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Energy Systems Modelling at the Interface of Science, Education, and Decision-Making: An Open-Source Toolkit for Europe
KTH, School of Industrial Engineering and Management (ITM), Energy Technology, Energy Systems.ORCID iD: 0000-0003-0098-8701
2024 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

In early 2024 the National Aeronautics and Space Administration (NASA) informed that 2023 has been the so far warmest year on record, with global temperatures being 1.2 degrees Celsius above the baseline. To limit further increases in global temperatures a strong reduction in greenhouse gas emissions is required. 70 percent of the anthropogenic greenhouse gas emissions are caused by the use of energy. This implies that to reduce anthropogenic greenhouse gas emissions a radical change in how humankind uses energy is required. Research shows that the necessary technologies for decarbonizing the energy system are available. It hence is on societies to carry out the relevant transitions. These transitions are complex to implement and require sophisticated planning to maximise the speed of emission reductions and limit social, economic, and environmental implications. Energy models are broadly used tools for energy systems planning in the scientific literature and in the policy making processes. However, energy models are complex tools that require training and expertise to be used in a meaningful way. The capability to communicate between energy modelling community and policy makers and society in general is therefore important for planning the energy transition. But at the same time the increasing interrelatedness of energy sectors and the increasing variability on the supply side with the expanding use of renewable energies lead to increasing complexity in the energy sector. Energy models aim to reflect these complexities and hence the complexity of models increases as well. This leads to an increasing challenge in communicating the results of energy models.

This dissertation provides methodological advances and energy modelling infrastructure to bridge the gap between energy modelling community and policy makers and stakeholders. The thesis investigates on an example model how energy system models can be set-up to facilitate the usage by inexperienced modellers and collaboratively. This model is then compared with a wide range of established models in the field to assess its performance. In a next step the implications of different foresight horizons in long-term planning models and the capability to model disruptive events are explored. This allows capturing potential challenges in policy design for the achievement of long-term goals. And lastly the thesis investigates the possibility to let non-modellers explore the dynamics of energy models via a game linked to an energy model.

In summary, the thesis identifies different means and options to bridge the energy modelling policymaking gap and facilitate a better understanding of energy models and their dynamics. This might facilitate the discussion for evidence based policy making using energy modelling.

Abstract [sv]

I början av 2024 informerade National Aeronautics and Space Administration (NASA) att 2023 hade varit det hittills varmaste året någonsin, med globala medeltemperaturer på 1,2 grader Celsius över baslinjen. För att begränsa ytterligare ökningar av den globala temperaturen krävs en kraftig minskning av utsläppen av växthusgaser. 70 procent av de antropogena utsläppen av växthusgaser orsakas av olika sorters energianvändning. Detta innebär att en minskning av antropogena växthusgaser kräver en radikal förändring av hur vi använder vår energi. Forskning visar att den nödvändiga teknologin för att minska koldioxidutsläppen i energisystemet finns tillgänglig. Det är därför upp till olika samhällen att genomföra omställningen. Detta kan vara komplicerat att genomföra, och kräver effektiv planering för snabb utsläppsminskning där negativa sociala, ekonomiska och miljömässiga konsekvenser minimeras. Energimodeller är brett använda verktyg för planering av energisystem i den vetenskapliga litteraturen och i politiska beslutsprocesser. Energimodeller är dock komplexa verktyg som kräver utbildning och expertis för att kunna användas på ett meningsfullt sätt. För planering av energiomställningen är det därför viktigt att systemanalytiker kan kommunicera utformning av, och resultat från energimodeller med beslutsfattare och samhället i stort. Samtidigt ökar komplexiteten i energisektorn till följd av sektorsamverkan samt fler alternativ på produktionssidan, t ex via förnybara alternativ som sol och vind. Detta leder till större utmaningar för att kommunicera resultaten av energimodeller.

Denna avhandling presenterar metodologiska framsteg och energimodelleringsinfrastruktur för att överbrygga klyftan mellan energianalytiker som arbetar med modeller, beslutsfattare och intressenter. Avhandlingen undersöker på en exempelmodell hur energisystemmodeller kan sättas upp för att underlätta användningen för oerfarna modellerare och på ett kollaborativt sätt. Denna modell jämförs sedan med en rad etablerade modeller inom området för att bedöma dess funktion. I ett nästa steg utforskas konsekvenserna av olika framtidsperspektiv i långsiktiga planeringsmodeller och förmågan att modellera disruptiva händelser. Detta gör det möjligt att fånga utmaningar i policyutformningen så att uppnå långsiktiga mål. Slutligen undersöker avhandlingen möjligheten för aktörer utan rörande modellen kan utforska dynamiken i energimodeller via ett spel kopplat till en energimodell.

Sammanfattningsvis identifierar avhandlingen olika alternativ för att överbrygga klyftan mellan energimodellering och politik för att på så vis underlätta förståelsen av energimodellerna och deras dynamik. Detta kan främja diskussionen kring evidensbaserad politik med hjälp av energimodellering.

Abstract [de]

Anfang 2024 teilte die National Aeronautics and Space Administration (NASA) mit, dass 2023 das bisher wärmste Jahr seit Beginn der Wetteraufzeichnungen war und die globalen Temperaturen 1,2 Grad Celsius über dem Basiswert lagen. Um einen weiteren Anstieg der globalen Temperaturen zu begrenzen, ist eine starke Reduzierung der Treibhausgas-emissionen erforderlich. 70 Prozent der menschen-gemachten Treibhausgasemissionen werden durch die Nutzung von Energie verursacht. Dies bedeutet, dass zur Reduzierung der menschengemachten Treibhausgas-emissionen eine radikale Änderung der Art und Weise wie die Menschheit Energie nutzt erforderlich ist. Untersuchungen zeigen, dass die notwendigen Technologien zur Dekarbonisierung des Energiesystems verfügbar sind. Es liegt daher an den Gesellschaften, die entsprechenden Veränderungen vorzunehmen. Diese Veränderungen sind komplex umzusetzen und erfordern eine ausgefeilte Planung, um die Geschwindigkeit der Emissionsreduzierung zu maximieren und die sozialen, wirtschaftlichen und ökologischen Auswirkungen zu begrenzen. Energiemodelle sind in der wissenschaftlichen Literatur und in den politischen Entscheidungsprozessen weit verbreitete Werkzeuge für die Planung von Energiesystemen. Energiemodelle sind jedoch komplexe Werkzeuge, die Schulung und Fachwissen erfordern, um sinnvoll eingesetzt zu werden. Die Fähigkeit zur Kommunikation zwischen dem Feld der Energiemodellierung, den politischen Entscheidungsträgern und der Gesellschaft im Allgemeinen ist daher für die Planung der Energiewende wichtig. Gleichzeitig führt die zunehmende Vernetzung der Energiesektoren und die zunehmende Variabilität auf der Produktionsseite durch zunehmenden Nutzung erneuerbarer Energien zu einer zunehmenden Komplexität im Energiesektor. Energiemodelle zielen darauf ab, diese Komplexitäten abzubilden, und daher nimmt auch die Komplexität der Modelle zu. Dies führt zu einer zunehmenden Herausforderung bei der Kommunikation der Ergebnisse von Energiemodellen.

Diese Dissertation bietet methodische Fortschritte und eine Infrastruktur zur Energiemodellierung, um die Kluft zwischen dem Feld der Energiemodellierung und politischen Entscheidungsträgern und Interessengruppen zu überbrücken. Die Arbeit untersucht anhand eines Beispielmodells, wie Energiesystemmodelle gestaltet werden können, um die Verwendung durch unerfahrene Modellierer und Kooperation zu erleichtern. Dieses Modell wird dann mit einer Gruppe von etablierten Modellen verglichen, um seine Leistungsfähigkeit zu bewerten. In einem nächsten Schritt werden die Auswirkungen unterschiedlicher Planungshorizonte in langfristigen Planungsmodellen und die Fähigkeit zur Modellierung disruptiver Ereignisse untersucht. Dies ermöglicht die Erkennung von potenziellen Herausforderungen durch kurzsichtige Entscheidungen in der Entwicklung von gesetzlichen Rahmenbedingungen zur Erreichung langfristiger Ziele. Und schließlich untersucht die Arbeit die Möglichkeit, Nicht-Modellierer die Dynamik von Energiemodellen über ein mit einem Energiemodell verknüpftes Spiel erkunden zu lassen.

Zusammenfassend identifiziert die Arbeit verschiedene Mittel und Optionen, um die Kluft zwischen Energiemodellierung und Politik zu schließen und ein besseres Verständnis von Energiemodellen und ihrer Dynamik zu ermöglichen. Dies könnte die Diskussion über evidenzbasierte Politik mithilfe von Energiemodellierung erleichtern.

Place, publisher, year, edition, pages
Stockholm: KTH Royal Institute of Technology, 2024. , p. 130
Series
TRITA-ITM-AVL ; 2024:17
Keywords [en]
OSeMOSYS, long-term, investment planning, policy-science interface
Keywords [de]
OSeMOSYS, langfristig, Investitionsplanung, Schnittstelle zwischen Politik und Wissenschaft
Keywords [sv]
OSeMOSYS, långsiktigt, investeringsplanering, policyvetenskap gränssnitt
National Category
Energy Engineering
Research subject
Energy Technology
Identifiers
URN: urn:nbn:se:kth:diva-352215ISBN: 978-91-8106-026-3 (print)OAI: oai:DiVA.org:kth-352215DiVA, id: diva2:1892440
Public defence
2024-09-23, Kollegiesalen / https://kth-se.zoom.us/j/64037744979, Brinellvägen 8, Stockholm, 09:00 (English)
Opponent
Supervisors
Funder
European Commission, 691739European Commission, 101022622European Commission, 689150Available from: 2024-08-27 Created: 2024-08-26 Last updated: 2024-09-24Bibliographically approved
List of papers
1. The Open Source electricity Model Base for Europe - An engagement framework for open and transparent European energy modelling
Open this publication in new window or tab >>The Open Source electricity Model Base for Europe - An engagement framework for open and transparent European energy modelling
2021 (English)In: Energy, ISSN 0360-5442, E-ISSN 1873-6785, Vol. 239, article id 121973Article in journal (Refereed) Published
Abstract [en]

The transition to a low carbon energy system as laid out in the Paris Agreement and the European GreenDeal presents challenges that involve society at all levels from planners to consumers. A key challenge isthe communication across these levels. Tools to foster engagement and discussion between the differentactors are open-source models with a low threshold for uptake. This paper presents the Open-Sourceelectricity Model Base for Europe an electricity sector engagement model covering all member statesof the EU, Norway, Switzerland and the United Kingdom. Built in OSeMOSYS and available on GitHub, themodel provides a starting point into energy systems modelling and can be further developed in acollaborative manner. It enables non-experts to develop an understanding of energy systems models andenergy planning. Thereby, it can serve as an engagement tool to carry the debate on the future of theEuropean power system beyond the academy, which might contribute to finding societal consensus onhow to decarbonise our energy system. The model allows dynamic power sector expansion analysis ofthe European power system till 2050. It can be used for scenario analysis and is expandable to othersectors to analyse the benefits of sector coupling.

Place, publisher, year, edition, pages
Elsevier BV, 2021
Keywords
Energy modelling, OSeMOSYS, Open-source, Europe, OSeMBE, FAIR
National Category
Energy Systems
Identifiers
urn:nbn:se:kth:diva-301862 (URN)10.1016/j.energy.2021.121973 (DOI)000701750100005 ()2-s2.0-85114711707 (Scopus ID)
Note

QC 20211028

Available from: 2021-09-14 Created: 2021-09-14 Last updated: 2024-08-26Bibliographically approved
2. Comparing energy system optimization models and integrated assessment models: Relevance for energy policy advice
Open this publication in new window or tab >>Comparing energy system optimization models and integrated assessment models: Relevance for energy policy advice
Show others...
2023 (English)In: Open Research Europe, E-ISSN 2732-5121, Vol. 3, p. 69-69Article in journal (Refereed) Published
Abstract [en]

 Background

The transition to a climate neutral society such as that envisaged in the European Union Green Deal requires careful and comprehensive planning. Integrated assessment models (IAMs) and energy system optimisation models (ESOMs) are both commonly used for policy advice and in the process of policy design. In Europe, a vast landscape of these models has emerged and both kinds of models have been part of numerous model comparison and model linking exercises. However, IAMs and ESOMs have rarely been compared or linked with one another.

Methods

This study conducts an explorative comparison and identifies possible flows of information between 11 of the integrated assessment and energy system models in the European Climate and Energy Modelling Forum. The study identifies and compares regional aggregations and commonly reported variables. We define harmonised regions and a subset of shared result variables that enable the comparison of scenario results across the models.

Results

The results highlight how power generation and demand development are related and driven by regional and sectoral drivers. They also show that demand developments like for hydrogen can be linked with power generation potentials such as onshore wind power. Lastly, the results show that the role of nuclear power is related to the availability of wind resources.

Conclusions

This comparison and analysis of modelling results across model type boundaries provides modellers and policymakers with a better understanding of how to interpret both IAM and ESOM results. It also highlights the need for community standards for region definitions and information about reported variables to facilitate future comparisons of this kind. The comparison shows that regional aggregations might conceal differences within regions that are potentially of interest for national policy makers thereby indicating a need for national-level analysis.

Place, publisher, year, edition, pages
European Commission, 2023
National Category
Energy Engineering Energy Systems
Research subject
Energy Technology
Identifiers
urn:nbn:se:kth:diva-350532 (URN)10.12688/openreseurope.15590.2 (DOI)2-s2.0-85197901429 (Scopus ID)
Funder
EU, Horizon 2020, 101022622
Note

QC 20240717

Available from: 2024-07-16 Created: 2024-07-16 Last updated: 2024-08-26Bibliographically approved
3. OSeMOSYS step - a python package for modelling energy systems under limited foresight and with decision trees
Open this publication in new window or tab >>OSeMOSYS step - a python package for modelling energy systems under limited foresight and with decision trees
(English)Manuscript (preprint) (Other academic)
Abstract [en]

A common challenge in energy system optimisation models is the representationof investment decision patterns. Such capacity expansion models often assume perfectforesight. Thereby they assume certainty for the entire modelling horizon. Thisproduces investment patterns that are cost optimal on the long-term but not necessarilyfor single assets on the short-term. Therefore, models with limited foresight can providevaluable insights when trying to anticipate investment patterns in the power sector.This article presents a Python package that expands the capabilities of the OpenSource energy Modelling System (OSeMOSYS) to facilitate modelling with limitedforesight. Furthermore, it applies the package to investigate the impact of foresighthorizon length on the accumulated CO2 emissions in a decarbonisation scenario andinvestigates the possibilities to model disruptive events.To expand the functionality of OSeMOSYS, a fully open Python package isdeveloped that allows the user to run a provided model with limited foresight. Themodel time horizon is divided into multiple independently cost-optimised time stepswith the option to vary parameters between time steps to represent decisions ordisruptive events. The package allows to run decision trees by providing multipledata options for model parameters. The decision tree then incorporates all possiblecombinations of the provided options.The article shows for the case of a decarbonisation scenario that a shortening of theforesight horizon leads to an increase in CO2 emissions accumulated over the modellinghorizon. This illustrates the importance of analysing and considering foresight horizonlengths at different levels of decision making in policy design.The analysis of model results when applying the decision tree feature illustratethat OSeMOSYS step facilitates to model sudden and disruptive events while keepinglimited foresight. This allows for analysis of the robustness of the energy system todeal with sudden changes in the boundary conditions.

Keywords
investment cycles, myopia, long-term planning, decision trees, decisions
National Category
Energy Engineering
Research subject
Energy Technology
Identifiers
urn:nbn:se:kth:diva-352214 (URN)10.5281/zenodo.13373403 (DOI)
Note

QC 20240829

Available from: 2024-08-26 Created: 2024-08-26 Last updated: 2024-08-29Bibliographically approved
4. Exploring European decarbonisation pathways in the Power Decisions Game
Open this publication in new window or tab >>Exploring European decarbonisation pathways in the Power Decisions Game
Show others...
2024 (English)In: Energy, Sustainability and Society, E-ISSN 2192-0567, Vol. 14, no 1, article id 41Article in journal (Refereed) Published
Abstract [en]

Background

Article 12 of the Paris Agreement summons the signing parties to co-operate in improving the education of their citizens on climate change and related matters. The article thereby acknowledges the importance of citizens’ support and understanding of climate change and needed measures to fight climate change. This work aims to inform European citizens on how climate change-related policies affect the power sector in Europe. For this purpose, a serious game, based on sound principles of energy systems analysis, has been developed to allow players to explore how key policy decisions affect capacity mix, investment needs, and electricity costs.

Results

The game is based on more than 1700 scenarios run through an open-source and accessible, yet technologically detailed, myopic energy system optimisation model for the electricity supply in the EU27 + 3. The game allows the user to take the role of a decision-maker and make decisions in 2020, 2030, and 2040 regarding the usage of CCS, biomass imports, cross-border electricity transmission and the pace of emission reductions. The user is then presented with economic, social, and environmental impacts of these choices. These impacts are, for example, measured and illustrated in the development of accumulated CO2 emissions per capita, levelised cost of electricity, and investment need per citizen.

Conclusion

The Power Decisions Game provides a first-of-its-kind open-source infrastructure that allows non-modellers to explore the impact of key decisions and preferences on the design of the future European power system. Furthermore, it provides insights on the consequences of short-sighted decision making. The game can be used to facilitate policy-science discussions.

Place, publisher, year, edition, pages
Springer Nature, 2024
Keywords
Energy transition, OSeMOSYS, Decarbonisation pathways, Modelling, OSeMBE
National Category
Energy Systems Energy Engineering Other Social Sciences
Research subject
Energy Technology
Identifiers
urn:nbn:se:kth:diva-350533 (URN)10.1186/s13705-024-00469-w (DOI)001269873200001 ()2-s2.0-85198086536 (Scopus ID)
Funder
EU, Horizon 2020, 691739KTH Royal Institute of Technology
Note

QC 20240717

Available from: 2024-07-16 Created: 2024-07-16 Last updated: 2024-08-26Bibliographically approved

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Henke H, 2024 - PhD thesis(4700 kB)303 downloads
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