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Decision Analysis in Energy Systems


Admission requirements

Required course(s):

None, but Energy & Resource Management is recommended.


The world is becoming more complex every day. Energy is a pillar for the functioning of our society and its management is dependent on data of different types. Preferences from multiple stakeholders (e.g., government, industry, civil society) need to be accounted for as well. In this context, decisions are more needed than ever, and they need to be taken quickly. How can we make sense of all this information to provide recommendations for Decision Makers (DMs) to manage energy systems? This course will start answering this question by introducing you to Multiple Criteria Decision Analysis (MCDA). MCDA is a discipline that has been specifically developed to help DMs make better decisions. It allows to comprehensively evaluate alternatives by integrating conflicting objectives and preferences of the DMs.

The students will learn the key concepts of decision quality in the context of sustainability and resilience-driven energy systems analysis. This will include the understanding of how sustainability and resilience frameworks can be applied to assess energy systems at different scales, from a micro (e.g., technologies) to a macro (e.g., countries) scale.

Key potentials of MCDA will be discussed, including the capability of conveying a wealth of information that describes each alternative in a synthetic fashion, like a ranking from the best to the worst, a sorting in good, medium, and bad classes, or the choice of a subset of the most preferred alternatives.

Throughout the Block, we will explore practical MCDA-based case studies which include, among others, sustainability evaluation of different mixes of energy technologies, resilience assessment of countries’ electricity supply, and risk assessment of energy accidents.

Course Objectives


  • Outline how sustainability and resilience frameworks are used to assess energy systems

  • Describe the Multiple Criteria Decision Analysis (MCDA) process and distinguish the role of the stakeholders in each of its steps

  • Explain MCDA methods of different type, tailored to the most common decision-making problems (i.e., ranking and classification) in energy systems analysis and beyond


  • Develop an energy system analysis model to rank a set of alternatives using sustainability and/or resilience frameworks

  • Transpose in own research projects solutions proposed to tackle challenging steps in decision support


Timetables for courses offered at Leiden University College in 2022-2023 will be published on this page of the e-Prospectus.

Mode of instruction

This course delivers a stepwise introduction to the tools needed to support complex decision-making, using a mix of lectures, class discussions, workshops, and small group meetings with the instructor to shape critical thinking and decision support expertise. The classes will be interactive and develop the students’ analytical skills for tackling pressing decision-making challenges, primarily in the area of energy systems analysis.
This course is (mostly) project-based, meaning that each student will be part of a specific group that will work on a project of interest* throughout the whole block. Each group will develop an understanding of the sustainability and/or resilience-related impacts of their project. After that, each group will tailor their decision support model to provide a comprehensive score for the alternatives under evaluation in order to rank them and identify the best performing one(s).

*Examples of previous projects include the choice of electricity storage technologies, location of a geothermal power plant, and development of energy transition policies for a country.

Assessment Method

  • Course participation (10%, ongoing week 1-7)

  • Group project part 1 (13%, week 3): Initial proposal for the case study to be modelled and analysed by means of MCDA

  • Group project part 2 (17%, week 6): Final presentation of the case study to be modelled and analysed by means of MCDA

  • Individual assignment (30%, week 7): Personal proposal of a research strategy to improve at least one step of the group project

  • Final exam (30%, week 8): Open and close-ended questions on course material

Reading list

Several readings will be made available throughout the course. These will include journal publications and chapters, including from these key books about MCDA:

  • Greco S, Ehrgott M, Figueira J. (Eds.) Multiple Criteria Decision Analysis: State of the Art Surveys. New York: Springer-Verlag; 2016. (A recent survey of the main families of MCDA methods presented by some of the main researchers in the area)

  • Belton V, Stewart TJ. (Eds.) Multiple criteria decision analysis - An integrated approach, Kluwer Academic Publisher; 2002. (A very approachable book as an introduction to MCDA and some of its methods)

  • Ren, J. (Ed.) Energy Systems Evaluation (Volume 2). Multi-Criteria Decision Analysis: Springer, Cham; 2021 (A good compendium of MCDA applications in the areas of energy systems analysis)


Courses offered at Leiden University College (LUC) are usually only open to LUC students and LUC exchange students. Leiden University students who participate in one of the university’s Honours tracks or programmes may register for one LUC course, if availability permits. Registration is coordinated by the Education Coordinator,


Dr. Marco Cinelli,