MoCho-TIMES -Modal choice within bottom-up optimization energy system models

1. Learnings from MoCho-TIMES - Modal
choice within bottom-up optimization energy
system models
ETSAP Meeting
College Park, 10th -11th July 2017
Jacopo Tattini
PhD Student
Energy System Analysis group

2. Motivation
• Bottom-up (BU) energy system models describe in detail the technical,
economic and environmental dimensions of an energy system
• They are weak in representing consumer behaviour: only one central-
decision maker is considered
• The behavioural dimension is fundamental in decision making in the
transportation sector  It shall not be neglected
• Essential to represent real households’ preferences
2 19 July 2017
Motivation MoCho-TIMES model Discussion
For more info: Venturini et al., Improvements in the representation of behaviour in integrated energy and transport models,
2017 (Under revision)

3. MoCho-TIMES model
• MoCho-TIMES (Modal Choice in TIMES) is an approach to
incorporate modal choice directly in BU optimization energy system models
• The methodology consists in two main steps:
1. Divide transport users into heterogeneous consumer groups
2. Incorporate intangible costs
• Other constraints:
-Monetary budget
-Availability of transport infrastructures
-Travel Time Budget (TTB)
-Travel patterns
-Maximum shift potential
-Maximum rate of shift
3 19 July 2017
For more info refer to working paper: Tattini et al., Improving the representation of modal choice into bottom-up optimization
energy system models – The MoCho-TIMES model, 2017
Motivation MoCho-TIMES model Discussion

4. Demand side heterogeneity
4 19 July 2017
DENMARK
DENMARK
EAST
DENMARK
WEST
URBAN SUBURBAN RURAL URBAN SUBURBAN RURAL
VERYLOWINCOME
MEDIUMINCOME
HIGHINCOME
LOWINCOME
VERYLOWINCOME
MEDIUMINCOME
HIGHINCOME
LOWINCOME
VERYLOWINCOME
MEDIUMINCOME
HIGHINCOME
LOWINCOME
VERYLOWINCOME
MEDIUMINCOME
HIGHINCOME
LOWINCOME
VERYLOWINCOME
MEDIUMINCOME
HIGHINCOME
LOWINCOME
VERYLOWINCOME
MEDIUMINCOME
HIGHINCOME
LOWINCOME
Modes have different
levels of service
Different
perceptions of
levels of service
• Heterogeneity differentiates modal perception among subgroups of transport
users
Motivation MoCho-TIMES model Discussion
Region
Urbanization
area
Income
level
Region
1
Region
2

5. Intangible costs
5 19 July 2017
Intangible costs are introduced for two reasons:
1. To capture other non-economic factors into the expression of the
generalized cost, accounting modal perception
2. To differentiate modal perceptions across consumer groups through
monetization.
Varies across
income classes
Varies across types
of urbanisation
Motivation MoCho-TIMES model Discussion

6. Overall structure of MoCho-TIMES
6 19 July 2017
NON
MOTORIZED
Fuel
ConsumerGroup2
Demands
ConsumerGroup1
ConsumerGroup24
ConsumerGroup3
Travel
time
Infrastructure
EXISTING
INFRA-
STRUCTURE
TRAVEL TIME
BUDGET
Perceived
cost
MONETARY
BUDGET
...
Intangible
cost CG1
Intangible
cost CG24
…
Intangible
cost CG2
PUBLIC
TRANSPORT
Intangible
cost CG1
Intangible
cost CG24
…
Intangible
cost CG2
PRIVATE CAR
Intangible
cost CG1
Intangible
cost CG24
…
Intangible
cost CG2
NEW
INFRA-
STRUCTURE
Motivation MoCho-TIMES model Discussion

7. Data requirement
7 19 July 2017
Motivation MoCho-TIMES model Discussion
• Many new data are required:
– Spatial distribution of the population (region, type of urbanization)
– Income distribution across the population
– Mileage distribution across the population
– LoS attributes: free travel time, congestion travel time, waiting time,
walking time, access/egress time, etc
– Value of time (VoT)
– Infrastructure data: investment and O&M costs, capacity utilization
level
– Travel pattern: share of km in the urban/suburban/rural areas
– Public transport fares
– Car parking cost
– …..
• Need a rich and reliable data-source, consistent with the energy system
model that will incorporate modal choice

8. Support model
• The development of MoCho-TIMES requires a support model:
-Transport model able to simulate modal choice
-Consistent with the geographical scope of the energy system model
• The support model is used to draw data and parameters for MoCho-TIMES
• The transport model might have a different time horizon than the energy
system model  Assumptions required
• In case support model is not available, a travel survey (travel diary) could be
used
8 19 July 2017
Transport Model
Motivation MoCho-TIMES model Discussion

9. Reflections
• Modal choice is determined at aggregated level, for macro clusters of
consumers, but is able to capture variability acorss population
• Dimensions for heterogeneity is crucial
• Finer resolution is achievable, but trade-off trade-off between model size and
representation of the population shall be pursued
• Additional variability to modal perception achieved through the ”clones”
• Vague spatial resolution  Focus is not trip, but entire energy system
• Heterogeneity overcomes the “mean-decision maker” perspective
• Perfect-information, perfect-foresight and perfect-rationality
9 19 July 2017
Motivation MoCho-TIMES model Discussion

10. Shall MoCho-TIMES be incorporated into an
integrated energy system model?
• Modal shift as an option to decarbonize energy system,within a unique
model framework.
• Effect of energy system dynamics on modal shares and vice versa
• Transport sector is expected to become increasingly integrated into
the energy system
• New policy and scenario analyses: effect of variations of LoS and
consumers’ perception of modes on rest of energy system and
viceversa
• Intangible costs act as a barrier to decarbonisation of the transport
sector  Required consistency across sectors
Compare MoCho-TIMES and soft-linking of TIMES with external
transport model (ABM+system dynamic model)
10 19 July 2017
Motivation MoCho-TIMES model Discussion

11. DTU Management Engineering, Technical University of Denmark11
Jacopo Tattini
jactat@dtu.dk
…questions, suggestions?!?!

13. DTU Management Engineering, Technical University of Denmark
Soft link of TIMES-DK and LTM
13
ABM+System
Dynamic
Inputs to ABM+SD model:
• Socioeconomic description:
gender, income class, car
ownership, age, nr. of
children, marital status,
GDP, employment
• Infrastructure: existing and
planned
• Average mode travel cost
• …
Outputs from LTM (2010-2030):
• Passenger travel demand per mode,
location, purpose (pkm)
• Freight travel demand per mode, location,
purpose (tkm)
• ……..
TIMES-DKInterface
Outputs from TIMES-DK:
• Fuels prices
Iterations
Modal choice in LTM and technology choice in TIMES-DK

14. MoCho-TIMES vs Soft-link with external model
Soft link with transport model
Advantages:
• Transport models have suitable
structure and mathematical
expression (MNL) for computing
modal shares
• Spatial disaggregated
• Household/Individual resolution
Disadvantages:
• Long computational time of transport
model
• Low sensitivity to price changes
• Iterations required?
14 19 July 2017
Motivation MoCho-TIMES model Discussion
MoCho-TIMES
Advantages:
• Wider scope of analysis, including
the energy system
• Enables assessing cross-sectoral
influences
• Flexible for scenario analysis
• Catch some variability of preferences
Disadvantages:
• Macro-clusters of consumers
• Aggregated spatial resolution

15. Disaggregated modal shares
15 19 July 2017

16. Disaggregated modal shares
16 19 July 2017

17. Disaggregated modal shares
17 19 July 2017

18. Disaggregated modal shares
18 19 July 2017

19. DTU Management Engineering, Technical University of Denmark19 19 July 2017
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