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Complementary data for Machine Learning-Driven Energy Management of a Hybrid Nuclear-Wind-Solar-Desalination Plant
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posted on 2022-05-20, 11:02 authored by Daniel Vazquez PomboAuthor: Daniel Vázquez Pombo (dvapo@elektro.dtu.dk), ORCID: https://orcid.org/0000-0001-5664-9421
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The paper related to this dataset is currently In Press.
Title: Machine Learning-Driven Energy Management of a Hybrid Nuclear-Wind-Solar-Desalination Plant
Submmited: Feb 2022
Accepted: May 2022
Published:
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The folder contains the data implemented in the study cases of the related paper.
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- Freshwater ecology
- Water treatment processes
- Water resources engineering
- Electrical energy generation (incl. renewables, excl. photovoltaics)
- Electrical energy transmission, networks and systems
- Chemical and thermal processes in energy and combustion
- Energy generation, conversion and storage (excl. chemical and electrical)
- Photovoltaic devices (solar cells)
- Nuclear engineering (incl. fuel enrichment and waste processing and storage)
- Machine learning not elsewhere classified
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