Intelligent Data Mining and Analysis in Power and Energy Systems

Zita A. Vale , Tiago Pinto , Michael Negnevitsky , Ganesh Kumar Venayagamoorthy 지음

Wiley-IEEE Press 2022년 12월 02일 출간

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책소개

Intelligent Data Mining and Analysis in Power and Energy Systems A hands-on and current review of data mining and analysis and their applications to power and energy systems In Intelligent Data Mining and Analysis in Power and Energy Systems: Models and Applications for Smarter Efficient Power Systems, the editors assemble a team of distinguished engineers to deliver a practical and incisive review of cutting-edge information on data mining and intelligent data analysis models as they relate to power and energy systems. You’ll find accessible descriptions of state-of-the-art advances in intelligent data mining and analysis and see how they drive innovation and evolution in the development of new technologies. The book combines perspectives from authors distributed around the world with expertise gained in academia and industry. It facilitates review work and identification of critical points in the research and offers insightful commentary on likely future developments in the field. It also provides: A thorough introduction to data mining and analysis, including the foundations of data preparation and a review of various analysis models and methods In-depth explorations of clustering, classification, and forecasting Intensive discussions of machine learning applications in power and energy systems Perfect for power and energy systems designers, planners, operators, and consultants, Intelligent Data Mining and Analysis in Power and Energy Systems will also earn a place in the libraries of software developers, researchers, and students with an interest in data mining and analysis problems.

목차

About the Editors Notes on Contributors Preface PART I. Data Mining and Analysis Fundamentals 1. Foundations Ansel Y. Rodríguez González, Angel Díaz Pacheco, Ramón Aranda, and Miguel Angel Carmona 2. Data mining and analysis in power and energy systems: an introduction to algorithms and applications Fernando Lezama 3. Deep Learning in Intelligent Power and Energy Systems Bruno Mota, Tiago Pinto, Zita Vale, and Carlos Ramos PART II. Clustering 4. Data Mining Techniques applied to Power Systems Sérgio Ramos, João Soares, Zahra Forouzandeh, and Zita Vale 5. Synchrophasor Data Analytics for Anomaly and Event Detection, Classification and Localization Sajan K. Sadanandan, A. Ahmed, S. Pandey, and Anurag K. Srivastava 6. Clustering Methods for the Profiling of Electricity Consumers Owning Energy Storage System Cátia Silva, Pedro Faria, Zita Vale, and Juan Manuel Corchado PART III. Classification 7. A Novel Framework for NTL Detection in Electric Distribution Systems Chia-Chi Chu, Nelson Fabian Avila, Gerardo Figueroa, and Wen-Kai Lu 8. Electricity market participation profiles classification for decision support in market negotiation Tiago Pinto and Zita Vale 9. Socio-demographic, economic and behavioural analysis of electric vehicles Rúben Barreto, Tiago Pinto, and Zita Vale PART IV. Forecasting 10. A Multivariate Stochastic Spatio-Temporal Wind Power Scenario Forecasting Model Wenlei Bai, Duehee Lee, and Kwang Y. Lee 11. Spatio-Temporal Solar Irradiance and Temperature Data Predictive Estimation Chirath Pathiravasam and Ganesh K. Venayagamoorthy 12. Application of decomposition-based hybrid wind power forecasting in isolated power systems with high renewable energy penetration

작가정보

저자(글) Zita A. Vale

저자(글) Tiago Pinto

저자(글) Michael Negnevitsky

저자(글) Ganesh Kumar Venayagamoorthy

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