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Intelligent Data-Driven Modelling and Optimization in Power and Energy Applications

Intelligent Data-Driven Modelling and Optimization in Power and Energy Applications

          
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About the Book

This book provides a comprehensive understanding of how intelligent data-driven techniques can be used for modelling, controlling, and optimizing various power and energy applications. It aims to develop multiple data-driven models for forecasting renewable energy sources and to interpret the benefits of these techniques in line with first-principles modelling approaches. By doing so, the book aims to stimulate deep insights into computational intelligence approaches in data-driven models and to promote their potential applications in the power and energy sectors. Its key features include:

  • an exclusive section on essential preprocessing approaches for the data-driven model
  • a detailed overview of data-driven model applications to power system planning and operational activities
  • specific focus on developing forecasting models for renewable generations such as solar PV and wind power, and
  • showcasing the judicious amalgamation of allied mathematical treatments such as optimization and fractional calculus in data-driven model-based frameworks

This book presents novel concepts for applying data-driven models, mainly in the power and energy sectors, and is intended for graduate students, industry professionals, research, and academic personnel.


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Product Details
  • ISBN-13: 9781032472065
  • Publisher: Taylor & Francis Ltd
  • Binding: Hardback
  • Language: English
  • Returnable: Y
  • Weight: 531 gr
  • ISBN-10: 1032472065
  • Publisher Date: 22 Apr 2024
  • Height: 234 mm
  • No of Pages: 238
  • Spine Width: 16 mm
  • Width: 156 mm


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