AI Techniques for Renewable Source Integration and Battery Charging Methods in Electric Vehicle Applications

AI Techniques for Renewable Source Integration and Battery Charging Methods in Electric Vehicle Applications

  • Angalaeswari, S.
  • Deepa, T.
  • Kumar, L. Ashok
Publisher:IGI GlobalISBN 13: 9781668488188ISBN 10: 1668488183

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AI Techniques for Renewable Source Integration and Battery Charging Methods in Electric Vehicle Applications is written by Angalaeswari, S. and published by IGI Global. It's available with International Standard Book Number or ISBN identification 1668488183 (ISBN 10) and 9781668488188 (ISBN 13).

Artificial intelligence techniques applied in the power system sector make the prediction of renewable power source generation and demand more efficient and effective. Additionally, since renewable sources are intermittent in nature, it is necessary to predict and analyze the data of input sources. Hence, further study on the prediction and data analysis of renewable energy sources for sustainable development is required. AI Techniques for Renewable Source Integration and Battery Charging Methods in Electric Vehicle Applications focuses on artificial intelligence techniques for the evolving power system field, electric vehicle market, energy storage elements, and renewable energy source integration as distributed generators. Covering key topics such as deep learning, artificial intelligence, and smart solar energy, this premier reference source is ideal for environmentalists, computer scientists, industry professionals, researchers, academicians, scholars, practitioners, instructors, and students.