Smart Energy and Electric Power Systems | Current Trends and New Intelligent Perspectives
Idioma: inglés
Editorial: Elsevier Inc, 2022
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Smart Energy and Electric Power Systems | Current Trends and New Intelligent Perspectives | Sanjeevikumar Padmanaban (u. a.) | Taschenbuch | Englisch | 2022 | Elsevier Inc | EAN 9780323916646 | Verantwortliche Person für die EU: Kolibri 360 GmbH, Ettore-Bugatti-Str. 6-14, 51149 Köln, produktsicherheit[at]kolibri360[dot]de | Anbieter: preigu.
N° de ref. del artículo 120936189
- Título
- Smart Energy and Electric Power Systems | Current Trends and New Intelligent Perspectives
- Autor
- Sanjeevikumar Padmanaban (u. a.)
- Editorial
- Elsevier Inc
- Año de publicación
- 2022
- Estado
- Neu
- Encuadernación
- Taschenbuch
- Idioma
- inglés
- ISBN 10
- 0323916643
- ISBN 13
- 9780323916646
- Peso del artículo
- 316 gramos
- Dimensiones
- 227 x 148 x 14 mm
- Catálogos de vendedores
- Bücher
Smart Energy and Electric Power Systems: Current Trends and New Intelligent Perspectives reviews key applications of intelligent algorithms and machine learning techniques to increasingly complex and data-driven power systems with distributed energy resources to enable evidence-driven decision-making and mitigate catastrophic power shortages. The book reviews foundations towards the integration of machine learning and smart power systems before addressing key challenges and issues. The work then explores AI- and ML-informed techniques to rebalancing of supply and demand. Methods discussed include distributed energy resources and prosumer markets, electricity demand prediction, component fault detection, and load balancing.
Security solutions are introduced, along with potential solutions to cyberattacks, security data detection and critical loads in power systems. The work closes with a lengthy discussion, informed by case studies, on integrating AI and ML into the modern energy sector.
- Helps improve the prediction capability of AI algorithms to make evidence-based decisions in the smart supply of electricity, including load shedding
- Focuses on how to integrate AI and ML into the energy sector in the real-world, with many chapters accompanied by case studies
- Addresses a number of proven AI and ML- informed techniques in rebalancing supply and demand
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Acerca del autor
Dr Jens Bo Holm-Nielsen is Associate Professor and Head of Center for Bioenergy and Green Engineering, Aalborg University, Aalborg, Denmark
Dr.Kayal Padmanandam has over a decade of credentials in the domain of Computer Science with wide exposure through teaching, research, and industry. She is passionate about research and specialized in Data Science and Machine Learning Algorithms in which she pursued her doctoral research. She has several publications especially related to machine-learning applications. She is a post-graduate/graduate educator for Engineering and Science scholars. Currently, she is working as an Associate Professor in the Department of Information Technology and as a Member of the Research & Development Cell, BVRITH College of Engineering, Hyderabad, India.
Dr. Rajesh Kumar Dhanaraj is a professor at the Symbiosis International (Deemed University) in Pune, India. His research and publication interests include cyber-physical systems, wireless sensor networks, and cloud computing. He is a senior member of the Institute of Electrical and Electronics Engineers (IEEE), a member of the Computer Science Teacher Association (CSTA) and member of the International Association of Engineers (IAENG). He is an expert advisory panel member of Texas Instruments Inc. (USA), and an associate editor of International Journal of Pervasive Computing and Communications (Emerald Publishing).
Dr. Balamurugan Balusamy is currently working as an Associate Dean Student in Shiv Nadar Institution of Eminence, Delhi-NCR. He is part of the Top 2% Scientists Worldwide 2023 by Stanford University in the area of Data Science/AI/ML. He is also an Adjunct Professor in the Department of Computer Science and Information Engineering, Taylor University, Malaysia. His contributions focus on engineering education, blockchain, and data sciences
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