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Multi-criteria evaluation of transition pathways

towards a sustainable energy system

Katharina Stahlecker, MSc

Prof. Dr. Jutta Geldermann

Chair of Production and Logistics

geldermann@wiwi.uni-goettingen.de

1. Problem Motivation: Research project

on sustainable electricity supply

2. Research question and research gap

3. Application of MCDA to evaluate

transition pathways with time-varying

criteria (Status quo)

4. Questions and challenges for further

research

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University of Göttingen

(Germany)

• Founded in 1734

• 13 Faculties with 27,500 students and

12,000 staff members (495 professors)

• 45 Nobel price laureates are linked to Göttingen via their CV

(2014: Stefan Hell (Chemistry) for "for the development

of super-resolved fluorescence microscopy”)

• Chair of Production and Logistics

(Faculty of Economic Sciences)

12 Research Associates /

Ph.D. students working on

current topics of sustainability and

energy efficiency,

using methods of Operations Research

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Transformation of the Energy Supply System

Large-scale power plants

380/220 kV

110 kV

20 kV

Industry

Industry/business units 0,4 kV

Households

Energy supply in former days:

0,4 kV

Flexible power plants

380/220 kV

110 kV

20 kV

Industry

Industry /business unit

Offshore-Windpower

Biogas plant

Wind power

plant

PV-parks

Co-generation

Onshore-Windfarm

Large-scale

storage

Storage

storage

E-mobility

Energy supply in future:

Households

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Energy mix pathway

Pathway 1 Pathway 2

Structure of the Primary Energy consumption in Germany for two different scenarios (BMU, 2012)

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Transition pathways towards a

sustainable electricity supply for Lower-Saxony

•16.11.2015

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OFFIS

Prof. Dr. Michael Sonnenschein

Prof. Dr. Dr. h.c. H.-Jürgen Appelrath †

Leibniz Universität Hannover

Prof. Dr.-Ing. habil. Lutz Hofmann

Jun.-Prof. Dr. Michael Hübler

TU Braunschweig

Prof. Dr. Frank Eggert

Prof. Dr.-Ing. Bernd Engel

Georg-August-Universität Göttingen

Prof. Dr. Jutta Geldermann

Universität Oldenburg

Jun.-Prof. Sebastian Lehnhoff

Prof. Dr. Dr. h.c. H.-Jürgen Appelrath †

apl. Prof. Dr. Niko Paech

Funded by Ministry

of Science and

Culture

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Transition pathways towards a

sustainable electricity supply for Lower-Saxony

Issue

• Targets:

– Reduction of GHG emissions by 80%-95% in 2050 compared to 1990

– Nuclear phase-out

• Transformation of the energy system with increased use of renewable energy

• Multiple conflicting objectives

Energy mix?

Grid expansion with more

fluctuating energy production?

Information technology

to flexibilize energy

demand? Electricity storage?

Security of supply Economic

competitiveness

Environmental

sustainability

Social acceptance

and wellbeing

Funded by Ministry

of Science and

Culture

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Status quo

Electricity Mix 2014

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Research questions within NEDS

• Transition takes a long time

• Various stakeholder groups

• Conflicting criteria from economic,

ecological, technological and social

perspective

Bandwidth of the total electricity generation from renewable energies for different

scenarios with goal of 80% GHG emissions reduction in 2050 (BMU, 2012)

What are possible transition pathways towards a sustainable electricity

supply for Lower Saxony in 2050?

How can we evaluate the sustainability of the different transition pathways?

Use of Multi-criteria

decision analysis

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Sustainability of energy systems: Related Research

Energy scenarios (Germany) MCDA & Energy scenarios Time-dependent MCDA

Objective

Forecasting/Backcasting

of scenarios for 2050

Explorative and normative

scenarios

Energy system modelling

Consideration of

sustainaibility through

cost and CO2

MCDA for decision between

different energy scenarios

Different MCDA methods

applied

Consideration of technical,

social, ecological and

economic criteria

MCDA for long-term, multi-

period decisions

Uncertainty in evaluation is

tackled e.g. through

scenario analysis,

probabilities, fuzzy numbers

Alternatives are static

One multi-period approach

Selected

papers

Prognos (2010)

Nitsch et al. (2012)

Faulstich et al. (2016)

Repenning et al.(2015)

Keles et al.(2011)

Kronenberg et al. (2011)

Diakoulaki & Karangelis (2007)

Kowalski et al. (2009)

Ribeiro et al. (2013)

Santoyo-Castelazo & Azapagic

(2014)

Zhang et al. (2015)

Bertsch & Fichtner (2015)

Wang et al. (2009)

Oberschmidt (2010)

Frini & BenAmor (2014)

Goumas & Lygerou (2000)

Heinrich (2007)

Durbach & Stewart (2012)

Stewart et al. (2013)

Research

Gap

Modeling different

sustainability criteria besides

CO2 emissions and cost

Study for a federal state (Lower-

Saxony)

Connection of different modeling

tools

Consideration of pathways with

time- varying criteria values

(“multi-period MCDA”)

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Alternative 1: Grid

expansion

Alternative 2:

Information technology

Grid simulation of alternatives (Hoffmann & Blaufuß)

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Methodological framework

Multi-criteria

decision

analysis

Determination of sustainability criteria

Technical model Economic model

Ecological model Social model

CO O

Future scenarios

(framework

conditions)

Identification of

relevant

parameters for

alternative

energy supply

Stakeholder

participation

Illustration based on Hoffmann (2015)

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Multi-criteria decision analysis – General process

Identification of the

problem / issue

Developing an

action plan

Problem

structuring Values

Stakeholders

Goals

Alternative

Uncertainties

Key issues

External

Environment

Constraints

Using the model to

inform and

challenge thinking

Model

Building Specifying

alternatives

Eliciting

values Defining

criteria Synthesis

of information

Challenging

intuition

Creating new

alternatives

Sensitivity

analysis

Robustness

analysis

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Belton and Stewart (2002)

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Goal Subgoals Subgoals Level 2 Subgoals Level 3 Criteria Attribute

Security of supply Availability of energy Import quota Min %

technical

Average Outage Min h/year

Reliability of supply

…

Cost of electricity Min €/kWh

economic

…

Sustainable electricity

supply

Noise exposure Min Qualitative scale

Quality of life

…

social

Income inequality Min Qualitative scale

Social justice

…

GHG emissions Minkg CO2-

Equivalents

Climate and air quality

…

ecological

Land use Min m²

Ressource protection

…

Sustainability criteria

• Criteria have been developed by research team based on the results

from public symposium and literature

• In total 33 criteria

• Challenge: Redundancy and independence of criteria with participation

Sustainable

electricity supply

Ressource

protection

ecological

social

Security of

supply

Reliability of

supply

technical

economic

Climate and air

quality

Quality of life

Social justice

Land use

…

Availability of

energy

Average Outage

…

Cost of electricity

Import quota

…

…

Noise exposure

…

Income inequality

…

GHG emissions Min

Min

%

h/year

€/kWh

Qualitative

scale

Qualitative

scale

kg CO2-

Equivalents

m²

Min

Min

Min

Min

Min

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Formal decision problem for MCDA

X

x x x x a

x x x x a

x x x x a

x x x x a

c c c c

mn mj 2 m 1 m m

in ij 2 i 1 i i

n 2 j 2 22 21 2

n 1 j 1 12 11 1

n j 2 1

=

L L

M O M O M M M

L L

M O M O M M M

L L

L L

L L

Decision matrix

Technical modelEconomic model

Ecological modelSocial model

CO O

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Evaluation of transition pathways: Time-varying alternatives

2015 2020 2030 2040 2050

Ecological

criteria

Technical

criteria

Social

criteria

Economic

criteria

System state 2015

Ecological

criteria

Technical

criteria

Social

criteria

Economic

criteria

Target state 2050 Ecological

criteria

Technical

criteria

Social

criteria

Economic

criteria

System state 20XX

Ecological

criteria

Technical

criteria

Social

criteria

Economic

criteria

System state 20XX

Ecological

criteria

Technical

criteria

Social

criteria

Economic

criteria

System state 20XX

Ecological

criteria

Technical

criteria

Social

criteria

Economic

criteria

System state 20XX

Ecological

criteria

Technical

criteria

Social

criteria

Economic

criteria

System state 20XX

Ecological

criteria

Technical

criteria

Social

criteria

Economic

criteria

System state 20XX

Ecological

criteria

Technical

criteria

Social

criteria

Economic

criteria

System state 20XX

Ecological

criteria

Technical

criteria

Social

criteria

Economic

criteria

System state 20XX

Ecological

criteria

Technical

criteria

Social

criteria

Economic

criteria

System state 20XX

MCDA with time-dependent criteria values

MCDA per time step:

One ranking per time step

t=1 t=2 t=3 t=4

Criteria values for one criterion over time

Alternative 1 Alternative 2 Alternative 3

t=1 t=2 t=3 t=4

MCDA Evaluation at discrete time steps

Alternative 1 Alternative 2 Alternative 3

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Why is it important to account for the time component in MCDA?

Distributional aspects

• Distribution of costs and benefits over time

• Intergenerational justice

Uncertainties in long-term decision making

• Technological change

• Values and behaviour changes over time

• Political and and economic framework conditions

• Interdependencies

Behavioural research (Psychology/ Economics)

• Intertemporal Preferences*

• Behavioural bias

*Berns et al. (2007), Loewenstein et. al (2002)

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PROMETHEE Preference Ranking Organisation Method for Enrichment Evaluations*

b1 a

p(b1,a)

p(a, b1)

a

b c

d e

a

d e

b c

Partial ranking

Complete ranking

*Brans et al. (1986)

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Possible ways to handle time-varying data for PROMETHEE

*Mareschal (2014), **Banamar & De Smet (2015)

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Questions and challenges for further research

Implementation of research methodology:

How to link MCDA to the results of other modeling tools? Is this

possible/reasonable?

Participation in complex decision problems:

How to deal with different stakeholder groups where nobody is the

actual decision maker?

How much participation is constructive?

Long-term decision making and time-component in MCDA:

How to deal with decisions affecting a long time horizon?

Which modification of the method is appropriate and well-founded to

account for the time-varying criteria values?

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Literature (1/3)

Banamar, I. & De Smet, Y. (2015). Extension of PROMETHEE method to temporal evaluations.

http://cs.ulb.ac.be/conferences/imw2015/files/slides/Banamar.pdf

Belton, V., & Stewart, T. (2002). Multiple criteria decision analysis: an integrated approach. Springer Science

& Business Media.

Berns, G. S., Laibson, D., & Loewenstein, G. (2007). Intertemporal choice–toward an integrative

framework. Trends in cognitive sciences, 11(11), 482-488.

Bertsch, V., & Fichtner, W. (2015). A participatory multi-criteria approach for power generation and

transmission planning. Annals of Operations Research, 1-31.

Brans, J. P., Vincke, P., & Mareschal, B. (1986). How to select and how to rank projects: The PROMETHEE

method. European journal of operational research, 24(2), 228-238.

Diakoulaki, D., & Karangelis, F. (2007). Multi-criteria decision analysis and cost–benefit analysis of

alternative scenarios for the power generation sector in Greece. Renewable and Sustainable Energy

Reviews, 11(4), 716-727.

Durbach, I. N., & Stewart, T. J. (2012). Modeling uncertainty in multi-criteria decision analysis. European

Journal of Operational Research, 223(1), 1-14.

Faulstich, M. , Beck, H.-P., Von Haaren, C., Kuck, J. &…&Yilmaz, C. (2016). Szenarien zur

Energieversorgung in Niedersachsen im Jahr 2050. Gutachten im Auftrag des Niedersächsischen

Ministeriums für Umwelt, Energie und Klimaschutz. Hannover.

Frederick, S., Loewenstein, G., & O'donoghue, T. (2002). Time discounting and time preference: A critical

review. Journal of economic literature, 40(2), 351-401.

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Literature (2/3)

Frini, A., & BenAmor, S. (2015). A TOPSIS multi-criteria multi-period approach for selecting projects in

sustainable development context. In Industrial Engineering and Operations Management (IEOM), 2015

International Conference on (pp. 1-9). IEEE.

Goumas, M., & Lygerou, V. (2000). An extension of the PROMETHEE method for decision making in fuzzy

environment: Ranking of alternative energy exploitation projects. European Journal of Operational Research,

123(3), 606-613.

Heinrich, G., Basson, L., Cohen, B., Howells, M., & Petrie, J. (2007). Ranking and selection of power

expansion alternatives for multiple objectives under uncertainty. Energy, 32(12), 2350-2369.

Keles, D., Möst, D., & Fichtner, W. (2011). The development of the German energy market until 2030—a

critical survey of selected scenarios. Energy Policy, 39(2), 812-825.

Kowalski, K., Stagl, S., Madlener, R., & Omann, I. (2009). Sustainable energy futures: Methodological

challenges in combining scenarios and participatory multi-criteria analysis. European Journal of Operational

Research, 197(3), 1063-1074.

Kronenberg, T., Martinsen, D., Pesch, T., Sander, M., Fischer, W., Hake, J. F., ... & Markewitz, P. (2011).

Energieszenarien für Deutschland: Stand der Literatur und methodische Auswertung. Energiewende-Aspekte,

Optionen, Herausforderungen, 132-166.

Mareschal, B. (2014). Dynamic MCDA with PROMETHEE and GAIA. http://www.promethee-

gaia.net/assets/dynmcda2014.pdf

Nitsch, J., Pregger, T., Naegler, T., Heide, D., de Tena, D. L., Trieb, F., ... & Trost, T. (2012).

Langfristszenarien und Strategien für den Ausbau der erneuerbaren Energien in Deutschland bei

Berücksichtigung der Entwicklung in Europa und global. Schlussbericht BMU–FKZ 03MAP146. Deutsches

Zentrum für Luft-und Raumfahrt

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Literature (3/3)

Oberschmidt, J. (2010). Multikriterielle Bewertung von Technologien zur Bereitstellung von Strom und

Wärme. Fraunhofer Verlag.

Repenning, J., Matthes, F., Blanck, R., Emele, L., Döring, U., Förster, H., ... & Jörß, W. (2015).

Klimaschutzszenario 2050. 2. Endbericht. Studie im Auftrag des BMUB. Technical report, Öko-Institut,

Fraunhofer ISI.

Ribeiro, F., Ferreira, P., & Araújo, M. (2013). Evaluating future scenarios for the power generation sector

using a multi-criteria decision analysis (MCDA) tool: the Portuguese case. Energy, 52, 126-136.

Santoyo-Castelazo, E., & Azapagic, A. (2014). Sustainability assessment of energy systems: integrating

environmental, economic and social aspects. Journal of Cleaner Production, 80, 119-138.

Prognos, EWI, GWS (2010). Energieszenarien für ein Energiekonzept der Bundesregierung. Basel, Köln,

Osnabrück.

Stewart, T. J., French, S., & Rios, J. (2013). Integrating multicriteria decision analysis and scenario

planning—Review and extension. Omega, 41(4), 679-688.

Wang, J. J., Jing, Y. Y., Zhang, C. F., & Zhao, J. H. (2009). Review on multi-criteria decision analysis aid in

sustainable energy decision-making. Renewable and Sustainable Energy Reviews, 13(9), 2263-2278.