Data Science for Wind Energy

Author:   Yu Ding
Publisher:   Taylor & Francis Ltd
ISBN:  

9781138590526


Pages:   400
Publication Date:   24 May 2019
Format:   Hardback
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

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Data Science for Wind Energy


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Full Product Details

Author:   Yu Ding
Publisher:   Taylor & Francis Ltd
Imprint:   CRC Press
Weight:   0.880kg
ISBN:  

9781138590526


ISBN 10:   1138590525
Pages:   400
Publication Date:   24 May 2019
Audience:   College/higher education ,  General/trade ,  Tertiary & Higher Education ,  General
Format:   Hardback
Publisher's Status:   Active
Availability:   In Print   Availability explained
This item will be ordered in for you from one of our suppliers. Upon receipt, we will promptly dispatch it out to you. For in store availability, please contact us.

Table of Contents

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

Reviews

This is the first book that focuses on the data science methodologies and their applications in a growing field, wind energy. It is well-organized and well-written. It will enhance the knowledge base of data science and its applications in the wind energy field. -- Elsayed A. Elsayed, Professor, Rutgers University


This is the first book that focuses on the data science methodologies and their applications in a growing field, wind energy. It is well-organized and well-written. It will enhance the knowledge base of data science and its applications in the wind energy field. -- Elsayed A. Elsayed, Professor, Rutgers University


Author Information

Yu Ding is the Mike and Sugar Barnes Professor of Industrial and Systems Engineering and Professor of Electrical and Computer Engineering at Texas A&M University, and a Fellow of the Institute of Industrial & Systems Engineers and the American Society of Mechanical Engineers

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