Applications of artificial intelligence in planning and operation of smart grids
Author(s)
Bibliographic Information
Applications of artificial intelligence in planning and operation of smart grids
(Power systems)
Springer, c2022
Available at 2 libraries
  Aomori
  Iwate
  Miyagi
  Akita
  Yamagata
  Fukushima
  Ibaraki
  Tochigi
  Gunma
  Saitama
  Chiba
  Tokyo
  Kanagawa
  Niigata
  Toyama
  Ishikawa
  Fukui
  Yamanashi
  Nagano
  Gifu
  Shizuoka
  Aichi
  Mie
  Shiga
  Kyoto
  Osaka
  Hyogo
  Nara
  Wakayama
  Tottori
  Shimane
  Okayama
  Hiroshima
  Yamaguchi
  Tokushima
  Kagawa
  Ehime
  Kochi
  Fukuoka
  Saga
  Nagasaki
  Kumamoto
  Oita
  Miyazaki
  Kagoshima
  Okinawa
  Korea
  China
  Thailand
  United Kingdom
  Germany
  Switzerland
  France
  Belgium
  Netherlands
  Sweden
  Norway
  United States of America
Note
Includes bibliographical references and index
Description and Table of Contents
Description
Artificial intelligence (AI) is going to play a significant role in smart grid planning and operation, especially in solving its real-time problems, as it is fast, adaptive, robust, and less dependent on the system's accurate model and parameters. This collection covers research advancements in the application of AI in the planning and operation of smart grids. A global group of researchers and scholars present innovative approaches to AI-based smart grid planning and operation, cover the theoretical concepts and experimental results of the application of AI-based techniques, and apply these techniques to deal with smart grid issues. Applications of Artificial Intelligence in Planning and Operation of Smart Grids is an ideal resource for researchers on the theory and application of AI, practicing engineers working in electrical power engineering, and students in advanced graduate-level courses.
Table of Contents
A New Agent based Machine Learning Strategic Electricity Market Modeling Approach towards Efficient Smart Grid Operation.- Reinforcement learning techniques for MPPT control of PV system under climatic changes.- A Novel Three Stage Short-Term Photovoltaic Prediction Approach Based on Neighbourhood Component Analysis and ANN Optimized with PSO (NCA-PSO-ANN).- Applications of Artificial Intelligence in Short-Term and Long-Term Forecasting Techniques.
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