1. Smart Cities: Some Activities at
the KTH ACCESS Center
Alessandra Parisio
ACCESS Linnaeus Center
Royal Institute of Technology, Sweden
2013 Conference, 23rd January, Porto, Portugal

2. Outline
• Motivation for smartness in cities
• Stockholm Royal Seaport Project
• Virtual Micro-Grid Laboratory
• Energy efficient building climate control
• Conclusion

3. Motivation
• Urban living and working must be sustainable
• Energy consumption and carbon emissions need to be reduced to
improve environmental sustainability and quality of life in cities
• Cities need to be smart
(e.g. smart buildings)
• Need of smart low-cost ICT
solutions

4. Smart Buildings in Europe
• 40% energy used in buildings
• 76% of this energy goes towards comfort
control in buildings – heating, ventilation
and air conditioning (HVAC)
• Large and attractive opportunities exist to reduce buildings’
energy use at lower costs and higher returns than in other
sectors
• Using more grid electricity from non-fossil sources (such as solar
and wind) will help to address climate change
International Energy Agency, Energy Efficiency Requirements in Building Codes – Energy Efficiency
Policies for New Buildings, 2008.

5. •F
From a brown field area to a sustainable city district
5
Stockholm Royal Seaport - Now

6. From a brown field area to a sustainable city district
6
Stockholm Royal Seaport - Future

7. Stockholm Royal Seaport Project
• Cities responsible for 2/3 of CO2 emissions
Regional GNP
• Demand for local
energy generation, Population
energy efficiency,
robust power supply,
market models,
regulations,… CO2 equivalent
• Goal: CO2 emissions below 1.5 tons per person by 2020 (today 4.5);
fossil fuel-free by 2030

8. Virtual Micro-Grid Laboratory
Smart House
Micro-Grid Home Automation
System
ZigBee
ZigBee
Smart
Appliances
ZigBee
Residential
Gateway
LTE
4G

9. The Active House in the Royal Seaport
• Smart home appliances and
Mobile services
controllable loads
Billing
meter
• ICT system connects Good night button
Visualization
the active house to power
distribution company and
energy market Controllable outlet Smart dryer
EC
• Energy management system Switch
to reach the high set climate Smart washing machine
goals! Home/away button
Smart dish washer
Control unit Energy meters

10. Energy Efficient Building Control
Standards:
Keep room temperature in
comfort range with a given
probability
Goal:
Minimize energy use
keeping the same level of
service
Method:
Stochastic Model Predictive Control
(SMPC) using weather and occupancy forecasts
• F. Oldewurtel, A. Parisio, C.N. Jones , D. Gyalistras, M- Gweder, V. Stauch, B. Lehmann and M. Morari, "Use of Model Predictive
Control and Weather Predictions for Energy Efficient Building Climate Control", Energy and Building (Elsevier)
• F. Oldewurtel, A. Ulbig, A. Parisio, G. Andersson and M. Morari, Reducing peak electricity demand in building climate control
using real-time pricing and Model Predictive Control, CDC 2010, 49th IEEE Conference on Decision and Control.

11. Stochastic Optimization Problem
energy costs
temperatures weatheruncertainties
energy sourcesforecasts
building dynamics
input constraints
output constraints
: comfort probability level
: prediction horizon

12. Simulation Evaluation
Investigated control strategies:
• PB: ideal controller
• CE: industry standard predictive
controller
• SMPC: uncertainty incorporated
in the controller
Energy use
[KWh/m2]
Amount of violations in thermal comfort
[Kh]
The proposed SMPC strategy outperforms the industry controllers

13. Conclusion
• Smart cities projects in Stockholm, e.g. Stockholm Royal
Seaport
• Need of integrating ICT with advanced control to achieve
climate goals in smart citie
• Accounting for uncertainty necessary to increase control
performance in smart buildings
THANK YOU FOR YOUR ATTENTION
Email: parisio@kth.se
Web: http://www.access.kth.se/