Greening The Internet of Things: Smart Products & People on the Smart Grid

1. Greening The Internet of Things: Smart Products & People on the Smart Grid Alice M. Agogino

2. What is the Smart Grid? Begins with the 2003 Northeast Blackout

3. What is the Smart Grid? Concept Expanded with the 2007 Energy Independence and Security Act

4. Electric Utilities BEFORE Smart Grid • Energy flows one way to customers • Simple interactions and little information flows Joe Hughes, EPRI, NIST Standards Workshop, April 28, 2008

5. Electric Utilities WITH Smart Grid • Energy and information flows to, from & between customers • Multi-stakeholder interactions Joe Hughes, EPRI, NIST Standards Workshop, April 28, 2008

6. Data-Centric View of the Smart Grid • Smart Sensors and Meters • Smart Devices • Computers, printers, appliances, thermal systems, lights, security systems, health monitoring, entertainment • Distributed Energy Generation • Wind, solar panels, micro-hydro, geothermal • Huge Amount of Data Collected, Validated, Corrected, Analyzed, etc. • Data Rates Could be Hourly or Less

7. Energy Generation & Storage View of the Smart Grid Joe Hughes, EPRI, NIST Standards Workshop, April 28, 2008

8. Hourly Day-Ahead Power Price July 2011 in North East U.S. Energy Information Administration (EIA)

9. Wind Energy in Denmark Wind power covers the entire demand for electricity in 200 hours (West Denmark) 2008 Future wind power will exceed demand in more than 1,000 hours Eco-Grid EU – Developing the Prototype of the European Smart Grid, Qiuwei Wu, DTU, CITIRS Workshop, June 23, 2011

10. How Do We Store Energy? Data from Ali Nourai, Electricity Storage Association

11. GM Announces Real-World Smart-Grid EV Pilot http://reviews.cnet.com/8301-13746_7-20081126-48/gm-announces-real-world-smart-grid-ev-pilot/

12. Customer-Centric View Pacific Gas & Electric Example • Save Energy • Increased Quality • Convenient • Feel Safe • Peace of Mind http://www.pge.com/smartmeter/customerstories/anja.shtml

13. Smart Homes, Offices, Cities ZigBeeAlliance

14. Cisco Systems

15. Cows in the Clouds http://www.youtube.com/watch?v=mf7HxU0ZR_Q

16. How to Green the Internet of Things?

17. http://www.couchsurfingori.com/blog/a-couchsurers-view-on-stuff-worldly-posessions/http://www.couchsurfingori.com/blog/a-couchsurers-view-on-stuff-worldly-posessions/

18. http://thetechnologicalcitizen.com/?p=2979 http://www.msnbc.msn.com/id/27668152/

19. http://www.beneficialrc.com/

20. http://www.greenpeace.org/china/en/campaigns/toxics/e-waste

21. Chris Jordan Photographs: Cell Phones Intolerable Beauty: Portraits of American Mass Consumption

22. Chris Jordan Photographs: Cell Phones Chargers Intolerable Beauty: Portraits of American Mass Consumption

23. Chris Jordan Photographs: Junk Intolerable Beauty: Portraits of American Mass Consumption

24. Chris Jordan Photographs: Cars Intolerable Beauty: Portraits of American Mass Consumption

25. Chris Jordan Photographs: Circuit Boards Intolerable Beauty: Portraits of American Mass Consumption

26. Chris Jordan Photographs: More Circuit Boards Intolerable Beauty: Portraits of American Mass Consumption

27. Apple Wants to Kill DVDs http://www.fastcompany.com/1768178/apple-thinks-the-dvd-is-dead

28. Products have shorter lives, yet product offerings are up * Data collected by Dr. Mark Martin for consumer electronics device

29. What Defines a Good Sustainable Product? • It’s sustainable over the product life cycle • It gets used • It satisfies people’s needs and wants and increases the quality of their lives • It doesn’t stand alone but is part of an infrastructure • It meshes with the culture

30. Sustainable Over Product Life Cycle Inputs Materials Energy Water Outputs Materials/ Products Solid Waste Airborne Emissions Waterborne Emissions

31. Sustainable Products Social Needs Human-centered design Uneconomical design Sustainable design Economic Needs Environmental Needs Unadopted designs http://sustainable-engineering.berkeley.edu/

32. Smart Lighting Example

33. Why Smart Lighting? • Lighting accounts for 30% energy use in office buildings

34. Smart Lighting • Potential for lighting management • Energy savings • Up to 25-60% potential savings with energy efficient lighting management technologies • Personal lighting preference & satisfaction • Lighting satisfaction correlates to productivity • Diverse among individuals • Varies with tasks and ages • Market for lighting annually • $12 billion (US) • $ 40 billion (worldwide)

35. New York Times Building • 70% Reduction in Lighting • 30% Daylight Harvesting • 10% Occupancy Sensing • 2% Scheduling • 58% Light Level Tuning • >$300K Savings Per Year

36. Why Retrofit Systems Are Not Adopted or Used? • Exorbitant retrofitting/rewiring cost • Designed only for energy savings – no Human-Centered Design • No accommodation for occupants’ preferences • Lamps wired together can only be controlled identically • Impossible to deliver personalized lighting in open space offices

37. Sustainable Smart Solution • Personalized settings using wireless micro platform • Minimal retrofitting • Extensible to load shedding building technologies • 17-344 environmental improvement

38. Successful Proof of Concept 50% energy savings in pilot implementation Over 70% savings with simulated daylight harvesting

39. High User Satisfaction • Personalized & optimized lighting • Energy efficiency • Ease of adoption “Before this system, I wasted a lot of energy when I was in the office alone. Now when I come into the office, I can adjust the lights to meet my needs while reducing energy consumption at the same time.” – Ryan Shelby

40. AI Behind the Scenes • Influence-Diagrams / Bayes’ Nets • Human-Centered Design • Smart Sensor Platforms • Mote-FVF: Fuzzy Validation and Fusion • Mote-Based Actuation • Optimization and Agents

41. Distributed Architecture • Global Level • Date/Time • Policy Decisions • Regional Level • Regional Decision • Light Actuation • Local Level • Sensor Validation • Sensor Fusion • Personalized Lighting Control

42. Preference Identification: Occupants P(Pi| Ti, Ei) ANOVA for significance of testing results Eprefi Preferred illuminance for each task is midpoint of ‘ideal’ range (used in value function)

43. Preference Testing - Results • No illuminance range proved to be ideal for all four occupants, even though all share the same switch (computer histogram)

44. Preferences: Facilities Management

45. Personalization & Control with Micro Sensor Platforms • Capabilities • Wireless communication • Computation • Sensing/actuation • Data logging • Features • Miniature size • Self-powered • Inexpensive • Network ready Intelligent decision making Mote actuation Office lighting Sensor validation and fusion Mote sensing

46. Mote-based Actuation

47. Measured illuminance Optimized lighting User preferred preference Optimized Lighting 47 • Scenario 2 • 7 present occupants • Preferences are conflicting, balanced • Uses only ~50% of energy • Scenario 1 • 4 present occupants • Preferences can be met perfectly • Uses only ~30% of energy

48. Other Extensions • Energy benefit • $9 billion savings for commercial buildings world-wide per year • Easily adaptable to other lighting technologies • Non-energy benefit • Increased worker productivity • Improve environmental impact of lighting • Mood lighting

49. Future Research • Scaling to Larger Open Space Offices • Add Daylighting & Window Control • Integrate with Heating & Cooling

50. Dual Implementation Sites NASA Ames Green Building Sustainability Base CITRIS (Center for Information Technology in the Interest of Society) Berkeley