Monitoring and Control of Electrical Power Systems using Machine Learning Techniques

Machine Learning Techniques are used to monitor and control electrical power systems, particularly for heavily distributed energy systems and real-time applications. The book reviews key applications of deep learning, spatio-temporal, and advanced signal processing methods for monitoring power quality and discusses monitoring and control of power quality disturbances using benchmark test systems.

Format: Paperback / softback
Length: 352 pages
Publication date: 27 January 2023
Publisher: Elsevier - Health Sciences Division

Monitoring and Control of Electrical Power Systems using Machine Learning Techniques is a groundbreaking book that seamlessly bridges the gap between advanced machine learning techniques and their practical application in the control and monitoring of electrical power systems, particularly in the context of heavily distributed energy systems and real-time applications. This comprehensive resource delves into the realm of power quality monitoring, exploring the utilization of deep learning, spatio-temporal, and advanced signal processing methods to ensure the reliability and efficiency of power systems.

The book begins by providing a comprehensive review of key applications of deep learning, spatio-temporal, and advanced signal processing methods in the field of power quality monitoring. It sheds light on how these techniques can be leveraged to detect and classify power quality disturbances, enabling timely mitigation and prevention of issues that can impact the performance and stability of electrical networks.

Furthermore, the book introduces guiding principles for the monitoring and control of power quality disturbances arising from the integration of power electronic devices. It discusses the importance of monitoring and controlling power quality in various industries, such as telecommunications, renewable energy, and transportation, and highlights the challenges associated with these applications.

To facilitate the development of bespoke advanced data analytic algorithms for monitoring and controlling electrical power systems, the book also provides detailed discussions on monitoring and control of electrical power systems using benchmark test systems. These test systems serve as valuable platforms for testing and validating new monitoring and control algorithms, ensuring their effectiveness and reliability in real-world scenarios.

By combining theoretical insights with practical applications, Monitoring and Control of Electrical Power Systems using Machine Learning Techniques offers a comprehensive and authoritative guide for professionals and researchers in the field of electrical power systems. It empowers readers with the knowledge and tools necessary to optimize the performance, reliability, and sustainability of electrical power systems, enabling them to meet the ever-growing demand for clean and efficient energy.

In conclusion, Monitoring and Control of Electrical Power Systems using Machine Learning Techniques is a must-read for anyone interested in advancing the state-of-the-art in the control and monitoring of electrical power systems. With its comprehensive coverage of deep learning, spatio-temporal, and advanced signal processing methods, this book provides valuable insights and practical solutions for professionals and researchers working in the field of power systems.

Weight: 450g
Dimension: 229 x 152 (mm)
ISBN-13: 9780323999045