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Supervised Machine Learning in Wind Forecasting and Ramp Event Prediction provides an up-to- date overview on the broad area of wind generation and forecasting, with a focus on the role and need of Machine Learning in this emerging field of knowledge. Various regression models and signal decomposition techniques are presented and analyzed, including least-square, twin support and random forest regression, all with supervised Machine Learning. The specific topics of ramp event prediction and wake interactions are addressed in this book, along with forecasted performance. Wind speed forecasting has become an essential component to ensure power system security, reliability and safe operation, making this reference useful for all researchers and professionals researching renewable energy, wind energy forecasting and generation. Features various supervised machine learning based regression modelsOffers global case studies for turbine wind farm layoutsIncludes state-of-the-art models and methodologies in wind forecasting
Approx.744 pages
Approx.734 pages
Fundamentals of Wind Farm Aerodynamic Layout Design, Volume Four provides readers with effective wind farm design and layout guidance through algorithm optimization, going beyond other references and general approaches in literature. Focusing on interactions of wake models, designers can combine numerical schemes presented in this book which also considers wake models¿ effects and problems on layout optimization in order to simulate and enhance wind farm designs. Covering the aerodynamic modeling and simulation of wind farms, the book's authors include experimental tests supporting modeling simulations and tutorials on the simulation of wind turbines. In addition, the book includes a CFD technique designed to be more computationally efficient than currently available techniques, making this book ideal for industrial engineers in the wind industry who need to produce an accurate simulation within limited timeframes.
Non-Destructive Testing and Condition Monitoring Techniques in Wind Energy looks at the complex and critical components of energy assets and the importance of inspection and maintenance to ensure their high availability and uninterrupted operation. Presenting the main concepts, state-of-the-art advances and case studies, this book approaches the topic by considering it as an integral part of the overall operation of any wind energy project. Linking the essential NDT subject with its sub disciplines, the book uses computational techniques, dynamic analysis, probabilistic methods, and mathematical optimization techniques to support analysis of prognostic problems with defined constraints and requirements. This book is the first of its kind and will provide useful insights to industrial engineers and scientists, academics and students in the possibilities that NDT and condition monitoring technologies can offer.
Published as an Open Access book available on Science Direct, IEA Wind Recommended Practices for the Implementation of Renewable Energy Forecasting Solutions translates decades of academic knowledge and standard requirements into applicable procedures and decision support tools for the energy industry. Designed specifically for practitioners in the energy industry, readers will find the tools to maximize the value of renewable energy forecast information in operational decision-making applications and significantly reduce the costs of integrating large amounts of wind and solar generation assets into grid systems through more efficient management of the renewable generation variability. Authored by a group of international experts as part of the IEA Wind Task 36 (Wind Energy Forecasting), the book addresses the issue that many current operational forecast solutions are not properly optimized for their intended applications. It provides detailed guidelines and recommended practices on forecast solution selection processes, designing and executing forecasting benchmarks and trials, forecast solution evaluation, verification, and validation, and meteorological and power data requirements for real-time forecasting applications. In addition, the guidelines integrate probabilistic forecasting, integrate wind and solar forecasting, offer improved IT data exchange and data format standards, and have a dedicated section to dealing with the requirements for SCADA and meteorological measurements. A unique and comprehensive reference, IEA Wind Recommended Practices for the Implementation of Renewable Energy Forecasting Solutions is an essential guide for all practitioners involved in wind and solar energy generation forecasting from forecast vendors to end-users of renewable forecasting solutions.
Wind Turbine Icing Physics and Anti-/De-Icing Technology gives a comprehensive update of research on the underlying physics pertinent to wind turbine icing and the development of various effective and robust anti-/de-icing technology for wind turbine icing mitigation. The book introduces the most recent research results derived from both laboratory studies and field experiments. Specifically, the research results based on field measurement campaigns to quantify the characteristics of the ice structures accreted over the blades surfaces of utility-scale wind turbines by using a Supervisory Control and Data Acquisition (SCADA) system and an Unmanned-Aerial-Vehicle (UAV) equipped with a high-resolution digital camera are also introduced. In addition, comprehensive lab experimental studies are explored, along with a suite of advanced flow diagnostic techniques, a detailed overview of the improvements, and the advantages and disadvantages of state-of-the-art ice mitigation strategies. This new addition to the Wind Energy Engineering series will be useful to all researchers and industry professionals who address icing issues through testing, research and industrial innovation. Covers detailed improvements and the advantages/disadvantages of state-of-the-art ice mitigation strategies Includes condition monitoring contents for lab-scale experiments and field tests Presents the potential of various bio-inspired icephobic coatings of wind turbine blades
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