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Energy Efficiency and Intelligent Cities

Energy Efficiency and Intelligent Cities. Simon Roberts Foresight, Innovation & Incubation Group. Arup. designers. we shape a better world. world map of offices. offices in US. Simmons Hall. Simmons Hall, MIT, Massachusetts, USA. Campus. Arup Campus, West Midlands. BedZED.

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Energy Efficiency and Intelligent Cities

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  1. Energy Efficiency and Intelligent Cities Simon Roberts Foresight, Innovation & Incubation Group

  2. Arup

  3. designers

  4. we shape a better world

  5. world map of offices

  6. offices in US

  7. Simmons Hall Simmons Hall, MIT, Massachusetts, USA

  8. Campus Arup Campus, West Midlands

  9. BedZED Beddington Zero Energy Development (BedZED)

  10. Oresund Link Øresund Link, Denmark - Sweden

  11. Druk White Druk White Lotus School, Ladakh, Northern India

  12. Drivers of Change

  13. 2006.driversofchange.com

  14. Audio PowerPoints

  15. Global View

  16. Limits to Growth (1972) • Jay W Forrester • Systems Dynamics Group • Sloan School of Management • MIT • Dennis Meadows • analyze long term causes and consequences of growth in population and material economy

  17. System Dynamics D Meadows et al

  18. Population and Industrial Capital D Meadows et al

  19. Flops and Watts • Each scenario • 6-monthly steps • for 200 years (1900-2100) • Hardware: • 1971 mainframe computer 10-15 min/scen. • 1991 desktop computers 3-5 min/scen. • 2001 laptop 4 s/scen.

  20. Outputs D Meadows et al, LTG-30YU, p244-

  21. Overshoot – What Type? or D Meadows et al

  22. Outputs D Meadows et al

  23. 2. New Cities

  24. Dongtan on China coast

  25. Dongtan

  26. Vision

  27. Scale

  28. Components of Urban Area

  29. Sim City Pro? www.os2world.com

  30. Architecture of Models B C A selected performance Indicators scenarios Inputs ‘Hub’ Outputs D F E technical model subcomponents (A – F)

  31. Influence Flowchart

  32. Resource Flows and Sustainability What should we measure as model outputs? • Air emissions (NOx, SOx, Particulates) • Imports / Exports • Demand for land (External / Internal) • Job creation • Financial / economic viability • Reduction, reuse, recycling • Water / fossil & non-fossil CO2 emissions • Waste consumption • Energy consumption generation (by components)

  33. Wildlife

  34. 3. Old Cities

  35. Problem: Oil?

  36. Oil and Natural Gas 2005

  37. “Peak Oil” and Natural Gas 2005 Colin Campbell

  38. What Should We Build Next? • Creationofcapital… • …is when we have options • How do we evaluate these capital creation options? ECCapO Model

  39. Embodied Energy - Nuclear Power Jan Willem Storm van Leeuwen

  40. ECCO Model

  41. Industry Sector One loop Capital Stock Thermal Energy Primary Energy Output LESS Investment in Other Sectors LESS Consumption LESS Exports

  42. Aim • model of London… • …within model of the UK • calibrated over 1985-2005 • run forward for 2005-2025 • using scenarios • “Peak Oil”: early or late • behaviour: reactive or proactive

  43. “Energy Efficiency and Intelligent Cities” • Models for Cities • What are the intelligent options for cities so they can prepare for: • Peak Oil • declining natural gas • and move to: • becoming carbon neutral

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