EnergySHR

A platform for energy dataset sharing and communications

Conference Paper (2025)
Author(s)

Zaman Ziabakhshganji ( Erasmus Universiteit Rotterdam)

Mathijs M. De Weerdt (TU Delft - Algorithmics)

S. Deb (TU Delft - Research Engineering & Infrastructure Team)

C.G. Duterloo (TU Delft - Corporate Innovations)

Yashar Ghiassi-Farrokhfal ( Erasmus Universiteit Rotterdam)

Doron Gollnast ( Erasmus Universiteit Rotterdam)

Jhon Jairo Quinones Cortes (TU Delft - Algorithmics)

Alicia Julia Wilson Takaoka ( Erasmus Universiteit Rotterdam)

Simon H. Tindemans (TU Delft - Intelligent Electrical Power Grids)

More authors

Research Group
Algorithmics
DOI related publication
https://doi.org/10.1145/3679240.3734680
More Info
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Publication Year
2025
Language
English
Research Group
Algorithmics
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository as part of the Taverne amendment. More information about this copyright law amendment can be found at https://www.openaccess.nl. Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.@en
Pages (from-to)
989-991
ISBN (electronic)
9798400711251
Reuse Rights

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Abstract

Because the energy transition is a critical and urgent issue that is increasingly reliant on data, the Center for Energy System Intelligence (CESI), a Convergence collaboration between TU Delft and Erasmus University Rotterdam, has developed a platform where researchers on the energy transition can share, publish, and/or find energy-related datasets and algorithms: EnergySHR. This platform aims to accelerate energy transition research into intelligent, data-driven algorithms. In this demonstration, we present the EnergySHR platform as both a platform for storing, accessing, managing, and archiving datasets as well as a tool to conduct empirical research about platformization and data-driven decision-making about the energy transition.

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