Supervised Machine Learning In Wind Forecasting And Ramp Event Prediction
Supervised Machine Learning In Wind Forecasting And Ramp Event Prediction Book in PDF, ePub and Kindle version is available to download in english. Read online anytime anywhere directly from your device. Click on the download button below to get a free pdf file of Supervised Machine Learning In Wind Forecasting And Ramp Event Prediction book. This book definitely worth reading, it is an incredibly well-written.
Supervised Machine Learning in Wind Forecasting and Ramp Event Prediction by Harsh S. Dhiman,Valentina Emilia Balas Pdf
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 models Offers global case studies for turbine wind farm layouts Includes state-of-the-art models and methodologies in wind forecasting
Supervised Machine Learning in Wind Forecasting and Ramp Event Prediction by Harsh S. Dhiman,Dipankar Deb,Valentina Emilia Balas Pdf
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 models Offers global case studies for turbine wind farm layouts Includes state-of-the-art models and methodologies in wind forecasting
Renewable Energy Optimization, Planning and Control by Anita Khosla,Monika Aggarwal Pdf
This book gathers selected high-quality research papers presented at International Conference on Renewable Technologies in Engineering (ICRTE 2021) organized by Manav Rachna International Institute of Research & Studies, Faridabad, Haryana, India, during 15–16 April 2021. The book includes conference papers on the theme “Computational Techniques for Renewable Energy Optimization”, which aims to bring together leading academic scientists, researchers and research scholars to exchange and share their experiences and research results on all aspects of renewable energy integration, planning, control and optimization. It also provides a premier interdisciplinary platform for researchers, practitioners and educators to present and discuss the most recent innovations, trends and concerns as well as practical challenges encountered and solutions adopted in the fields of renewable energy and resources.
Soft Computing Applications by Valentina Emilia Balas,Lakhmi C. Jain,Marius Mircea Balas,Shahnaz N. Shahbazova Pdf
This book presents the proceedings of the 8th International Workshop on Soft Computing Applications, SOFA 2018, held on 13–15 September 2018 in Arad, Romania. The workshop was organized by Aurel Vlaicu University of Arad, in conjunction with the Institute of Computer Science, Iasi Branch of the Romanian Academy, IEEE Romanian Section, Romanian Society of Control Engineering and Technical Informatics – Arad Section, General Association of Engineers in Romania – Arad Section and BTM Resources Arad. The papers included in these proceedings, published post-conference, cover the research including Knowledge-Based Technologies for Web Applications, Cloud Computing, Security Algorithms and Computer Networks, Business Process Management, Computational Intelligence in Education and Modelling and Applications in Textiles and many other areas related to the Soft Computing. The book is directed to professors, researchers, and graduate students in area of soft computing techniques and applications.
Corrosion and Corrosion Protection of Wind Power Structures in Marine Environments by Andreas Momber Pdf
Corrosion and Corrosion Protection of Wind Power Structures in Marine Environments: Volume 2: Corrosion Protection Measures offers the first comprehensive review on corrosion and corrosion protection of offshore wind power structures. The book extensively discusses corrosion phenomena and corrosion types in different marine corrosion zones, including the modeling of corrosion processes and interactions between corrosion and structural stability. The book addresses important design issues, namely materials selection relevant to their performance in marine environments, corrosion allowance, and constructive design. Active and passive corrosion protection measures are emphasized, with special sections on cathodic corrosion protection and the use of protective coatings. Seawater related issues associated with cathodic protection, such as calcareous deposit formation, hydrogen formation, and fouling, are discussed. With respect to protective coatings, the book considers, for the first time, complete loading scenarios, including corrosive loads, mechanical loads, and special loads, and covers a wide range of coating materials. Problems associated with fouling and bacterial-induced corrosion are extensively reviewed. The book closes with a chapter on recent developments in maintenance strategies, inspection techniques, and repair technologies. The book will be of special interest to materials scientists, materials developers, corrosion engineers, maintenance engineers, civil engineers, steel work designers, mechanical engineers, marine engineers, chemists, and coating specialists. Offshore wind power is an emerging renewable technology and a key factor for a cleaner environment. Offshore wind power structures are situated in a demanding and challenging marine environment. The structures are loaded in a complex way, including mechanical loads and corrosive loads. Corrosion is one of the major limiting factors to the reliability and performance of the technology. Maintenance and repair of corrosion protection systems are particularly laborious and costly. Explores the literature between 1950 and 2020 and contains over 2000 references Offers the most complete monograph on the issue Covers all aspects of corrosion protection in detail, including coatings, cathodic protection, corrosion allowance, constructive design, as well as maintenance and repair Delivers the most complete review on corrosion of metals in marine/offshore environments Focuses on all aspects of offshore wind power structures, namely foundations, towers, internal sections, connection flanges, and transformation platforms
Wind Power Ensemble Forecasting by André Gensler Pdf
This thesis describes performance measures and ensemble architectures for deterministic and probabilistic forecasts using the application example of wind power forecasting and proposes a novel scheme for the situation-dependent aggregation of forecasting models. For performance measures, error scores for deterministic as well as probabilistic forecasts are compared, and their characteristics are shown in detail. For the evaluation of deterministic forecasts, a categorization by basic error measure and normalization technique is introduced that simplifies the process of choosing an appropriate error measure for certain forecasting tasks. Furthermore, a scheme for the common evaluation of different forms of probabilistic forecasts is proposed. Based on the analysis of the error scores, a novel hierarchical aggregation technique for both deterministic and probabilistic forecasting models is proposed that dynamically weights individual forecasts using multiple weighting factors such as weather situation and lead time dependent weighting. In the experimental evaluation it is shown that the forecasting quality of the proposed technique is able to outperform other state of the art forecasting models and ensembles.
Advances in Computational Intelligence by Ignacio Rojas,Gonzalo Joya,Joan Cabestany Pdf
This two-volume set LNCS 7902 and 7903 constitutes the refereed proceedings of the 12th International Work-Conference on Artificial Neural Networks, IWANN 2013, held in Puerto de la Cruz, Tenerife, Spain, in June 2013. The 116 revised papers were carefully reviewed and selected from numerous submissions for presentation in two volumes. The papers explore sections on mathematical and theoretical methods in computational intelligence, neurocomputational formulations, learning and adaptation emulation of cognitive functions, bio-inspired systems and neuro-engineering, advanced topics in computational intelligence and applications
Improving Short-term Wind Power Forecasting Through Measurements and Modeling of the Tehachapi Wind Resource Area by Aubryn Cooperman,Cornelis P. Van Dam,John Zack,Shu-Hua Chen,Clinton Paul MacDonald,California Wind Energy Collaborative Pdf
Development of an Offshore Specific Wind Power Forecasting System by Melih Kurt Pdf
This study explains the data preparation processes, plausibility checking of meteorological parameters, correction of met-mast wind speed, and also the determination of the nominal power of a wind farm using met-mast measurements. The wind speed correction of met-mast FINO1 is evaluated from the perspective of power produced by alpha ventus by using uncorrected and corrected measurements from this met-mast. Afterwards this data is used for the determination of nominal power for alpha ventus.
Data Science for Wind Energy provides an in-depth discussion on how data science methods can improve decision making for wind energy applications, near-ground wind field analysis and forecast, turbine power curve fitting and performance analysis, turbine reliability assessment, and maintenance optimization for wind turbines and wind farms. A broad set of data science methods covered, including time series models, spatio-temporal analysis, kernel regression, decision trees, kNN, splines, Bayesian inference, and importance sampling. More importantly, the data science methods are described in the context of wind energy applications, with specific wind energy examples and case studies. Please also visit the author’s book site at https://aml.engr.tamu.edu/book-dswe. Features Provides an integral treatment of data science methods and wind energy applications Includes specific demonstration of particular data science methods and their use in the context of addressing wind energy needs Presents real data, case studies and computer codes from wind energy research and industrial practice Covers material based on the author's ten plus years of academic research and insights
Computational Sustainability by Jörg Lässig,Kristian Kersting,Katharina Morik Pdf
The book at hand gives an overview of the state of the art research in Computational Sustainability as well as case studies of different application scenarios. This covers topics such as renewable energy supply, energy storage and e-mobility, efficiency in data centers and networks, sustainable food and water supply, sustainable health, industrial production and quality, etc. The book describes computational methods and possible application scenarios.
Windsense Project by Rob Kamisky,Cornelis P. Van Dam,Clinton Paul MacDonald,Craig Collier,University of California, Davis,Sonoma Technology Inc,DNV GL (Firm) Pdf
Decision and Control in Hybrid Wind Farms by Harsh S. Dhiman,Dipankar Deb Pdf
This book focuses on two of the most important aspects of wind farm operation: decisions and control. The first part of the book deals with decision-making processes, and explains that hybrid wind farm operation is governed by a set of alternatives that the wind farm operator must choose from in order to achieve optimal delivery of wind power to the utility grid. This decision-making is accompanied by accurate forecasts of wind speed, which must be known beforehand. Errors in wind forecasting can be compensated for by pumping power from a reserve capacity to the grid using a battery energy storage system (BESS). Alternatives based on penalty cost are assessed using certain criteria, and MCDM methods are used to evaluate the best choice. Further, considering the randomness in the dynamic phenomenon in wind farms, a fuzzy MCDM approach is applied during the decision-making process to evaluate the best alternative for hybrid wind farm operation. Case studies from wind farms in the USA are presented, together with numerical solutions to the problem. In turn, the second part deals with the control aspect, and especially with yaw angle control, which facilitates power maximization at wind farms. A novel transfer function-based methodology is presented that controls the wake center of the upstream turbine(s); lidar-based numerical simulation is carried out for wind farm layouts; and an adaptive control strategy is implemented to achieve the desired yaw angle for upstream turbines. The proposed methodology is tested for two wind farm layouts. Wake management is also implemented for hybrid wind farms where BESS life enhancement is studied. The effect of yaw angle on the operational cost of BESS is assessed, and case studies for wind farm datasets from the USA and Denmark are discussed. Overall, the book provides a comprehensive guide to decision and control aspects for hybrid wind farms, which are particularly important from an industrial standpoint.