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Monitoring and control of electrical power systems using machine learning techniques /

"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 re...

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Bibliographic Details
Corporate Author: ScienceDirect (Online service)
Other Authors: Espejo, Emilio Barocio (Editor), Sevilla, Felix Rafael Segundo (Editor), Korba, Petr (Editor)
Format: eBook
Language:English
Published: Amsterdam, Netherlands ; Oxford, United Kingdom ; Cambridge MA : Elsevier, [2023]
Subjects:
Electric power systems > Control.
Machine learning.
Réseaux électriques (Énergie) > Régulation.
Apprentissage automatique.
Electric power systems > Control
Machine learning
Electronic books.
Online Access:Connect to the full text of this electronic book
Description
Summary:"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."--Provided by Publisher.
Physical Description:1 online resource (xiv, 339 pages) : illustrations
Bibliography:Includes bibliographical references and index.
ISBN:9780323984041
0323984045