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Multi-Model Ecologies for Shaping Future Energy Systems: Design Patterns and Development Paths

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Multi-Model Ecologies for Shaping Future Energy Systems: Design Patterns and Development Paths University of Groningen Multi-model ecologies for shaping future energy systems Bollinger, L. A.; Davis, C. B.; Evins, R.; Chappin, E. J. L.; Nikolic, I. Published in: Renewable & Sustainable Energy Reviews DOI: 10.1016/j.rser.2017.10.047 IMPORTANT NOTE: You are advised to consult the publisher's version (publisher's PDF) if you wish to cite from it. Please check the document version below. Document Version Publisher's PDF, also known as Version of record Publication date: 2018 Link to publication in University of Groningen/UMCG research database Citation for published version (APA): Bollinger, L. A., Davis, C. B., Evins, R., Chappin, E. J. L., & Nikolic, I. (2018). Multi-model ecologies for shaping future energy systems: Design patterns and development paths. Renewable & Sustainable Energy Reviews, 82(Part 3), 3441-3451. https://doi.org/10.1016/j.rser.2017.10.047 Copyright Other than for strictly personal use, it is not permitted to download or to forward/distribute the text or part of it without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license (like Creative Commons). The publication may also be distributed here under the terms of Article 25fa of the Dutch Copyright Act, indicated by the “Taverne” license. More information can be found on the University of Groningen website: https://www.rug.nl/library/open-access/self-archiving-pure/taverne- amendment. Take-down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Downloaded from the University of Groningen/UMCG research database (Pure): http://www.rug.nl/research/portal. For technical reasons the number of authors shown on this cover page is limited to 10 maximum. Download date: 03-10-2021 Renewable and Sustainable Energy Reviews 82 (2018) 3441–3451 Contents lists available at ScienceDirect Renewable and Sustainable Energy Reviews journal homepage: www.elsevier.com/locate/rser Multi-model ecologies for shaping future energy systems: Design patterns T and development paths ⁎ L.A. Bollingera, , C.B. Davisb, R. Evinsa,c, E.J.L. Chappind, I. Nikolicd a Empa - Swiss Federal Laboratories for Materials Science and Technology, Urban Energy Systems Laboratory, Überlandstrasse 129, Dübendorf 8600, Switzerland b University of Groningen, Faculty of Science and Engineering, Energy and Environmental Studies ESRIG, Nijenborgh 6, AG Groningen 9747, The Netherlands c University of Victoria, Department of Civil Engineering, Engineering and Computer Science (ECS) 304, PO Box 1700 STN CSC, Victoria, BC, Canada V8W 2Y2 d Delft University of Technology, Faculty of Technology, Policy and Management, Jaffalaan 5, 2628 BX Delft, The Netherlands ARTICLE INFO ABSTRACT Keywords: As energy systems grow more complex, modeling efforts spanning multiple scales, disciplines and perspectives Energy systems are essential. Improved methods are needed to guide the development of not just individual models, but also Modeling multi-model ecologies – systems of interacting models. Currently there is a lack of knowledge concerning how Multi-model ecologies multi-model ecologies can and should be designed to facilitate adequate understanding of energy system com- Complexity plexity and its consequences. Via an analysis of twelve multi-model initiatives both within and outside the Energy policy energy domain, this paper elucidates possible design patterns and development paths for multi-model ecologies. The results highlight two broad paths to developing energy system multi-model ecologies, one prioritizing interoperability and the other prioritizing diversity. The former path facilitates the efficient development of models spanning multiple scales and (to a degree) disciplines, and can ease systematic testing of assumptions. The latter is suited to bridging traditional disciplines and perspectives and advancing knowledge within the interstices of different knowledge communities. It is furthermore suggested that a combination of diversity, connectivity and hierarchy in multi-model ecology composition is central to enabling the development of complex webs of models capable of addressing the complexity of real-world energy systems. 1. Introduction As energy systems grow more complex and society's demands on their performance more stringent, we need improved methods to guide Current trends towards less carbon intensive, more decentralized, the development of not just individual models, but also of multi-model more interconnected and smarter energy systems are threads in a ecologies – systems of interacting models [4]. Multi-model ecologies are continuous process of energy systems evolution. The need to under- essential for exploring the interactions amongst energy consumption, stand and steer this evolution with effective policies demands knowl- production, distribution and transmission; amongst different energy edge creation and management processes aligned with the complexity and non-energy infrastructures such as electricity, heat, gas, transpor- of the energy system itself. Insofar as they enable systematic explora- tation and communications; and amongst socio-economic, environ- tion of the consequences of complex sets of technical and societal in- mental and technical phenomena. By facilitating exploration of com- teractions, computer models are vital tools in this process. plex energy system dynamics on multiple scales and from multiple The implementation of mathematical relations in the form of com- perspectives and disciplines, multi-model ecologies open up possibi- puter models combined with ongoing advancements in computational lities for addressing problems and questions that were previously be- capabilities have drastically expanded our ability to grasp complex yond reach, and enable systematic testing of assumptions. interactions. However, individual computer models are still undeniably Moreover, deliberately viewing systems of models as multi-model restricted in the scope of system complexity they are able to effectively ecologies enhances our capacity to strategically steer their combined capture [1–3]. This limits our ability to holistically understand the development. Rather than starting from scratch with each new pro- operation and development of energy systems – across scales, dis- blem, question or research agenda, existing models can be reused, ciplines and perspectives – and thus our capacity to effectively shape combined, expanded or adapted to address new questions that arise. their evolution. Focus shifts from the development of individual models to the ⁎ Corresponding author. E-mail addresses: [email protected] (L.A. Bollinger), [email protected] (C.B. Davis), [email protected] (R. Evins), [email protected] (E.J.L. Chappin), [email protected] (I. Nikolic). https://doi.org/10.1016/j.rser.2017.10.047 Received 10 October 2016; Received in revised form 22 June 2017; Accepted 26 October 2017 Available online 10 November 2017 1364-0321/ © 2017 Elsevier Ltd. All rights reserved. L.A. Bollinger et al. Renewable and Sustainable Energy Reviews 82 (2018) 3441–3451 deliberate cultivation of a system of models in a manner which provides goal in itself – and indeed brings many challenges – it is a fundamental ongoing value and effectively adapts to changes in knowledge needs. side-effect of efforts to enhance energy system sustainability, flexibility, The relevance of multi-model ecologies for energy systems is high- efficiency and resilience. This is illustrated by several trends: lighted by a variety of research initiatives seeking to develop and in- tegrate energy system models addressing different scales, scopes and • The push towards smarter and more distributed energy systems will disciplines, and by recent appeals to the need for such research: entail the instantiation of more and faster communication feedbacks between system elements and levels – from the scale of buildings • Spataru, et al [5] cite the need for a “holistic, multi-dimensional and and neighbourhoods to countries and continents – as well as the multi-scale framework” to address urban energy challenges. integration of a diversity of IT devices into the existing infra- • Grijalva [6] suggests that emerging engineering challenges in the structure. electricity sector require a “holistic, multi-dimensional, multi-scale • The liberalization/deregulation of energy systems has already led to framework”, and notes specific challenges aggravated by computa- a variety of new roles and markets and, in the future, can be ex- tional limitations, such as dispatch with large penetration of wind pected to further the involvement of a greater diversity of autono- generation, demand response in smart grids and multi-level in- mous actors in the energy system – e.g. power producers, trans- formation in transmission and distribution. mission and distribution system operators, retailers, aggregators – • Strachan, et al [7] describe the danger of silos built around specific interacting with one another within an increasing diversity of modeling approaches in energy modeling, and the need for explicit markets. model comparisons for effectively informing policy. • The integration of different infrastructures – such as electricity, gas, • Ferris [8] calls for layered or hierarchical models to support decision heat, transport and IT – will create new feedbacks fand inter- processes in power systems planning, and notes specifically a need dependencies, local and global, amongst infrastructures
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