Conferencia del Dr. Robert Rosner: Energía y desarrollo en las ciudades contemporáneas

Energy Policy Institute at Chicago

H A R R I S S C H O O L O F P U B L I C P O L I C YS T I G L ER C EN T ER

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H A R R I S S C H O O L O F P U B L I C P O L I C YS T I G L ER C EN T E R


H A R R I S S C H O O L O F P U B L I C P O L I C YS T I G L ER C EN T E R

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Urban transformations in an informatics-advanced world facing climate and energy

constraints

Robert Rosner

Energy Policy Institute at Chicago [EPIC] The University of Chicago

Sponors:

Instituto para la ciudad en movimiento Gobierno de la Ciudad de Buenos Aires Consejo Profesional de Ingenieria Civil

2 de Agosto, 2012, Buenos Aires, Argentina



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Preliminaries … •  There are a number of factors that provide the ‘boundary condi9ons’ for how

we should think about the evolu9on of urban environments … –  Increasing urbaniza9on throughout the world –  Growing dispari9es in income, educa9onal achievement and social integra9on

among urban popula9ons, especially in the largest ci9es … –  Broad penetra9on of wireless communica9on technologies –  Development of inexpensive but capable sensor technologies for probing the

environment –  Significant advances in our ability to accumulate and analyze enormous data sets

•  … all in the context of exis9ng urban environments whose physical infrastructure and poli9cal structures were not designed to deal with the present extent and rate of urbaniza9on …

•  … and there are a number of issues that ci9es must (and will) deal with: –  Energy supply and use … –  Environmental management – and the impacts of climate change … –  Service delivery …

Smart Cities Initiative 2



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The ques9on we’d like to address … •  How can the tools of modern informa9cs be used to

–  Op9mize urban energy produc9on and use? –  Minimize urban environmental impacts of energy use? –  Op9mize the delivery of service?

•  The core of our argument is: moderns tools of informa9cs poten9ally allow us to –  Gather informa9on at unprecedented scales, and –  Analyze informa9on at unprecedented scales.

•  Most important, we argue that modern informa9cs allows us to –  Act on the analyses … that is: sense, think, then act, but always subject to the constraints of

•  Public/poli9cal acceptance •  Realis9c economic ‘business case’ •  Legal/regulatory structures (viz., privacy rights, …)




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There are constraints and opportuni9es at all levels … • Huge data volumes for collec9on, storage and analyses

–  Dimensional reduc9on? Data mining? Machine learning? … –  Sensor, transmission costs?

• Rela9ng ‘real world’ problems to technological solu9ons –  Economic considera9ons

• What is the business case? What is the ‘return on investments’ (ROI)? • Who are the stake holders who care about the ROI?

–  Poli9cal considera9ons • Who are the poli9cal ‘stake holders’, and how do they react to ‘solu9ons’?

–  Social considera9ons • What do people really want, and what don’t they want?

–  Legal issue (viz., regulatory environments, privacy rights, …) • Taking advantage of the penetra9on of mobile technologies and social media …




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Before geXng to the specifics … … it’s important to repeat, and keep in mind, that we want to

•  Start with the problems to be solved in modern urban conglomera9ons, •  Iden1fy possible solu9ons, based on

–  Available technology –  Sensible economic analyses, demonstra9ng an ROI acceptable to all stake holders

–  Poli9cal and sociological feasibility •  Deploy solu9ons •  Verify and validate, i.e., carry out an impact analysis …

Why this emphasis? •  Because Smart City ini9a9ves are oZen ‘captured’ by technology vendors, who want to sell, but not necessarily solve …

•  Thus: there is an opportunity for re-‐thinking the rela9onship between natural sciences (and informa9cs) and the social sciences …




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Example 1: Energy use in urban environments …

•  Ci9es are one of the dominant consumers of energy in the world –  This fact, together with the great popula9on density in ci9es, suggests par9cularly

large leverage in deploying energy-‐saving technologies … •  Energy use in urban environs occurs in 2 dominant sectors …

–  Transport sector •  Private and public transport

–  Building sector •  Hea9ng/cooling •  Ligh9ng •  Machinery: light industry, computers, …

•  How might we monitor energy use in the urban environment? –  Transport sector: real-‐9me monitoring via dispersed sensor networks –  Building sector: “smart” grid, embedded and distributed sensors, …

•  How do we deal with the heterogeneity of large urban agglomera9ons? –  For example: how can technology serve as an economic ‘leveler’?

–  Energy-‐saving technologies are oZen viewed as targeted to the well-‐off, not the poor –  Can technologies that sharply lower up-‐front capital costs redress this perceived

imbalance? Smart Cities Initiative 6



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Example 2: The poten9al impact of informa9cs in the urban transport sector …

•  Real-‐9me traffic monitoring, coupled to networked traffic control technologies – Intelligent Transport Systems (ITS) –  “Standard” ITS: What’s already being done …

•  Real-‐9me control of traffic signaling •  Real-‐9me accident/incident management •  Conges9on charge for inner ci9es (e.g., London, UK)

–  “Intrusive” ITS: Going beyond what’s done today … •  Real-‐9me control of access by private transport, for example, real-‐.me control of conges9on pricing (with variable zones, 9me-‐variable pricing, …)

•  Real-‐9me re-‐rou9ng of surface public transport (buses), with integrated use of smartphones for customer rou9ng informa9on

•  “Personaliza9on” of public transport … •  Impacts …

–  Op9mum reduc9on of … •  Conges9on •  Commute 9mes •  Pollu9on




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Example 3: Energy use op9miza9on in the built urban environment

•  Virtually all modern ci9es cons9tute an already ‘built’ environment … –  RetrofiXng of exis9ng structures is usually extremely expensive –  This suggests that energy monitoring of exis9ng building stock take

advantage of •  Wireless technologies – no re-‐cabling of legacy buildings! •  Low-‐speed technologies (‘Internet-‐0’ or ZigBee) – drive down cost per sensor and cost per actuator

– Local vs. centralized control? •  Local control – i.e., distributed architecture – minimizes requirements for communica9ons – consistent with Internet-‐0 & ZigBee technology

•  Local control avoids ‘single-‐point’ failures, inherently isolates faults, allows for incremental implementa9on in legacy environments

•  Local control – coupled to low-‐speed wireless technologies – can be more ‘affordable’, hence has the poten9al of allowing technology penetra9on into lower urban income groups – and indigenous produc9on!

•  Local control may be more amenable to smart phone/cellular service interfacing: Personalized environmental control in the built environment




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•  Ci9es are rarely – if ever – located where ‘renewable’ or ‘green’ energy genera9on technologies make tradi9onal sense …

•  Opportuni9es –  Mo9vates re-‐engineering of na9onal and regional grids

•  For example: systema9c replacement of HVAC with HVDC lines for long-‐distance transmission

–  Coupling remote intermikent ‘renewables’ to an electrified urban transport sector using storage (bakeries?) for cars and buses

Urban rooZop windmills and solar panels (Chicago, IL)

Example 4: “Green” energy deployment in urban environments

•  The public and private urban transport sector as a large-‐scale storage medium for ‘renewables’

–  Local genera9on •  Urban-‐adapted wind turbines … •  Roof-‐top solar … •  Combus9on of urban waste …

Smart Cities Initiative 9 200 MW waste combus9on plant (Trondheim, Norway)



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•  Op9mizing water distribu9on and use in the built environment … –  Clean, potable water is increasingly scarce and expensive … –  Can cellular technology be used to op9mize urban water use?

•  Wireless technology has penetrated most urban environments – and is thus ubiquitous •  Wireless technology avoids the infrastructure disrup9on and costs of wired systems …

–  Wireless water meters – coupled to remotely-‐controlled valves – can be used to •  Meter water use on the individual user level …

–  Poten9ally allow ci9es to charge for water use – on the personal use level –  Early/efficient detec.on and localiza.on of water leaks

•  Regulate water use – poten9ally allow real-‐9me throkling of excessive water use during shortages … the water use equivalent of ‘brown-‐outs’ in the electricity sector

•  This is just an example of the general issue of instrumen.ng urban infrastructure, including the electric grid, the natural gas distribu9on system, the waste collec9on system(s) – and the need to op9mally minimize service interrup9ons, energy use, and environmental impacts …

Example 5: Op9mizing urban water use




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•  A core ques9on is: how do we measure air pollu9on so that we accurately determine human impacts?

– Are sta9onary sensors sufficient? • How do sta9onary sensor measurements correlate with the ‘lived’ pollu9on exposure of typical urban dwellers?

• What is the distribu9on func9on of pollu9on exposure – possibly as a func9on of urban loca9on?

•  Example: Real-‐9me sensing of ambient air quality in the ‘lived’ environment

– Deploy portable networked air quality sensor using city employees •  City workers can provide a high-‐quality reference set of city dwellers’ air quality experience over a large part of the urban environment …

•  This allows iden9fica9on of air pollu9on ‘hot spots’ in real 9me – Respond to pollu9on ‘hot spots’ by re-‐direc9on of human and/or vehicle traffic

Example 6: Managing urban air pollu9on




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What do all these poten9al advances have in common?

•  A fully ‘instrumented’ urban environment –  Enabled by technology advances in component miniaturiza9on, wireless

communica9ons, communica9on protocols, … •  Capacity to store and analyze – if needed, in real .me – extremely large

data sets –  Enabled by the revolu9on in massively parallel compu9ng, cloud technologies, …

Image copyright & courtesy SOM (2012)

•  Implementa.on capacity –  Capture and analysis of informa9on is

ul9mately useless unless one has the capability to act on the gathered informa9on

–  But: Field experience to date is sparse – pilot projects are cri9cal first steps!

•  THUS: we need urban pilot projects! –  Example: The ‘Lakeside Project’ in Chicago …




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The Chicago Lakeside Ini9a9ve … •  Site of former US Steel plant •  ~600 acres, landfill •  Former ‘brown field’, now cleaned … •  3 partners: McCaffery Interests, US Steel, & Chicago Lakeside Development LLC


Lakeside Today

•  ~14,000 dwelling units •  ~17,500,000 square feet commercial space

–  Light industry, shopping, … •  Schools, ‘informal’ educa9on, … •  Technology leader: district energy, low waste, highly connected, … Lakeside in 2030



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Final thoughts … •  “Smart City” ini9a9ves typically focus on technology – and tend to

be weak on the social sciences –  How does the inser9on of ‘smart city’ enclaves into an exis9ng urban

environment modify that exis9ng environment? –  How do these perturba9ons of exis9ng urban environments depend on the

scale of a ‘smart city’ enclave ? –  How does informa9on technology interact with social sciences?

•  Urban problems are rarely only technological … •  Can informa9on technology address problems that urbanologists – urban sociologists, anthropologists … – have iden9fied … as opposed to solving technology challenges that natural scien9sts are used to solve …

–  This perspec9ve can lead to a new paradigm in the natural science/social science interac9on …

•  Can urban issues serve as the ‘playground’ in which we explore the use of natural science ‘tools’ in the social sciences?

–  Data mining, dimensional reduc9on, machine learning? Smart Cities Initiative 14



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… which brings us to ques9ons and discussion


Documents

Conferencia del Dr. Robert Rosner: Energía y desarrollo en las ciudades contemporáneas