Energy Technology Roadmap & Energy Technology Roadmap &
StakeholderStakeholder PerspectivesPerspectives
SIXTH FRAMEWORK PROGRAMME[6.1]
[ Sustainable Energy Systems]
Stefan Hirschberg, Paul Scherrer InstitutBrussels, 17 February 2009
The NEEDS Integrated Project(Where does RS2b fit in?)
NEEDS: New Energy Externalities Developments for Sustainability
Extend
geographic
coverage
Communicate
& Disseminate
Externalities
in energy
extraction &
transport
New & improved methods to
estimate external costs
LCA/costs of
new
technologies
Model internalization
strategies & scenario
building
1d
Transfer &
general-
ization
1c
1a
2b
3a
3b
1b
2a
Energy technology
roadmap & forecast
Integration
Stakeholder assess-
ment & acceptance
NEEDS RS2b Objectives
General - Combine technology knowledge with stakeholder preferences, examining
Robustness of results for different stakeholders
Specific
Stakeholder acceptance of external costsassessed
Sustainability of technologies
Sensitivity to stakeholder preference patterns
Identify robust (and/or promising) technologies
Stream Structure and Status
External costs
acceptabilityTechnology Assessment
under stakeholder perspectives
Survey I
(WP12&13)
Case study
Acceptability
of monetary
values
(WP11)
Establishment of
criteria & indicators
Review (WP1)
Social (WP2)
Full set (WP3)
Survey II (WP12&13)
Quantification of
Indicators
Economy (WP5)
Environment (WP6)
Risks (WP7)
Social (WP8)
Documentation
Multi-criteria
decision analysis
Requirements (WP9)
Sensitivities (WP4)
Developments,
Implementation
& Evaluation (WP10)
Inputs from
RS1a
Inputs from
RS1a & RS1b
Case Study and Surveys
• Case study:
- the acceptability of monetary valuation methods and
- their role in the energy policy making processes in France, UK and US.
• Three “surveys” with stakeholder participation:
- Acceptability of the externality framework, evaluation of results and their uses
- Selection of evaluation criteria and indicators
- Elicitation of stakeholder preferences leading to multi-criteria sensitivity mapping of technological options
Case Study Conclusions
• Large variation between France, UK and US in the uses of externality valuation in policy
• Formal requirements are crucial in order to consider the full costs and benefits of proposed regulation
• There is more extensive use of the monetary valuation of externalities in transport and water policy than in the energy sector
Main Stakeholder Categories
Each category is further divided into several sub-categories
Other
Consultant
Researcher / Academic
Politician
Association (e.g. trade or industry)
Regulator / Government Authority
Government Energy or Environmental Agency
Non-Governmental Organization (NGO)
Energy Consumer
Energy Supplier
Stakeholder Categories & Sub-categories1/4
Energy Demand• Technology Supplier (e.g. Manufacturer of Appliances
• Energy Consuming Industry
• Agriculture
• Transport Sector
• Services
• Households
• Technology Agency
• Sectoral Association
Energy Supply• (Centralized or Decentralized)
• Manufacturer
• Technology Agency
• Transmission & Distribution
• Sectoral Association
Regulators / Authorities• European
• National
• Regional / Local
Governmental Energy & Environmental Agencies• European
• National
• Regional / Local
NGOs• International
• European
• National
Stakeholder Categories & Sub-categories2/4
Researchers• Energy
- Fossil
- Renewables
- Nuclear
- Demand
- Systems Analysis
- Other
• Non-Energy
Consultants• Small or Medium (1 – 30 employees)
• Large (> 30 employees)
Stakeholder Categories & Sub-categories3/4
Associations• European
• National
• Regional / Local
Politicians• Left / Green(Socialist Group, Group of the Greens / European Free Alliance, Confederal Group of the European United Left)
• Center / Liberal(European People's Party and European Democrats, Alliance of Liberals and Democrats)
• Right / Conservative(Independence/Democracy Group, Union for Europe of the Nations Group)
Stakeholder Categories & Sub-categories 4/4
Justified and Non-Justified Stakeholder Criticisms of External Costs
• Monetisation as such is not accepted by all.
• Alternatives to Willingness to Pay (WTP) are preferred.
• The way WTP estimates are generated is questionable.
• Very large overall uncertainties mean non-robust rankings.
• The history of cost estimates is troublesome.
• Estimates of specific external costs often questionable; for some with potential importance they are not available.
• Social factors are scarcely represented.
• It is impossible and/or meaningless to monetise some of the social factors.
Survey I: Evaluating Monetisation
Source: Faberi et al., 2007
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Loss of human lives Loss of biodiversity Damage to ecosystems Global warming
No opinion/don't know
Monetisation is impossible as a matter of principle
Monetisation may be possible, but problematic
Monetisation is possible, but values too uncertain
Monetisation is possible
17% skipped these questions
Survey I: Evaluating Monetisation
Source: Faberi et al., 2007
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Nuclear Proliferation Security against
terrorism
Nuclear waste storage Security of electricity
supply
No opinion/don't know
Monetisation is impossible as a matter of principle
Monetisation may be possible, but problematic
Monetisation is possible, but values too uncertain
Monetisation is possible
17% skipped these questions
Survey I: Usefulness of Externalities
Source: Faberi et al., 2007
Statement: External cost assessment provides decision makers with basic estimates to support their policy decisi ons. Without such estimates, the social cost of a wrong choice c ould be very large and harmful.
0% 10% 20% 30% 40% 50% 60%
Mostly agree
Fully agree
Fully disagree
Mostly disagree
I don't know
Survey I: Externality Concept, Results and Uses
In spite of the limitations, there is general accep tance of the concept of externalities, of the internalisation of external c osts and of most results, but…
0% 10% 20% 30% 40% 50% 60%
Coal and oil technologies have thelowest external costs
Natural gas technologies have quitelow external costs due to low air
pollution and moderate external costsdue to greenhouse gases.
Renewable technologies have mostlylow external costs
Nuclear energy has low external costs
I don’t know Fully agree Mostly agree Mostly disagree Fully disagree
Source: Faberi et al., 2007
What is Multi-Criteria Decision Analysis (MCDA) and why is it necessary?
• Decision support through the combination of many criteria, based on decision-maker/stakeholder preferences
• Cognitive limitations (7 criteria average max.)
• Comparison to monetisation (damage costs v. control costs v. market cost v. individual’s…)
• Reconciling preferences with preconceptions…
Balancing Tradeoffs - Terminology
Discrete
alternatives
may be either
individual
technologies,
or utility
strategies
Environment
Eco
no
my
7 Steps Towards MCDA7 Steps Towards MCDA
1 Select alternatives (with stakeholder input)
2 Establish criteria and indicators (with stakeholder input)
3 Quantify the technology- and country-specific indicators
4 Analyse the MCDA requirements
5 Select the most suitable MCDA method(s) and tool(s)
6 Test and adapt the selected method(s) and tool(s)
7 Elicit stakeholder preferences, provide feedback
MCDA-based Aggregation :General Algorithm
Sustainability Criteria
Sou
rce: Hirschbe
rg et a
l., 200
7&20
08
Criterion
RESOURCES Energy Resources
Mineral Resources (Ores) CLIMATE CHANGE
IMPACT ON ECOSYSTEMS
Impacts from Normal Operation Impacts from Severe Accidents WASTES
Special Chemical Wastes stored in Underground Depositories
EN
VIR
ON
ME
NT
AL
DIM
EN
SIO
N
Medium and High Level Radioactive Wastes to be stored in Geological Repositories
IMPACTS ON CUSTOMERS Price of Electricity IMPACTS ON OVERALL ECONOMY Employment
Autonomy of Electricity Generation IMPACTS ON UTILITY Financial Risks
ECO
NO
MIC
DIM
EN
SIO
N
Operation
SECURITY/RELIABILITY OF ENERGY PROVISION Political Threats to Continuity of Energy Service
Flexibility and Adaptation POLITICAL STABILITY AND LEGITIMACY
Potential of Conflicts induced by Energy Systems. Necessity of Participative Decision-making Processes SOCIAL AND INDIVIDUAL RISKS
Expert-based Risk Estimates for Normal Operation Expert-based Risk Estimates for Accidents Perceived Risks
Terrorist Threat QUALITY OF RESIDENTIAL ENVIRONMENT Effects on the Quality of Landscape
SO
CIA
L D
IME
NS
ION
Noise Exposure
Risk-relevant Criteria & Indicators (NEEDS) 1/2
Source: NEEDS Project; Hirschberg et al., 2007
Risk-relevant Criteria & Indicators (NEEDS) 2/2
Sou
rce: NEEDS Project; H
irschbe
rg et a
l., 200
7
Q5: Main stakeholder categories
Survey II: Stakeholder Profile
• Researcher/Academia strongly dominated (61.45%)
• Only three other categories were between 5 and 10 %
-Energy Supplier
- Government Energy & Environmental Agency
- Consultant
• Within Researcher/Academia five sub-categories had the
strongest representation:
- Energy: Renewables (9.45%)
- Energy: Nuclear (11.64%)
- Energy: Systems Analysis (19.27%)
- Energy: Other (6.18%)
- Non-Energy (11.27%)
Source: Burgherr et al., 2008
Survey II on Sustainability Criteria and Indicators
• Response rate of 9.7%
• Highly qualified / educated participants, but an over-representation of researchers
• General acceptance of indicator set
• Few individual indicators considered problematic
• Strong minority (44%) opts for less criteria; i.e. about 20
• Most participants from CH followed by DE
� Small number of indicator descriptions were slightly modified
� 4 indicators from the social dimension were eliminated giving a final set of 36
Survey II: Feedback
Q49: 5 most important indicators to be absolutely INCLUDED
5119Impacts of toxic substances
Environment
7226Mortality due to normal operation
Social
7828Independence from energy imports
Economy
8029Impacts of air pollution Environment
12144Average generation cost
Economy
17463Consumption of fossil resources
Environment
18367Global warming potential
Environment
PARTICIPANTS
N°
PARTICIPANTS %
INDICATORCATEGORY
Survey II: Feedback
Q50: 5 least important indicators to be absolutely EXCLUDED?
Source: Burgherr et al., 2008
4717Willingness of NGOs and others to act against the realization of an option
Social
5520Total traffic loadSocial
5620Subjective health fears due to normal operation
Social
6423Psychometric variables: personal control, catastrophic potential, perceived equity familiarity
Social
6724Construction timeEconomy
7126Share of the electricity costs in the budget of a social welfare recipient
Social
11140Work qualifications: workforce education
Social
PARTICIPANTS
N°
PARTICIPANTS %
INDICATORCATEGORY
Technology Range
• 24MW turbine in deep water• Offshore wind turbineWIND
• Cells - Crystalline silicon (ribbon)
• Thin film (Cadmium Telluride)
• Concentrating trough collectors
• Photovoltaics
- Centralised and decentralised
• Centralised thermal power plant
SOLAR
• Gasified waste wood to fuel cells.
• Gasified cultivated wood and waste straw to gas turbine.
• Decentralised cogeneration
- Fuel cells.
- Gas turbine.
BIOMASS
• Conventional and gasification
- with/without carbon capture (CCS)
� Post-combustion
� Oxyfuel
• Internal combustion engine (NG)
• Molten carbonate and solid oxide fuel cells (NG)
Centralised
• Coal
• Lignite
• Natural Gas (NG).
Decentralised cogeneration
• Natural Gas only (NG)
FOSSIL
• European Pressurised Reactor (EPR – GEN III)
• European Fast Reactor (EFR- GEN IV)
• Generation III
• Generation IV
NUCLEAR
Total of 26 for FR, 25 for DE, 21 for IT and 19 for CH
The MCA Indicator Database
NEEDS Database Adjustments
• Fossil: Thermal efficiencies depend on ambient air temperature causing lower values in Italy
• Lignite: FR & DE only; heating value adjusted
• Natural gas: Country specific import mix
• Biomass: Poplar irrigation & yield higher in Italy
• Solar & Offshore wind: Hours/year adjusted
• Solar thermal: FR & IT only
• Nuclear: Site specific risk
• LCA: Generic but country specific
Environment:GHG Emissions (2050)
Source: Bauer et al., 2008
Nuclear Fossil Renewablekg
(C
O2-
eq.)
/ kW
h
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
EU Pressurised Reactor
EU Fast Reactor
Pulverised Coal (PC)
PC & Post comb.CCS
PC & OxyfuelCCS
Integrated Gasification
Int. Gasification & CCS
Pulverised Lignite (PL)
PL & Post comb.CCS
PL & Oxyfuel& CCS
Integrated Gasification
Int. Gasification & CCS
Combined Cycle (CC)
CC & Post comb. CCS
Internal Comb. <1MW
MC Fuel cell 2MW
SO Fuel cell <1MW
MC Fuel cell <1MW
MC Fuel cell <1MW
SRC Poplar 9MW
Waste straw 9MW
PV, large scale
PV, small scale
PV, Thin-film
, small sc.
Thermal power plant
Offshore 24MW
GEN
III
GEN
IV
COAL LIGNITE NAT. GAS NAT. GAS
Cogeneration
BIOMASS
Cogeneration
SOLAR WIND
IT DE CH FR
Environment:Non-energetic Resource Consumption (2050)
Source: Bauer et al., 2008
Nuclear Fossil Renewablekg (Sb-eq.) / kW
h
0.E+00
1.E-06
2.E-06
3.E-06
4.E-06
5.E-06
EU Pressurised Reactor
EU Fast Reactor
Pulverised Coal (PC)
PC & Post comb.CCS
PC & OxyfuelCCS
Integrated Gasification
Int. Gasification & CCS
Pulverised Lignite (PL)
PL & Post comb.CCS
PL & Oxyfuel& CCS
Integrated Gasification
Int. Gasification & CCS
Combined Cycle (CC)
CC & Post comb. CCS
Internal Comb. <1MW
MC Fuel cell 2MW
SO Fuel cell <1MW
MC Fuel cell <1MW
MC Fuel cell <1MW
SRC Poplar 9MW
Waste straw 9MW
PV, large scale
PV, small scale
PV, Thin-film
, small sc.
Thermal power plant
Offshore 24MW
GEN
III
GEN
IV
COAL LIGNITE NAT. GAS NAT. GAS
Cogeneration
BIOMASS
Cogeneration
SOLAR WIND
IT DE CH FR
Environment:Accidental Radioactive Contamination (2050)
Source: Burgherr & Hirschberg., 2008
km2/ GW
e-yr
Nuclear Fossil Renewable
0.E+00
1.E-05
2.E-05
3.E-05
4.E-05
5.E-05
6.E-05
7.E-05
EU Pressurised Reactor
EU Fast Reactor
Pulverised Coal (PC)
PC & Post comb.CCS
PC & OxyfuelCCS
Integrated Gasification
Int. Gasification & CCS
Pulverised Lignite (PL)
PL & Post comb.CCS
PL & Oxyfuel& CCS
Integrated Gasification
Int. Gasification & CCS
Combined Cycle (CC)
CC & Post comb. CCS
Internal Comb. <1MW
MC Fuel cell 2MW
SO Fuel cell <1MW
MC Fuel cell <1MW
MC Fuel cell <1MW
SRC Poplar 9MW
Waste straw 9MW
PV, large scale
PV, small scale
PV, Thin-film
, small sc.
Thermal power plant
Offshore 24MW
GEN
III
GEN
IV
COAL LIGNITE NAT. GAS NAT. GAS
Cogeneration
BIOMASS
Cogeneration
SOLAR WIND
IT DE CH FR
Social:Years Of Life Lost - YOLL (2050)
Source: Friedrich & Preiss, 2008
Nuclear Fossil RenewableYOLL / kW
h
0.E+00
1.E-07
2.E-07
3.E-07
4.E-07
5.E-07
EU Pressurised Reactor
EU Fast Reactor
Pulverised Coal (PC)
PC & Post comb.CCS
PC & OxyfuelCCS
Integrated Gasification
Int. Gasification & CCS
Pulverised Lignite (PL)
PL & Post comb.CCS
PL & Oxyfuel& CCS
Integrated Gasification
Int. Gasification & CCS
Combined Cycle (CC)
CC & Post comb. CCS
Internal Comb. <1MW
MC Fuel cell 2MW
SO Fuel cell <1MW
MC Fuel cell <1MW
MC Fuel cell <1MW
SRC Poplar 9MW
Waste straw 9MW
PV, large scale
PV, small scale
PV, Thin-film
, small sc.
Thermal power plant
Offshore 24MW
GEN
III
GEN
IV
COAL LIGNITE NAT. GAS NAT. GAS
Cogeneration
BIOMASS
Cogeneration
SOLAR WIND
IT DE CH FR
Social:Fatality Rates and Max. Consequences (2050)
Source: Burgherr & Hirschberg, 2008
Nuclear Fossil
0.000001
0.00001
0.0001
0.001
0.01
0.1
1
IT DE
CH
FR IT DE
CH
FR
Pul
veris
ed C
oal (
PC
)
PC
& P
ost c
omb.
CC
S
PC
& O
xyfu
elC
CS
Inte
grat
ed G
asifi
catio
n
Int.
Gas
ifica
tion
& C
CS
Pul
veris
ed L
igni
te (
PL)
PL
& P
ost c
omb.
CC
S
PL
& O
xyfu
el&
CC
S
Inte
grat
ed G
asifi
catio
n
Int.
Gas
ifica
tion
& C
CS
Com
bine
d C
ycle
(C
C)
CC
& P
ost c
omb.
CC
S
Inte
rnal
Com
b. <
1MW
MC
Fue
l cel
l 2M
W
SO
Fue
l cel
l <1M
W
MC
Fue
l cel
l <1M
W
GEN III - EUPressurised Reactor
GEN IV - EU FastReactor
COAL LIGNITE NAT. GAS NAT. GASCogeneration
Fatalities / GW
e-yr
1
10
100
1000
10000
100000
Maximum fatalities
F-N Curves:Latent Cancer Fatalities (LCF) for current plants and EPR
1.E-12
1.E-11
1.E-10
1.E-9
1.E-8
1.E-7
1.E-6
1.E-5
1.E-4
1 10 100 1000 10000 100000
Number of Late Cancer Fatalities (LCF)
Frequency of exceedance per GWeyr
CH 2000
FR 2030 CH 2030
FR 2000
Source: Hirschberg et al., 2008
Social: legitimacy, necessity of participative decision making
Source: Gallego et al., 2008
Social: legitimacy, conflict potential
Source: Gallego et al., 2008
Economy:Direct Work Opportunities (2050)
Source: Schenler et al., 2008
Nuclear Fossil Renewable
0
50
100
150
200
250
300
350
400
450
EU Pressurised Reactor
EU Fast Reactor
Pulverised Coal (PC)
PC & Post comb.CCS
PC & OxyfuelCCS
Integrated Gasification
Int. Gasification & CCS
Pulverised Lignite (PL)
PL & Post comb.CCS
PL & Oxyfuel& CCS
Integrated Gasification
Int. Gasification & CCS
Combined Cycle (CC)
CC & Post comb. CCS
Internal Comb. <1MW
MC Fuel cell 2MW
SO Fuel cell <1MW
MC Fuel cell <1MW
MC Fuel cell <1MW
SRC Poplar 9MW
Waste straw 9MW
PV, large scale
PV, small scale
PV, Thin-film, small sc.
Thermal power plant
Offshore 24MW
GEN
III
GEN
IV
COAL LIGNITE NAT. GAS NAT. GAS
Cogeneration
BIOMASS
Cogeneration
SOLAR WIND
Person-yrs / GWh
IT DE CH FR
Economy:Capital costs (France, 2050)
Source: Schenler et al., 2008
0
500
1000
1500
2000
2500
3000
3500
EU Pressurised Reactor
EU Fast Reactor
Pulverised Coal (PC)
PC & Post comb.CCS
PC & OxyfuelCCS
Integrated Gasification
Int. Gasification & CCS
Pulverised Lignite (PL)
PL & Post comb.CCS
PL & Oxyfuel& CCS
Integrated Gasification
Int. Gasification & CCS
Combined Cycle (CC)
CC & Post comb. CCS
Internal Comb. <1MW
MC Fuel cell 2MW
SO Fuel cell <1MW
MC Fuel cell <1MW
MC Fuel cell <1MW
SRC Poplar 9MW
Waste straw 9MW
PV, large scale
PV, small scale
PV, Thin-film
, small sc.
Thermal power plant
Offshore 24MW
GEN
III
GEN
IV
COAL LIGNITE NAT. GAS NAT. GAS
Cogeneration
BIOMASS
Cogeneration
SOLAR WIND
Present value capital costs ( €/ kW
e)Nuclear Fossil Renewable
Total Costs
• Internal + External = Total Costs
• Money becomes the common denominator for all indicators.
• It is assumed that all indicators can be monetized.
• It is assumed that stakeholders can agree on the value of life, the environment, etc.
• Nevertheless, money is the most useful and widely accepted common numerator.
• Cost-benefit analysis based on (total) costs has great attractions for guiding public policy
Multi-Criteria Decision Analysis (MCDA)
• An extensive survey of multi-criteria methods for the technology choice problem was made.
• A full MCDA problem specification was made of the NEEDS problem.
• Existing multi-criteria analysis methods for discrete alternatives had significant deficiencies for the NEEDS problem specification.
• As a result, IIASA has developed and implemented a range of new MCDA methods (algorithms), far beyond the original NEEDS scope.
MCDA Process in NEEDS
• Extensive survey of multi-criteria methods for the technology choice problem
• Full MCDA specification
• Existing MCDA methods for discrete alternatives had significant deficiencies for NEEDS
- Many not suited to discrete alternatives
- Orientation to alternative ranking v. indicator results
- Weighted sum method (rank reversal problem)
� As a result, IIASA developed and implemented a range of new MCDA methods (algorithms), beyond the original NEEDS scope.
MCDA-based Aggregation :General Algorithm
MCDA Methods Developed for NEEDS
• Objective aspiration/reservation
• Reference point – Nadir
• Reference point – Utopia
• Reference point – Pareto
• Dominating alternative
• Non-linear aggregation
• Quantile aggregation
• LexMax regularization
• Weighted sum
MCDA Methods Developed
Methods developed (and variations) fall into several main groups:
• Aspiration/Reservation
• Reference Point (Utopia, Pareto & Nadir)
• Dominating Alternative
• LexMaxReg (improving worst criteria)
• Quantile & Non-linear Aggregation
The weighted sum approach (with known deficiencies) was also implemented for comparison.
MCDA Review & Selection Process
• 9 algorithms were evaluated
• (using weighted sum as a reference)
• Blind testing by PSI team (2 rounds)
• expected response to multiple preference profiles
• sensitivity to shifting preferences
• Iteration with 3 algorithm modifications
• Selection of Dominating Alternative algorithm
Examples of criteria/issues for Examples of criteria/issues for
MCDA method and tool selectionMCDA method and tool selection
• Is method/tool available or requires limited amount of adjustments and tests?
• Availability (free or licence, restrictions, price)
• Has method/tool been successfully used for energy applications relevant for NEEDS?
• Simplicity, transparency, easy to use, interactivity
• Mathematical correctness (within limits)
• Internal consistency checks
• Suitable for large amount of applications
• Processing, analysis and presentation of results
• Sensitivity analysis capability (uncertainty analysis probably not realistic)
• Compatibility with the intended (problematic) elicitation of preferences
• Possibility to use “simulated” typical preference profiles
• Expandability in the future
• Can minority views be considered?
• Non-discriminatory treatment of technologies
The Chosen MCA Algorithm
• The dominating alternative (DA) algorithm compares pairs of alternatives and chooses one that tends to minimize poor performance (similar to a max-min approach). By n-1 comparisons it selects the best of the n alternatives.
• This algorithm was selected by blind testing by a PSI team from a portfolio of 12 different solvers. The criteria included;
- expected responses to known preferences, using multiple profiles
- sensitivity to shifting preferences
Dominance Components and Index
))]()(()([)(11
jk
n
kikjkikk
n
kjikijkij rrrrwdcdcd ββ −∗−∗=−= ∑∑
==
dcijk = wk ∗ (rik − rjk )∗ β(rik )
dcjik = wk ∗ (rjk − rik )∗ β(rjk )
β(x) = α−x(alpha = 10, 0 < x < 1 for the MCDA analysis)
If dij > 0 then alternative i dominates j, i.e. alternative i is preferred to j.
The beta factor is key, otherwise the algorithm reduces to the weighted
sum approach.
indicator weight
relative ∆ in indicator performance
absolute performance weighting factor
Dominating Alternative Flowchart
• Compares pairs of alternatives
• Selects one that tends to minimizes poor performance.
• By n-1 comparisons it selects the best of the n alternatives.
• Transitivity check compares best to all others.
• Remove best & repeat to get full ranking
The Online MCDA Survey Application
Key elements:
• Interactive, graphic interface
1 Open website
2 Enter preferences
3 Solve to show ranking
4 Examine trade-offs for ‘best’ technologies
5 Repeat until satisfied
• Immediate feedback
• Iterative learning
• Automatic data collection
Online Demo of NEEDS Survey
Distribution of NEEDS Survey Respondents by top level criteria weights
Criteria Weights:All survey respondents
Technology Ranks:All survey respondents
Technology Ranks:
Cluster group 1 (11)
Technology Ranks:
Cluster group 2 (148)
Technology Ranks:equal weighting of highest level criteria (37)
Technology Ranks:
environment dominant (22)
Technology Ranks:
economy dominant (6)
Technology Ranks:
social dominant (2)
Total Costs with MCDA Ranking
Nuclear Fossil RenewableWorst
Best
Average MCDA Ranking
€cents / kW
h
0
5
10
15
20
25
Total costs = generation costs + externalities
EU Pressurised Reactor
EU Fast Reactor
Pulverised Coal (PC)
PC & Post comb.CCS
PC & OxyfuelCCS
Integrated Gasification
Int. Gasification & CCS
Pulverised Lignite (PL)
PL & Post comb.CCS
PL & Oxyfuel& CCS
Integrated Gasification
Int. Gasification & CCS
Combined Cycle (CC)
CC & Post comb. CCS
Internal Comb. <1MW
MC Fuel cell 2MW
SO Fuel cell <1MW
MC Fuel cell <1MW
MC Fuel cell <1MW
SRC Poplar 9MW
Waste straw 9MW
PV, large scale
PV, small scale
PV, Thin-film, small sc.
Thermal power plant
Offshore 24MW
GEN
III
GEN
IV
COAL LIGNITE NAT.
GAS
NAT. GAS
Cogeneration
BIOMASS
Cogeneration
SOLAR WIND
0
5
10
15
20
25GHG em. High
GHG em. Low
Pollution
Land use
Generation cost
Source: Hirschberg et al., to be published
RS2b Conclusions
• Large variation in FR, UK and US using externality valuation forpolicy making.
• General acceptance of the concept of externalities, internalisation of external costs and most results in spite of limitations.� Results for nuclear remain controversial.
• A powerful framework for MCDA-based sustainability assessment developed, implemented and applied to four countries.
•Wide stakeholder acceptance of the proposed criteria and indicator set.
• Comprehensive indicator database established for four countries.
•Optimistic-realistic technology development scenarios show remarkable future performance improvements for renewables, particularly for solar.
• Total cost approach favours nuclear and disfavours biomass. Ranking of fossil technologies in comparison to (remarkably improved) solar and wind strongly depends on which value for GHG-damages is used.
RS2b Conclusions (cont.)
• None of the technological options can fulfill all sustainability criteria and market requirements. Trade-offs between environmental, economic and social sustainability components are heavily influenced by valuejudgements.
• MCDA-approach favours renewables, in particular solar technologies.
• Inclusion of a wide set of social criteria leads to lower ranking of nuclear with GEN IV fast breeder performing better than GEN III EPR.
• Coal technologies perform worst in MCDA while centralized gas options are along with nuclear in the midfield. CCS-performance is mixed.
• Emphasis on environment penalizes fossil options; emphasis on economy penalizes renewable options; emphasis on social penalizes nuclear.
• Need for future extensions of scope and depth- Coverage of technologies (heating systems, transportation, conventional and advanced electric, efficiency)
- Indicators (e.g. surveys for social indicators)analytical issues (e.g. integration of TIMES and MCDA)tools (e.g. MCDA-methods and user interfaces)
- Geographic coverage (world) and applications (e.g. MCDA for policies)- Broader involvement of stakeholders and more direct interactions desirable
Contributors and ResponsibilitiesContributors and Responsibilities
PSITechnical stream co-ordination14
ISIS/PSIAnalysis and elaboration of the results 13
ISIS/PSIOrganisation/management of surveys and communication12
ARMINESAcceptability of monetary valuation methods11
PSIEvaluation and analysis integration10
IIASAMCDA approach and tool selection9
USTUTT.SOZQuantification of social indicators8
PSIQuantification of risk indicators7
PSIQuantification of environmental indicators6
EDFQuantification of economic indicators5
CESIRICERAExtended technology characterisation4
PSIEstablishment of full criteria set3
USTUTT.SOZEstablishment of social criteria2
PSISurvey of criteria and indicators1
LEADERSWORK PACKAGE TITLEWP
Contributors included also NGOs: GLOBE and HELIO IN TERNATIONAL
Thank you for your attention
Stefan Hirschberg
Laboratory for Energy systems Analysis (LEA)
http://lea.web.psi.ch/