Premium
Making energy system models useful: Good practice in the modelling of multiple vectors
Author(s) -
Hawker Graeme S.,
Bell Keith R. W.
Publication year - 2019
Publication title -
wiley interdisciplinary reviews: energy and environment
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.158
H-Index - 35
eISSN - 2041-840X
pISSN - 2041-8396
DOI - 10.1002/wene.363
Subject(s) - consistency (knowledge bases) , computer science , relevance (law) , audit , process (computing) , risk analysis (engineering) , management science , work (physics) , data science , energy (signal processing) , cover (algebra) , industrial engineering , process management , operations research , systems engineering , artificial intelligence , engineering , business , mechanical engineering , statistics , mathematics , political science , law , operating system , accounting
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