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
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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
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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
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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