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Monitoring and Control of Electrical Power Systems using Machine Learning Techniques

By: (Edited by) Emilio Barocio Espejo , (Edited by) Felix Rafael Segundo Sevilla , (Edited by) Petr Korba

Extended Catalogue

Ksh 22,850.00

Format: Paperback / Softback

ISBN-10: 0323999042

ISBN-13: 9780323999045

Publisher: Elsevier - Health Sciences Division

Imprint: Elsevier - Health Sciences Division

Country of Manufacture: NL

Country of Publication: GB

Publication Date: Jan 23rd, 2023

Print length: 352 Pages

Weight: 584 grams

Dimensions (height x width x thickness): 15.10 x 22.70 x 2.10 cms

Product Classification: Electric motors

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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.

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