Post on 20-Oct-2014
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Francesco Rizzi f.rizzi@sssup.it
Madrid, 2013-12-16
Action COST “People friendly cities in a data rich world” WG 2 “Knowledge platform”
New urban environments: an enterpreneurial perspective
pag. 2!
Big cities: a valuable business environment
Chapter 1: The state of the planet page 59
IVORY COAST
8.6
PERU21.073%
CANADA26.380%
ROMANIA11.6
54
BEIJING12.7
SHANGHAI17.3
GUANDONG7.3
CHINA559.242%
INDIA329.329%
AUSTRALIA18.389%
BANGLADESH38.226%
INDONESIA114.150%
JAPAN84.766%
N KOREA14.162%
S KOREA39.081%
MALAYSIA18.169%
MYANMAR16.532%
THAILAND21.533%
VIETNAM23.327%
PHILIPPINES55
64%
PAKISTAN59.336%
SEOUL23.2 OSAKA
16.6
MANILA15.4
TOKYO33.4
DHAKA13.8
KOLKATA15.5
UZBEKISTAN10.137%
KAZAKH-STAN8.6
SYRIA10.251%
IRAN48.468%
IRAQ 20.367%
SAUDI ARABIA20.981%
TURKEY51.168%
AFGHAN-ISTAN
7.8
UKRAINE30.968%
RUSSIA103.673%UK
5490%
SWEDEN7.6
NETHERLANDS13.381%
BELGIUM10.297% CZECH
REPUBLIC7.4
FRANCE46.977%
GERMANY62
75%
ITALY39.668%
POLAND23.962%
SPAIN33.677%
US246.281%
NEW YORK21.8
LOS ANGELES
17.9
LONDON12
MEXICO84.392
77% MEXICO
CITY22.1
MOSCOW13.4
MUMBAI21.3
LAGOS10.0
ANGOLA9.3
ALGERIA22.0
MOROCCO19.460%
NIGERIA68.650%
MOZAM-BIQUE
CAMEROON9.5
CONGO, DR OF20.233%
EGYPT33.143%
ETHIOPIA13
16%GHANA
11.349%
KENYA7.6
TANZANIA9.925%
S AFRICA28.660%
SUDAN16.343%
TUNISIA
BRAZIL162.685%
ARGENTINA35.690%
COLOMBIA34.373%
VENEZUELA26
94%
CHILE14.688%
RIO DE JANEIRO
12.2
BUENOSAIRES13.5
SÃO PAULO20.4
TEHERAN12.1
NEW DELHI21.1
KARACHI14.8
ISTANBUL11.7
CAIRO15.9
JAKARTA14.9
IVORY COAST
8.6
PERU21.073%
CANADA26.380%
ROMANIA11.6
54
BEIJING12.7
SHANGHAI17.3
GUANDONG7.3
CHINA559.242%
INDIA329.329%
AUSTRALIA18.389%
BANGLADESH38.226%
INDONESIA114.150%
JAPAN84.766%
N KOREA14.162%
S KOREA39.081%
MALAYSIA18.169%
MYANMAR16.532%
THAILAND21.533%
VIETNAM23.327%
PHILIPPINES55
64%
PAKISTAN59.336%
SEOUL23.2 OSAKA
16.6
MANILA15.4
TOKYO33.4
DHAKA13.8
KOLKATA15.5
UZBEKISTAN10.137%
KAZAKH-STAN8.6
SYRIA10.251%
IRAN48.468%
IRAQ 20.367%
SAUDI ARABIA20.981%
TURKEY51.168%
AFGHAN-ISTAN
7.8
UKRAINE30.968%
RUSSIA103.673%UK
5490%
SWEDEN7.6
NETHERLANDS13.381%
BELGIUM10.297% CZECH
REPUBLIC7.4
FRANCE46.977%
GERMANY62
75%
ITALY39.668%
POLAND23.962%
SPAIN33.677%
US246.281%
NEW YORK21.8
LOS ANGELES
17.9
LONDON12
MEXICO84.392
77% MEXICO
CITY22.1
MOSCOW13.4
MUMBAI21.3
LAGOS10.0
ANGOLA9.3
ALGERIA22.0
MOROCCO19.460%
NIGERIA68.650%
MOZAM-BIQUE
CAMEROON9.5
CONGO, DR OF20.233%
EGYPT33.143%
ETHIOPIA13
16%GHANA
11.349%
KENYA7.6
TANZANIA9.925%
S AFRICA28.660%
SUDAN16.343%
TUNISIA
BRAZIL162.685%
ARGENTINA35.690%
COLOMBIA34.373%
VENEZUELA26
94%
CHILE14.688%
RIO DE JANEIRO
12.2
BUENOSAIRES13.5
SÃO PAULO20.4
TEHERAN12.1
NEW DELHI21.1
KARACHI14.8
ISTANBUL11.7
CAIRO15.9
JAKARTA14.9
Figure 38: The number of people living in cities in each country of the world in 2010, together with the percentage of the population in countries with large urban populations.In the developed world, the proportion of people living in cities is typically higher than 75%, and often exceeds 85%. The largest urban population in the developed world is in the USA (246 million). However, in China, even though the proportion of people living in cities is under 50%, the total number of urban dwellers is greatest (559 million). In India, by comparison, the number is 329 million (UN population division). (Figure drawn by the World Business Council for Sustainable Development in WBCSD, 2012, based on data from the UN Population Division UN, 2010)
TODAY’S URBAN POPULATION:
3,307,905,000Key
Cities over 10 million people (greater urban area)
Predominantly urban 75% or over
Predominantly urban 50 - 74%
Urban 0 - 49%
IN 2050, TWO OUT OF EVERY THREE PEOPLE WILL LIVE IN A CITY (UN, 2009)
Number of people that live in cities and percentage of inhabitants in big cities (2010). Source: WWF, 2012 !
pag. 3!
The problem
Public debt (%GDP)
Source: Wikipedia on data from Eurostat (2012) and US.CIA (2013)
pag. 4!
The challenge
How to do better things
Without increasing costs?
pag. 5!
The opportunity
City = platform
For an efficient use of
resources
pag. 6!
The value of data
pag. 7!
pag. 8!
Smart meters: lessons learnt
pag. 9!
20 IEEE power & energy magazine january/february 2010
system engineering, assisted by an array of new approaches, technologies and applications, allows the existing grid to tra-verse the complex yet staged trajectory of architecture, proto-cols, and standards towards the smart grid.
Smart Grid DriversAs the backbone of the power industry, the electricity grid is now the focus of assorted technological innovations. Utilities in North America and across the world are taking solid steps towards incorporating new technologies in many aspects of their operations and infrastructure. At the core of this trans-formation is the need to make more effi cient use of current assets. Figure 4 shows a typical utility pyramid in which asset management is at the base of smart grid development. It is on this base that utilities build a foundation for the smart grid through a careful overhaul of their IT, communication, and circuit infrastructure.
As discussed, the organic growth of this well-designed layer of intelligence over utility assets enables the smart grid’s fundamental applications to emerge. It is interesting to note that although the foundation of the smart grid is built on a lateral integration of these basic ingredients, true smart grid capabilities will be built on vertical integration of the upper-layer applications. As an example, a critical capability such as demand response may not be feasible without tight integration of smart meters and home area networks.
As such, one may argue that given the size and the value of utility assets, the emergence of the smart grid will be more likely to follow an evolutionary trajectory than to involve a
drastic overhaul. The smart grid will therefore materialize through strategic implants of distributed control and moni-toring systems within and alongside the existing electric-ity grid. The functional and technological growth of these embryos over time helps them emerge as large pockets of distributed intelligent systems across diverse geographies. This organic growth will allow the utilities to shift more of the old grid’s load and functions onto the new grid and so to improve and enhance their critical services.
These smart grid embryos will facilitate the distributed generation and cogeneration of energy. They will also pro-vide for the integration of alternative sources of energy and the management of a system’s emissions and carbon foot-print. And last but not least, they will enable utilities to make more effi cient use of their existing assets through demand response, peak shaving, and service quality control.
The problem that most utility providers across the globe face, however, is how to get to where they need to be as soon as possible, at the minimum cost, and without jeopardizing the critical services they are currently providing. Moreover, utilities must decide which strategies and what road map they should pursue to ensure that they achieve the highest possible return on the required investments for such major undertakings.
As is the case with any new technology, the utilities in the developing world have a clear advantage over their counter-parts in the developed world. The former have fewer legacy issues to grapple with and so may be able to leap forward without the need for backward compatibility with their exist-ing systems.
Intelligent Grid
Digital
Two-Way Communication
Distributed Generation
Network
Sensors Throughout
Self-Monitoring
Self-Healing
Adaptive and Islanding
Remote Check/Test
Pervasive Control
Many Customer Choices
Existing Grid
Electromechanical
One-Way Communication
Centralized Generation
Hierarchical
Few Sensors
Blind
Manual Restoration
Failures and Blackouts
Manual Check/Test
Limited Control
Few Customer Choices
figure 1. The smart grid compared with the existing grid.
Increasin
g Capabilit
ies
DistributionAutomation
End-to-EndCommunication
DataManagement
UtilityApplications
The first
step in
the evo
lution of th
e electricit
y
grid st
arts at th
e distrib
ution si
de, enablin
g
new applicatio
ns and operatio
nal effic
iencies
to be intro
duced in
to the sy
stem.
figure 2. Utility-desired capabilities.
Regardless of how quickly various utilities embrace smart grid concepts, technologies, and systems, they all agree on the inevitability of this massive transformation.
12
the catalogue fall in the Smart Meters category; these projects involve the installation of more than
40 million devices for a total investment of around €3 billion. Estimates forecast about 240 million
smart meters to be installed by 2020 [Pike Research, 2011].
AT
6.1%
BE
4.2%
DE
11.1%
DK
22.0%
EL
2.0%
ES
8.7%
FI
1.5%
FR
4.2%
IE
2.4%
IT
5.5%
NL
6.8% PT
2.4%SE
5.0%
UK
6.8%
SK 0.7%
SI 3.1%
RO 0.6%
PL 1.7%
MT 0.4%
LV 0.7%
LT 0.4%
HU 1.1%
EE 0.2%
CZ 1.7%
CY 0.4%
BG 0.4%
Others 11.3%
Figure 2. Distribution of projects between EU15 and EU12 Countries
Figure 3 - Geographical distribution of investments and project categories
EU12 Member States: Bulgaria, Cyprus, Czech Republic, Estonia, Hungary, Latvia, Lithuania, Malta, Poland, Romania, Slovakia, Slovenia
Source: EC-JRC USA-DOE
Who can do that?
Smart meters: lessons learnt
pag. 10!
Successes and failures
pag. 11!
Successes and failures
pag. 12!
The theoretical perspective
pag. 13!
Last 20 years of inventions in the field of RESs
Bold: Belgium, Denmark, France, Germany, Greece, Italy, Netherland, Spain, Sweden, Switzerland, United Kingdom
Italic: World regions with the exclusion of Europe, North America, West Asia
Isomorphism threats & the opportunities for smart communities
pag. 14!
Characteristics of the problem
Focal agent’s need for distant search
Reliability of the crowd as problem solver
Evaluability of the solutions
Pervasiveness of the information platform
Ease
of d
elin
eatio
n an
d tr
ansm
issio
n
Mod
ular
izab
ility
of th
e pr
oble
m
Effe
ctive
dist
ance
of k
now
ledg
e
Taci
tnes
s an
d co
mpl
exity
of t
he s
olut
ion
Perv
asive
ness
of k
now
-how
in th
e cr
owd
Mot
ivatio
ns o
f pot
entia
l sol
vers
Nat
ure
of th
e so
lutio
n N
uber
of e
valu
ator
s
Afuah, A., & Tucci, C. L. (2012). Crowdsourcing as a solution to distant search. Academy of Management Review, 37(3), 355-375.!
Crowdsourcing: the alternative way
pag. 15!
Crowdsourcing and urban sustainability governance
pag. 16!
Crowdsourcing and urban sustainability governance
pag. 17!
Francesco Rizzi Istituto di Management Scuola Superiore Sant’Anna f.rizzi@sssup.it