This book shows how data science methods can improve decision making for wind energy applications. A broad set of data science methods will be covered, and the data science methods will be described in the context of wind energy applications, with specific wind energy examples and case studies.
This book shows how data science methods can improve decision making for wind energy applications. A broad set of data science methods will be covered, and the data science methods will be described in the context of wind energy applications, with specific wind energy examples and case studies.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Dr. Yu Ding is the Anderson-Interface Chair and Professor in the H. Milton School of Industrial and Systems Engineering at Georgia Tech. Prior to joining Georgia Tech in 2023, he was the Mike and Sugar Barnes Professor of Industrial and Systems Engineering at Texas A&M University and served as Associate Director for Research Engagement of Texas A&M Institute of Data Science. Dr. Ding's research is in the area of data and quality science. He received the 2019 IISE Technical Innovation Award and 2022 INFORMS Impact Prize for his data science innovations impacting wind energy applications. Dr. Ding is a Fellow of IISE and ASME. He has served as editor or associate editor for several major engineering data science journals, including as the 14th Editor in Chief of IISE Transactions, for the term of 2021-2024.
Inhaltsangabe
Chapter 1 Introduction Part I Wind Field Analysis Chapter 2 A Single Time Series Model Chapter 3 Spatiotemporal Chapter 4 Regimeswitching Part II Wind Turbine Performance Analysis Chapter 5 Power Curve Modeling and Analysis Chapter 6 Production Efficiency Analysis Chapter 7 Quantification of Turbine Upgrade Chapter 8 Wake Effect Analysis Chapter 9 Overview of Turbine Maintenance Optimization Chapter 10 Extreme Load Analysis Chapter 11 Computer Simulator Based Load Analysis Chapter 12 Anomaly Detection and Fault Diagnosis
Chapter 1 Introduction Part I Wind Field Analysis Chapter 2 A Single Time Series Model Chapter 3 Spatiotemporal Chapter 4 Regimeswitching Part II Wind Turbine Performance Analysis Chapter 5 Power Curve Modeling and Analysis Chapter 6 Production Efficiency Analysis Chapter 7 Quantification of Turbine Upgrade Chapter 8 Wake Effect Analysis Chapter 9 Overview of Turbine Maintenance Optimization Chapter 10 Extreme Load Analysis Chapter 11 Computer Simulator Based Load Analysis Chapter 12 Anomaly Detection and Fault Diagnosis
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