Environment Friendly Energy Efficient Distributed Data Centers

Ali, Ahsan; Özkasap, Öznur

doi:10.1007/978-3-319-22635-4_6

Cited by 1 publication

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“…The microservices approach, for example, builds larger applications out of modular and re-usable 'services'-for example a database service-which communicate with each other through standard protocols and are configured and managed through an automated system like Docker (Boettiger 2015). Common data formats for energy model data can serve as the standard protocol layer, for example the IAMC (Gidden and Huppmann 2019) or friendly_data formats (Ali 2022). In terms of complexity, at the very simple end of the scale, an immediately practical approach is to make the building blocks so easy to use that a standard interface is not needed.…”

Section: Discussionmentioning

confidence: 99%

Open code and data are not enough: understandability as design goal for energy system models

Pfenninger

2024

Prog. Energy

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Energy system models do not represent natural processes but are assumption-laden representations of complex engineered systems, making validation practically impossible. Post-normal science argues that in such cases, it is important to communicate embedded values and uncertainties, rather than establishing whether a model is “true” or “correct”. Here, we examine how open energy modelling can achieve this aim by thinking about what “a model” is and how it can be broken up into manageable parts. Collaboration on such building blocks – whether they are primarily code or primarily data – could become a bigger focus area for the energy modelling community. This collaboration may also include harmonisation and intercomparison of building blocks, rather than full models themselves. The aim is understandability, which will make life easier for modellers themselves (by making it easier to develop and apply problem-specific models) as well as for users far away from the modelling process (by making it easier to understand what is qualitatively happening in a model - without putting undue burden on the modellers to document every detail).

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Section: Discussionmentioning

confidence: 99%

Open code and data are not enough: understandability as design goal for energy system models

Pfenninger

2024

Prog. Energy

View full text Add to dashboard Cite

show abstract

Environment Friendly Energy Efficient Distributed Data Centers

Cited by 1 publication

References 25 publications

Open code and data are not enough: understandability as design goal for energy system models

Open code and data are not enough: understandability as design goal for energy system models

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