Monitoring and Control of Electrical Power Systems using Machine Learning Techniques
Language: English
Published by Elsevier Inc, 2023
- Softcover
- New
Seller: AHA-BUCH GmbH, Einbeck, GermanyAHA-BUCH GmbH
AbeBooks seller since August 14, 2006
Condition: New
£ 315.76
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Add to basketItem description from seller
nach der Bestellung gedruckt Neuware - Printed after ordering - Monitoring and Control of Electrical Power Systems using Machine Learning Techniques bridges the gap between advanced machine learning techniques and their application in the control and monitoring of electrical power systems, particularly relevant for heavily distributed energy systems and real-time application. The book reviews key applications of deep learning, spatio-temporal, and advanced signal processing methods for monitoring power quality. This reference introduces guiding principles for the monitoring and control of power quality disturbances arising from integration of power electronic devices and discusses monitoring and control of electrical power systems using benchmark test systems for the creation of bespoke advanced data analytic algorithms.
Seller Inventory # 9780323999045
- Title
- Monitoring and Control of Electrical Power Systems using Machine Learning Techniques
- Author
- Felix Rafael Segundo Sevilla
- Publisher
- Elsevier Inc
- Publication year
- 2023
- Condition
- Neu
- Binding
- Taschenbuch
- Language
- English
- ISBN 10
- 0323999042
- ISBN 13
- 9780323999045
- Item weight
- 475 grams
- Dimensions
- 229x152x19 mm
- Covers advanced applications and solutions for monitoring and control of electrical power systems using machine learning techniques for transmission and distribution systems
- Provides deep insight into power quality disturbance detection and classification through machine learning, deep learning, and spatio-temporal algorithms
- Includes substantial online supplementary components focusing on dataset generation for machine learning training processes and open-source microgrid model simulators on GitHub
"Synopsis" may belong to another edition of this title.
About the Author
Felix Rafael Segundo Sevilla received his PhD degree from Imperial College London, United Kingdom in 2013. From January 2013 to July 2014, Dr Segundo was a postdoctoral research fellow at the KTH Royal Institute of Technology in Stockholm, Sweden. Since 2014, he has been a Research Associate in the Zurich University of Applied Science ZHAW, Switzerland. Dr Segundo was awarded with an Ambizione Energy grant from the Swiss National Science Foundation (SNSF) to conduct his own research project entitled “Stability Assessment of Forthcoming Power Networks with Massive Integration of Renewable Energy Sources for the period 2018-2021. Dr Segundo is a Senior Member of the IEEE, chair of the annual international workshop DynPOWER and chair of the IEEE task force " Application of Big Data Analytics on Transmission System Dynamic Security Assessment".
Petr Korba received his Dr.-Ing. degree from the University of Duisburg, Germany in 1999. He worked for more than 10 years as a principal scientist at ABB Corporate Research. He became a professor of electric power systems at the ZHAW and deputy head of the institute of energy systems in 2012 and 2015, respectively. Dr Korba has published over 100 articles in international journals and at international conferences in the field of automatic control and electric power systems. He has authored and co-authored over 100 US and European patents and patent applications and was nominated for the Best European Patent Award in 2011 for his achievements in the wide-area monitoring and control of electric power systems.
"About the title" may belong to another edition of this title.
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