Machine learning-driven energy management of a hybrid nuclear-wind-solar-desalination plant

HIGHLIGHTS

• who: Daniel Vu00e1zquez Pombo from the Wind and Energy Systems, Technical University of Denmark (DTU), Frederikborsvej, Roskilde, Denmark have published the research work: Machine learning-driven energy management of a hybrid nuclear-wind-solar-desalination plant, in the Journal: (JOURNAL)
• what: In this direction, Sadeghi et_al performed an economic assessment of desalinated water for scenarios in which energy is obtained from solar, small modular reactor (SMR) or both; concluding on the superiority of the HyPP structure. The aim is to coordinate dispatch, reduce construction costs, increase the plant`s efficiency, overinstallation at the same pointof . . .
  

   

  

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