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WIREs Energy Environ.
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Making energy system models useful: Good practice in the modelling of multiple vectors

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Abstract Energy system models which cover multiple vectors have become increasingly used to provide an evidence base for policy and commercial decisions in real‐world energy systems undergoing change. In particular, such models are often used to derive “optimal” pathways to decarbonization considering the planning or operation of systems with multiple technology options. This paper explores how the concept of “usefulness”—the applicability and relevance of modelling outcomes—may be used to establish criteria for modelling design and practice at the outset, and looks at the difficulties that may be faced in achieving this. The application should inform the choice of modelling framework and the manner in which tractability should be addressed and results meaningfully presented. A process of continuous engagement is proposed which guides modelling work towards “useful” outcomes, as well as mitigating the danger of results being more reflective of design choices than the properties of the real‐world systems being modeled. Because of the difficulties in maintaining and auditing complex datasets spanning expertise from multiple sectors, there is a clear role for independent data curators to facilitate rigor in model parameterization and to allow consistency between modelling efforts. Specialists from the different disciplines represented should be engaged to ensure that data have been interpreted and applied correctly. All modelling choices should be clearly documented along with advice on their possible implications in respect of use of the results. This article is categorized under: Energy Systems Analysis > Systems and Infrastructure
An overview of the modelling stages, separating properties internal to the model from its external context
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The key stages of policymaking through energy system modelling, adapted from (Mirakyan & De Guio, )
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The relationship between scenarios as exogenous visions of the future and scenarios as different realizations of local variables, shown here for the example of investment in generation capacity from (Bukhsh, Bell, Vergnol, Weynants, & Sprooten, )
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Example output from an optimization‐based energy simulation model, dispatching multiple energy vectors to supply domestic heat demand with the goal of emissions minimization while respecting network limits (adapted from Hawker, )
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