Intelligent data-driven modelling and optimization in power and energy applications /

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 benefi...

Full description

Bibliographic Details
Corporate Author:	Taylor & Francis
Other Authors:	Prusty, B. Rajanarayan (Editor), Gupta, Neeraj (Editor), Bingi, Kishore (Editor), Sehgal, Rakesh (Editor)
Format:	eBook
Language:	English
Published:	Boca raton, FL : CRC Press, 2024.
Series:	Intelligent Data-Driven Systems and Artificial Intelligence
Subjects:	Renewable energy sources > Computer simulation. Artificial intelligence > Engineering applications. Énergies renouvelables > Simulation par ordinateur. Intelligence artificielle > Applications en ingénierie. TECHNOLOGY / Electricity TECHNOLOGY / Electronics / General Electronic books.
Online Access:	Connect to the full text of this electronic book

Description
Summary:	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.
Item Description:	Includes index.
Physical Description:	1 online resource (xiv, 238 pages).
ISBN:	9781003470274 1003470270 9781040016251 1040016251 1040016111 9781040016114