Urbanization Trends and Patterns, Energy Flows, Energy Security Scenario, Solution: Structured Modelling; Activity Based Demand Models, Integrated Modelling Approaches: Syncity, AMMUA, RTN Model, Service Network Design Models; Urban Ontology, Modelling Framework, Policy Relevance and Use Cases.

1. Global Energy
Consumption Patterns
Assessment Patterns & Modelling Urban Energy
Systems :Activity Based Models Of Demand
Prof. Omkar Parishwad
Asst. Professor,Town Planning
+91 9922952801
ogp.civil@coep.ac.in
Elective II
15/01/2016
URBAN ENERGY SYSTEMS

2. Urban Energy Systems…
▪ Hypothesis: Cities are inefficient in their use of
Energy.
▪ Question: Could u run the city on half the
energy that it consumes and still do the things
that you would like to do, in a city?

3. Why Cities? Urbanization trends..

4. Why Cities? Cities are in flux
and compete..
SizeRank
Cities are competing as much as countries are competing..

5. • Few Mega Cities with <10% of
Urban Population.
• Urban Settlements with less
than 5 lakh >50% of Urban Pop.
• City dwellers use 3x more
energy than Rural dwellers.
Population by Residence and
Settlement Size; Urban Energy..
Source: UN Dept of Economic and Social
Affairs; World Urbanization Prospects.

6. Patterns…
▪ Per capita Energy demand is higher in cities because;
a) High standard of living & more income b) Access to
technical energy (Electricity and refined fuels).
▪ Energy consumption in a city is much more
fluctuating than national average energy (especially
electricity) because cities do not have the big
industrial processes that consume electricity in a day.
▪ Ratio of peak energy to base is changing.Therefore
inefficient production to consumption ratio.

7. Cities are Different

8. Cities are the Same…

9. Todays Cities are inefficient…
Primaryenergyindifferentforms…

10. Energy and Exergy Flows…

11. Patterns…
▪ Exergy = Quantity + Quality ;of energy.
▪ Cities are wasteful in not only the volume of
heat, but also destroy the quality of energy.
▪ Yes, its possible to run the city in 50% amount
of energy. However… its difficult!
▪ Cities are not only inefficient, but are big
polluters as well!
▪ Cities are centers of consumption.

12. Cities pollute directly..

13. Emphasis on air quality…

14. And Indirectly…
Indirectly/Embodied energy (Goods & services, construction materials, etc.)
Energy consumption of the city
Service oriented

15. Direct & Indirect reserves…
50%

16. But energy density provides
opportunities..
W/m2
Area (m2)
Policy Paradox: largest leverage from systems integration, but most
difficult due to policy fragmentation.

17. India’s Energy Security
Scenario’s: Demand & Supply
http://indiaenergy.gov.in/

18. India’s Energy Security
Scenario’s: Flows in the
Indian Energy System (Least effort)

19. India’s Energy Security
Scenario’s: Flows in the
Indian Energy System (Heroic effort)

20. India’s Energy Security
Scenario’s: Land Requirement
A city demands for resources. Since, we don’t use Energy as an end in its own, it’s a
means to some kind of end.

21. India’s Energy Security
Scenario’s: Dependence costs

22. Solution: Structured,
Systematic approach…

23. Modeling approach??
How are cities organized:
▪ Spatial plan of the city, what kind of economic
activities take place; where and in what kind of
buildings do people live; Climatic, geographic
features..
▪ How do people actually interact and behave? How
does their behavior result in energy consumption?
▪ How can we change the way resources flow, are
converted and utilized in a city?
SMART Modelling!!

24. What do we model in a city?

25. Integrated Modelling framework

26. Land Use / Built
Environment

27. Key Capabilities: Spatial
Energy Systems analysis…

28. Key Capabilities: Analysis of
complex Energy chains…

29. Land Use and Built
Environment: Layout Model

30. Smart Design: Layout & Built
Environment_Eco town
Constrained, Livable, low energy design

31. Urban Form & Sprawl vs Smart
Growth
Crucial determinant for transport and total GHG emissions.

32. Toronto: Energy consumption…

33. Layout and Transport…

34. Buildings Life Cycle CO2
emissions & costs per sq.m.

35. Efficiency Improvement potentials
in Thermal retrofit of housing
Frankfurt passive house standards..

36. ABMS: Land Use and Transport

37. People: Results of London
Travel Study

38. Resource Flow /
Conversion Optimization

39. Resource (service) demands

40. RTN Model

41. Low Carbon no-coal City
Lingang New City

42. Energy System Optimization

43. Overall System Design…

44. 50% reduction cost effective

45. Urban Energy transitions…

46. Sustainability Constraints
▪ Energy demand and pollution density
▪ Heat island effect
▪ Capital intensity of infrastructure
investments
▪ Policy paradox
▪ Population vs. Energy demand density.

47. Modelling Urban Energy
Systems
Activity Based Models Of Demand
Shraddha Sule,
Town & Country Planning,
College of Engineering, Pune

48. WHY ACTIVITY BASED DEMAND
MODELS ?
• Cities use energy as a result of human activity
economic, social, recreational etc.
• To understand and model energy use in cities we must
model this human activity
• Human activity is spatially and temporally distributed
and transport facilitates, constrains and modulates all
these activities

49. • How the space is organized: built environment and
it’s functions (activity location); transport system.
• How agents use the space.
• How resource demands vary in space and time.
• What is the best resource inter-conversion technology
and flow network ?
• What is the best engineering service network ?
What do we model in a city ?

50. Integrated Modelling Approach
Four Sub-systems;
• Layout model
• Agent based micro-simulation model of
Urban Activities (AMMUA)
• Resource Technology Network (RTN)
Model
• Service Networks Design Model

51. SynCity is a modelling platform developed by
Imperial College London
SynCity

52. Input
 Spatial
description (i.e
size and location
of discrete zones)
 Available
Building Types
 Available
Transport Modes
 Aggregate
activity demands
Model
 Mixed integer
linear
programme
 Objective: min.
cost, energy or
carbon
 Implemented
with Gams
Output
 Location of
building types
and activities
 Transport
network
structure and
indicative flows
 Estimated costs,
energy and
carbon
consumption
Layout Model

53. AMMUA Model

54. Input
 Spatially and
temporally
resolved pattern of
resource demands
 Available energy
resources
 Available
conversion and
transportation
technologies
Model
 Mixed integer
linear
programme
 Objective:
min. cost,
energy or
carbon
Output
 Resource
distribution
Networks
 Number and
position of
conversion
technologies
and operating
rates
 Total system
cost
RTN Model

55. Service Network Design Model
• Converts a macro-scale network designs
produced by the RTN model in to more detailed
engineering specification
• Concerned with the design of robust urban
power networks that embrace hererogeneity of
generation and conversion and which
incorporate the state of the art in the particular
network type (power, gas heat etc.)

56. SynCity..
An integrated modelling platform in Java
for urban energy system that links the 4
sub-models into one toolkit;
▪ How resource demands vary in space and time.
▪ Three components to SynCity development
▪ Series of demand and supply models.
▪ Unify ontology and database to describe and store
core data objects
▪ Executive to assemble and co-ordinate the running
of modelling scenarios.

57. SynCity
Executive (Java)
Sub -models
(Java and
other)
Core data
objects (Java)
User Application
My SOL DB
UES Ontology

58. Urban Ontology
• A common data model to represent urban concepts and their interactions
Class Description
Space Physical space of city & hinterlands
Agent Occupants of the city(households, firms,
government)
Resource Materials that are consumed, produced
(electricity, water, wastes, petrol, money etc)
Process Convert one set of resources into another set
(e.g. an electrical generator, travel, a storage process)
Technology Physical objects required for processes and agents to
(roads, buildings, urban infrastructure)

59. What all we include in
Integrated Modelling ?

60. Modelling Framework

61. Short term
daily Models
Supply chain
model
Medium term
daily Models

64. Policy Relevance & Use Cases
Scenarios that can be analysed with SynCity
▪ Infrastructure-oriented policies CBA and impact Assessment
for investment
– Demand management policies
– Direct & indirect effects of mobility taxes, smart meters,
– Combined effects of time of day road and electricity pricing
▪ Lifestyle & behavior changes
– Smart choices
– Barriers and enablers
▪ Demographic trends
– Ageing populations, global mobility, fragmentation of families
▪ New developments, technological trends
– Digital / mobile services, LEVs

65. Policy Relevance & Use Cases
Potential Solutions
▪ Engineering solutions
– Optimal design of infrastructures, retrofitting, exploiting synergies
between urban sub-systems (eg CHP)
▪ Technological solutions
– LEVs, smart mobility, smart metering, mobile travel information
- Policies
- Taxation/pricing, carbon credits, incentives,
- Encouraging smarter choices

66. Conclusions…
Integrated modeling of demand and supply vectors in
urban areas;
▪ Layout model introduces potential for supporting re-
zoning and retrofitting policies
▪ ABMS simulates the activities leading to resource
demands bottom-up,
▪ policy sensitive
▪ RTN designs optimum supply networks
Flexible model that can be (easily) transferred.
All urban sub-systems, households and firms, passenger
travel and urban goods and service flows.

67. Thank you for Listening…
http://www.slideshare.net/omkarparishwad/
Special Thanks to Professor Nilay Shah, Imperial College, London;
and "Energy Futures Lab".
https://www.youtube.com/watch?v=AoedCVvOGH8
https://www.youtube.com/watch?v=BEmlRE2YdQE