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Om Artificial Intelligence for Renewable Energy systems

Artificial Intelligence for Renewable Energy Systems addresses the energy industries remarkable move from traditional power generation to a cost-effective renewable energy system, and most importantly, the paradigm shift from a market-based cost of the commodity to market-based technological advancements. Featuring recent developments and state-of-the-art applications of artificial intelligence in renewable energy systems design, the book emphasizes how AI supports effective prediction for energy generation, electric grid related line loss prediction, load forecasting, and for predicting equipment failure prevention. Looking at approaches in system modeling and performance prediction of renewable energy systems, this volume covers power generation systems, building service systems and combustion processes, exploring advances in machine learning, artificial neural networks, fuzzy logic, genetic algorithms and hybrid mechanisms.

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  • Språk:
  • Engelska
  • ISBN:
  • 9780323903967
  • Format:
  • Häftad
  • Sidor:
  • 406
  • Utgiven:
  • 11. augusti 2022
  • Mått:
  • 152x229x0 mm.
  • Vikt:
  • 1000 g.
Leveranstid: 2-4 veckor
Förväntad leverans: 29. januari 2025

Beskrivning av Artificial Intelligence for Renewable Energy systems

Artificial Intelligence for Renewable Energy Systems addresses the energy industries remarkable move from traditional power generation to a cost-effective renewable energy system, and most importantly, the paradigm shift from a market-based cost of the commodity to market-based technological advancements. Featuring recent developments and state-of-the-art applications of artificial intelligence in renewable energy systems design, the book emphasizes how AI supports effective prediction for energy generation, electric grid related line loss prediction, load forecasting, and for predicting equipment failure prevention. Looking at approaches in system modeling and performance prediction of renewable energy systems, this volume covers power generation systems, building service systems and combustion processes, exploring advances in machine learning, artificial neural networks, fuzzy logic, genetic algorithms and hybrid mechanisms.

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