Predictive Maintenance Framework Applied To Wind Turbines Sensor Data

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Predictive Maintenance Framework Applied to Wind Turbines Sensor Data

Author : Carlos Molina Mendiola
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (112 download)

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Book Synopsis Predictive Maintenance Framework Applied to Wind Turbines Sensor Data by : Carlos Molina Mendiola

Download or read book Predictive Maintenance Framework Applied to Wind Turbines Sensor Data written by Carlos Molina Mendiola and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Maintenance costs have an important impact in wind energy profits. The main goal of this project is to implement a predictive maintenance framework as an added routine for controlling wind turbines status. Based on an statistical approach, this framework has a relevant impact in increase production and saving operational costs. Predictive maintenance methodology is based on an early warning system to detect failures (work orders emitted from the control system) before they occur. Two approaches are developed. Latent environmental and internal factors might be detected with power curve study, where individual power curve in a normal performance status is compared against individual empirical power curves in different states. On the other hand, specific part failures are more suitable to be found using normal models from sensors and then comparing with individual signals. Both ways end up with an on go failure detection system. Condition monitored data is extracted from turbines through SCADA, a system that provides sensor signals from different parts of the system. Failure data is processed from a the register of work order per machine.

A Machine Learning Framework for Predictive Maintenance of Wind Turbines

Author : Katherine Yuchen Wang
Publisher :
ISBN 13 :
Total Pages : 75 pages
Book Rating : 4.:/5 (123 download)

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Book Synopsis A Machine Learning Framework for Predictive Maintenance of Wind Turbines by : Katherine Yuchen Wang

Download or read book A Machine Learning Framework for Predictive Maintenance of Wind Turbines written by Katherine Yuchen Wang and published by . This book was released on 2020 with total page 75 pages. Available in PDF, EPUB and Kindle. Book excerpt: Wind energy is one of the fastest growing energy sources in the world. However, the failure to detect the breakdown of turbine parts can be very costly. Wind energy companies have increasingly turned to machine learning to improve wind turbine reliability. Thus, the goal of this thesis is to create a flexible and extensible machine learning framework that enables wind energy experts to define and build models for the predictive maintenance of wind turbines. We contribute two libraries that provide experts with the necessary tools to solve prediction problems in the wind energy industry. The first is GPE, which translates and uses the desired prediction problem to generate machine learning training examples from turbine operations data. The other library, CMS-ML, provides the architecture for building machine learning models using vibration data generated by turbine sensors within the Condition Monitoring System (CMS). With this architecture, we can easily create modular feature engineering and machine learning pipelines for the CMS signal data. Finally, we demonstrate the application of these two libraries on proprietary wind turbine data and analyze the effects of their parameters.

Zephyr

Author : Frances R. Hartwell
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (139 download)

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Book Synopsis Zephyr by : Frances R. Hartwell

Download or read book Zephyr written by Frances R. Hartwell and published by . This book was released on 2023 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Because wind turbines often operate through harsh weather events, under variable operating conditions, and in difficult-to-access locations, turbine maintenance is often challenging and costly. In this thesis, we present Zephyr, a flexible machine learning framework for predictive maintenance of wind energy assets. Manual analysis of wind turbine data is difficult and time-consuming due to its volume, variety, and, most importantly, the need for quick detection of issues. Machine learning (ML) methods are able to automate large-scale data analysis. However, the enormous amount of contextual information required to actually understand the data impedes the ability of ML frameworks to provide actionable insights. To this end, Zephyr enables Subject Matter Experts (SMEs) to incorporate their knowledge at various stages of ML model development. The Zephyr framework consists of a signal-processing-based featurization library, a data labeling algorithm - which helps analyze operational data and maintenance events in order to create labels for machine learning problems - and a set of automated machine learning pipelines for predicting outcome types. SMEs incorporate their expertise by providing labeling functions, bands for frequency domain-based featurization, and several other inputs in an intuitive way. We demonstrate the efficacy of this framework through two case studies involving maintenance operation data from wind turbines. Moreover, we show that ML performance can increase when involving domain expertise by a value as high as 48%.

Maintenance Management of Wind Turbines

Author : Fausto Pedro García Márquez
Publisher : MDPI
ISBN 13 : 3039366297
Total Pages : 394 pages
Book Rating : 4.0/5 (393 download)

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Book Synopsis Maintenance Management of Wind Turbines by : Fausto Pedro García Márquez

Download or read book Maintenance Management of Wind Turbines written by Fausto Pedro García Márquez and published by MDPI. This book was released on 2020-12-06 with total page 394 pages. Available in PDF, EPUB and Kindle. Book excerpt: “Maintenance Management of Wind Turbines” considers the main concepts and the state-of-the-art, as well as advances and case studies on this topic. Maintenance is a critical variable in industry in order to reach competitiveness. It is the most important variable, together with operations, in the wind energy industry. Therefore, the correct management of corrective, predictive and preventive politics in any wind turbine is required. The content also considers original research works that focus on content that is complementary to other sub-disciplines, such as economics, finance, marketing, decision and risk analysis, engineering, etc., in the maintenance management of wind turbines. This book focuses on real case studies. These case studies concern topics such as failure detection and diagnosis, fault trees and subdisciplines (e.g., FMECA, FMEA, etc.) Most of them link these topics with financial, schedule, resources, downtimes, etc., in order to increase productivity, profitability, maintainability, reliability, safety, availability, and reduce costs and downtime, etc., in a wind turbine. Advances in mathematics, models, computational techniques, dynamic analysis, etc., are employed in analytics in maintenance management in this book. Finally, the book considers computational techniques, dynamic analysis, probabilistic methods, and mathematical optimization techniques that are expertly blended to support the analysis of multi-criteria decision-making problems with defined constraints and requirements.

Proceedings of the IV Workshop on Disruptive Information and Communication Technologies for Innovation and Digital Transformation

Download Proceedings of the IV Workshop on Disruptive Information and Communication Technologies for Innovation and Digital Transformation PDF Online Free

Author : Carlos Ramos
Publisher : Ediciones Universidad de Salamanca
ISBN 13 : 8413115833
Total Pages : 126 pages
Book Rating : 4.4/5 (131 download)

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Book Synopsis Proceedings of the IV Workshop on Disruptive Information and Communication Technologies for Innovation and Digital Transformation by : Carlos Ramos

Download or read book Proceedings of the IV Workshop on Disruptive Information and Communication Technologies for Innovation and Digital Transformation written by Carlos Ramos and published by Ediciones Universidad de Salamanca. This book was released on 2022-04-15 with total page 126 pages. Available in PDF, EPUB and Kindle. Book excerpt: Descripción / Resumen (Español / Castellano): El intercambio de ideas entre científicos y técnicos, tanto del ámbito académico como empresarial, es fundamental para facilitar el desarrollo de sistemas que puedan satisfacer las demandas de la sociedad actual. La transferencia de tecnología en este campo sigue siendo un reto y, por ello, este tipo de aportaciones se consideran de forma destacada en esta recopilación. Este libro trae debates y publicaciones sobre el desarrollo de técnicas innovadoras de problemas complejos de IoT. El programa técnico se centra tanto en la alta calidad como en la diversidad, con contribuciones en áreas de investigación bien establecidas y en evolución. Específicamente, 10 capítulos fueron presentados a este libro. Los editores alentaron y agradecieron particularmente las contribuciones sobre IA y computación distribuida en aplicaciones de IoT. Los editores agradecen especialmente el apoyo financiero del proyecto “Virtual-Ledgers-Tecnologías DLT/Blockchain y Cripto-IOT sobre organizaciones virtuales de agentes ligeros y su aplicación en la eficiencia en el transporte de última milla”, ID SA267P18, financiado por Junta de Castilla y León y fondos FEDER. Descripción / Resumen (Inglés): The exchange of ideas between scientists and technicians, from both academic and business areas, is essential in order to ease the development of systems which can meet the demands of today’s society. Technology transfer in this field is still a challenge and, for that reason, this type of contributions are notably considered in this compilation. This book brings in discussions and publications concerning the development of innovative techniques of IoT complex problems. The technical program focuses both on high quality and diversity, with contributions in well-established and evolving areas of research. Specifically, 10 chapters were submitted to this book. The editors particularly encouraged and welcomed contributions on AI and distributed computing in IoT applications. The editors are specially grateful for the funding supporting by the project “Virtual-Ledgers-Tecnologías DLT/Blockchain y Cripto-IOT sobre organizaciones virtuales de agentes ligeros y su aplicación en la eficiencia en el transporte de última milla”, ID SA267P18, financed by regional government of Castilla y León and FEDER funds.

Predictive Engineering in Wind Energy

Author : Wenyan Li
Publisher :
ISBN 13 :
Total Pages : 0 pages
Book Rating : 4.:/5 (958 download)

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Book Synopsis Predictive Engineering in Wind Energy by : Wenyan Li

Download or read book Predictive Engineering in Wind Energy written by Wenyan Li and published by . This book was released on 2009 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: The large-scale wind energy industry is relatively new and is rapidly expanding. The ability of a wind turbine to extract power from the wind is a function of three main factors: the measured wind speed, the power curve of the turbine, and the ability of the machine to handle wind fluctuations. The key parameter determining wind turbine performance is wind speed and it is normally measured with an anemometer placed at the nacelle of a turbine. The dynamic nature of wind speed, however, is a barrier for applying predictive engineering in wind energy. Traditional approaches based on physical science and mathematical modelings have limitations on wind power prediction models. Conventional approach based on dynamic modeling has disadvantage of power generation process modeling due to time-shift nature of the process. Data mining is a promising approach for modeling wind energy, e.g., power prediction and optimization, wind speed forecasting, power curve monitoring and fault diagnosis. It involves a number of steps including data pre-processing, data sampling, feature selection, dimension reduction and, etc. This thesis focus on applying data mining to predictive engineering in wind industry, and ultimately builds wind speed prediction and wind farm power prediction models, develops turbine dynamic control and power optimization strategy, explores methodology for system level fault diagnosis. However the philosophy, methods and frameworks discussed in this research can also be applied to other industrial processes. This thesis proposes a series of predictive models under the framework of data mining. Chapter 2 introduces a methodology for short term wind speed prediction based on wind farm layout information. Chapter 3 and Chapter 4 present prediction models for wind turbine parameters. Chapter 5 proposes strategies for dynamic control of wind turbines. Chapter 6 explores the fault diagnosis and prediction using SCADA data.

Big Data Analytics Framework for Smart Grids

Author : Rajkumar Viral
Publisher : CRC Press
ISBN 13 : 1003828027
Total Pages : 220 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Big Data Analytics Framework for Smart Grids by : Rajkumar Viral

Download or read book Big Data Analytics Framework for Smart Grids written by Rajkumar Viral and published by CRC Press. This book was released on 2023-12-22 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: The text comprehensively discusses smart grid operations and the use of big data analytics in overcoming the existing challenges. It covers smart power generation, transmission, and distribution, explains energy management systems, artificial intelligence, and machine learning–based computing. •Presents a detailed state-of-the-art analysis of big data analytics and its uses in power grids. • Describes how the big data analytics framework has been used to display energy in two scenarios including a single house and a smart grid with thousands of smart meters. •Explores the role of the internet of things, artificial intelligence, and machine learning in smart grids. • Discusses edge analytics for integration of generation technologies, and decision-making approaches in detail. • Examines research limitations and presents recommendations for further research to incorporate big data analytics into power system design and operational frameworks. The text presents a comprehensive study and assessment of the state-of-the-art research and development related to the unique needs of electrical utility grids, including operational technology, storage, processing, and communication systems. It further discusses important topics such as complex adaptive power system, self-healing power system, smart transmission, and distribution networks, and smart metering infrastructure. It will serve as an ideal reference text for senior undergraduate, graduate students, and academic researchers in the areas such as electrical engineering, electronics and communications engineering, computer engineering, and information technology.

An Introduction to Predictive Maintenance

Author : R. Keith Mobley
Publisher : Elsevier
ISBN 13 : 0080478697
Total Pages : 451 pages
Book Rating : 4.0/5 (84 download)

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Book Synopsis An Introduction to Predictive Maintenance by : R. Keith Mobley

Download or read book An Introduction to Predictive Maintenance written by R. Keith Mobley and published by Elsevier. This book was released on 2002-10-24 with total page 451 pages. Available in PDF, EPUB and Kindle. Book excerpt: This second edition of An Introduction to Predictive Maintenance helps plant, process, maintenance and reliability managers and engineers to develop and implement a comprehensive maintenance management program, providing proven strategies for regularly monitoring critical process equipment and systems, predicting machine failures, and scheduling maintenance accordingly. Since the publication of the first edition in 1990, there have been many changes in both technology and methodology, including financial implications, the role of a maintenance organization, predictive maintenance techniques, various analyses, and maintenance of the program itself. This revision includes a complete update of the applicable chapters from the first edition as well as six additional chapters outlining the most recent information available. Having already been implemented and maintained successfully in hundreds of manufacturing and process plants worldwide, the practices detailed in this second edition of An Introduction to Predictive Maintenance will save plants and corporations, as well as U.S. industry as a whole, billions of dollars by minimizing unexpected equipment failures and its resultant high maintenance cost while increasing productivity. A comprehensive introduction to a system of monitoring critical industrial equipment Optimize the availability of process machinery and greatly reduce the cost of maintenance Provides the means to improve product quality, productivity and profitability of manufacturing and production plants

Maintenance, Replacement, and Reliability

Author : Andrew K. S. Jardine
Publisher : CRC Press
ISBN 13 : 042966446X
Total Pages : 419 pages
Book Rating : 4.4/5 (296 download)

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Book Synopsis Maintenance, Replacement, and Reliability by : Andrew K. S. Jardine

Download or read book Maintenance, Replacement, and Reliability written by Andrew K. S. Jardine and published by CRC Press. This book was released on 2021-09-15 with total page 419 pages. Available in PDF, EPUB and Kindle. Book excerpt: Since the publication of the second edition in 2013, there has been an increasing interest in asset management globally, as evidenced by a series of international standards on asset management systems, to achieve excellence in asset management. This cannot be achieved without high-quality data and the tools for data interpretation. The importance of such requirements is widely recognized by industry. The third edition of this textbook focuses on tools for physical asset management decisions that are data driven. It also uses a theoretical foundation to the tools (mathematical models) that can be used to optimize a variety of key maintenance/replacement/reliability decisions. Problem sets with answers are provided at the end of each chapter. Also available is an extensive set of PowerPoint slides and a solutions manual upon request with qualified textbook adoptions. This new edition can be used in undergraduate or post-graduate courses on physical asset management.

Handbook of Dynamic Data Driven Applications Systems

Author : Frederica Darema
Publisher : Springer Nature
ISBN 13 : 3031279867
Total Pages : 937 pages
Book Rating : 4.0/5 (312 download)

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Book Synopsis Handbook of Dynamic Data Driven Applications Systems by : Frederica Darema

Download or read book Handbook of Dynamic Data Driven Applications Systems written by Frederica Darema and published by Springer Nature. This book was released on 2023-10-16 with total page 937 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Second Volume in the series Handbook of Dynamic Data Driven Applications Systems (DDDAS) expands the scope of the methods and the application areas presented in the first Volume and aims to provide additional and extended content of the increasing set of science and engineering advances for new capabilities enabled through DDDAS. The methods and examples of breakthroughs presented in the book series capture the DDDAS paradigm and its scientific and technological impact and benefits. The DDDAS paradigm and the ensuing DDDAS-based frameworks for systems’ analysis and design have been shown to engender new and advanced capabilities for understanding, analysis, and management of engineered, natural, and societal systems (“applications systems”), and for the commensurate wide set of scientific and engineering fields and applications, as well as foundational areas. The DDDAS book series aims to be a reference source of many of the important research and development efforts conducted under the rubric of DDDAS, and to also inspire the broader communities of researchers and developers about the potential in their respective areas of interest, of the application and the exploitation of the DDDAS paradigm and the ensuing frameworks, through the examples and case studies presented, either within their own field or other fields of study. As in the first volume, the chapters in this book reflect research work conducted over the years starting in the 1990’s to the present. Here, the theory and application content are considered for: Foundational Methods Materials Systems Structural Systems Energy Systems Environmental Systems: Domain Assessment & Adverse Conditions/Wildfires Surveillance Systems Space Awareness Systems Healthcare Systems Decision Support Systems Cyber Security Systems Design of Computer Systems The readers of this book series will benefit from DDDAS theory advances such as object estimation, information fusion, and sensor management. The increased interest in Artificial Intelligence (AI), Machine Learning and Neural Networks (NN) provides opportunities for DDDAS-based methods to show the key role DDDAS plays in enabling AI capabilities; address challenges that ML-alone does not, and also show how ML in combination with DDDAS-based methods can deliver the advanced capabilities sought; likewise, infusion of DDDAS-like approaches in NN-methods strengthens such methods. Moreover, the “DDDAS-based Digital Twin” or “Dynamic Digital Twin”, goes beyond the traditional DT notion where the model and the physical system are viewed side-by-side in a static way, to a paradigm where the model dynamically interacts with the physical system through its instrumentation, (per the DDDAS feed-back control loop between model and instrumentation).

Predictive Maintenance of Wind Generators Based on AI Techniques

Author : Emin Elmar oglu Mammadov
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (126 download)

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Book Synopsis Predictive Maintenance of Wind Generators Based on AI Techniques by : Emin Elmar oglu Mammadov

Download or read book Predictive Maintenance of Wind Generators Based on AI Techniques written by Emin Elmar oglu Mammadov and published by . This book was released on 2019 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: As global warming is slowly becoming a dangerous reality, governments and private institutions are introducing policies to minimize it. Those policies have led to the development and deployment of Renewable Energy Sources (RESs), which introduces new challenges, among which the minimization of downtime and Levelised Cost of Energy (LCOE) by optimizing maintenance strategy where early detection of incipient faults is of significant intent. Hence, this is the focus of this thesis. While there are several maintenance approaches, predictive maintenance can utilize SCADA readings from large scale power plants to detect early signs of failures, which can be characterized by abnormal patterns in the measurements. There exists several approaches to detect these patterns such as model-based or hybrid techniques, but these require the detailed knowledge of the analyzed system. As SCADA system collects large amounts of data, machine learning techniques can be used to detect the underlying failure patterns and notify customers of the abnormal behaviour. In this work, a novel framework based on machine learning techniques for fault prediction of wind farm generators is developed for an actual customer. The proposed fault prognosis methodology addresses data limitation such as class imbalance and missing data, performs statistical tests on time series to test for its stationarity, selects the features with the most predictive power, and applies machine learning models to predict a fault with 1 hour horizon. The proposed techniques are tested and validated using historical data for a wind farm in Summerside, Prince Edward Island (PEI), Canada, and models are evaluated based on appropriate evaluation metrics. The results demonstrate the ability of the proposed methodology to predict wind generator failures, and the viability of the proposed methodology for optimizing preventive maintenance strategies.

Digitalization of Power Markets and Systems Using Energy Informatics

Author : Umit Cali
Publisher : Springer Nature
ISBN 13 : 3030833011
Total Pages : 255 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Digitalization of Power Markets and Systems Using Energy Informatics by : Umit Cali

Download or read book Digitalization of Power Markets and Systems Using Energy Informatics written by Umit Cali and published by Springer Nature. This book was released on 2021-09-26 with total page 255 pages. Available in PDF, EPUB and Kindle. Book excerpt: The objective of this textbook is to introduce students and professionals to fundamental principles and techniques and emerging technologies in energy informatics and the digitalization of power markets and systems. The book covers such areas as smart grids and artificial intelligence (AI) and distributed ledger technology (DLT), with a focus on information and communication technologies (ICT) deployed to modernize the electric energy infrastructure. It also provides an overview of the smart grid and its main components: smart grid applications at transmission, distribution, and customer level, network requirements with communications technologies, and standards and protocols. In addition, the book addresses emerging technologies and trends in next-generation power systems, i.e., energy informatics, such as digital green shift, energy cyber-physical-social systems (E-CPSS), energy IoT, energy blockchain, and advanced optimization. Future aspects of digitalized power markets and systems will be discussed with real-world energy informatics projects. The book is designed to be a core text in upper-undergraduate and graduate courses such as Introduction to Smart Grids, Digitalization of Power Systems, and Advanced Power System Topics in Energy Informatics.

Dynamics in Logistics

Author : Herbert Kotzab
Publisher : Springer
ISBN 13 : 3319235125
Total Pages : 697 pages
Book Rating : 4.3/5 (192 download)

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Book Synopsis Dynamics in Logistics by : Herbert Kotzab

Download or read book Dynamics in Logistics written by Herbert Kotzab and published by Springer. This book was released on 2015-12-21 with total page 697 pages. Available in PDF, EPUB and Kindle. Book excerpt: This contributed volume brings together research papers presented at the 4th International Conference on Dynamics in Logistics, held in Bremen, Germany in February 2014. The conference focused on the identification, analysis and description of the dynamics of logistics processes and networks. Topics covered range from the modeling and planning of processes, to innovative methods like autonomous control and knowledge management, to the latest technologies provided by radio frequency identification, mobile communication, and networking. The growing dynamic poses wholly new challenges: logistics processes and networks must be(come) able to rapidly and flexibly adapt to constantly changing conditions. The book primarily addresses the needs of researchers and practitioners from the field of logistics, but will also be beneficial for graduate students.

Predictive Maintenance Modelling on Offshore Wind Turbines

Author : Luke Simon Payne
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (132 download)

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Book Synopsis Predictive Maintenance Modelling on Offshore Wind Turbines by : Luke Simon Payne

Download or read book Predictive Maintenance Modelling on Offshore Wind Turbines written by Luke Simon Payne and published by . This book was released on 2022 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt:

Wireless Health Monitoring and Improvement System for Wind Turbines

Author : Suratsavadee Koonlaboon Korkua
Publisher :
ISBN 13 :
Total Pages : pages
Book Rating : 4.:/5 (794 download)

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Book Synopsis Wireless Health Monitoring and Improvement System for Wind Turbines by : Suratsavadee Koonlaboon Korkua

Download or read book Wireless Health Monitoring and Improvement System for Wind Turbines written by Suratsavadee Koonlaboon Korkua and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Wind power has become the world's fastest growing renewable energy resource. The world-wide wind power installed capacity has exceeded 120 GW. The United States has set a target of 20% wind-based electricity generation, over 300 GW, by 2030. As wind power is growing towards becoming a major utility source, it is urgent to guarantee the reliable operation of wind power systems. To avoid unexpected equipment failures, the focus in most wind farm is shifting from scheduled preventive maintenance to predictive maintenance. Predictive maintenance by condition-based monitoring of electrical machines is a scientific approach that is becoming a new strategy for maintenance management. Vibration analysis is also a measurement tool used to identify, predict, and prevent failures in rotating machinery. Implementing vibration analysis will improve the reliability of the machine and lead to better machine efficiency, reducing downtime by eliminating unexpected mechanical or electrical failures. Traditionally, monitoring systems are implemented as in wired systems formed by communication cables and various types of sensors. The cost of installation and maintenance such a system is more expensive than the cost of the sensors themselves. To overcome the restrictions of wired networks, using wireless system for monitoring is proposed. A wireless sensor network is a new control network that integrates the sensors, and embedded computer, wireless communication, and intelligent processing technology. ZigBee is a new wireless networking technology with low power, low cost, and short time-delay characteristics. Compared with other similar standards such as Bluetooth, it tends to provide each single device lower complexity and cost. Based on ZigBee network communication technology, the system can deal with the various operating parameters of remote transmission, real-time data collection, and real-time health monitoring systems. Moreover, ZigBee wireless technology enables the identification of the location of each node under the network with several types of positioning algorithms. This study presents and develops a ZigBee based wireless sensor network for machine health monitoring of induction machines. The three-axis vibration signals obtained from the monitoring system are then processed and analyzed with signal processing techniques. The vibration detection techniques with suitably modified algorithms are used to extract information for an induction machine health diagnostic. The severity level of abnormality and the remaining usable life are also explored. The goal for this research is not only to monitor the machine health of wind turbine system, but also to develop a control method for doubly-fed induction generators (DFIG) that addresses the issues associated to the rotor imbalance condition of the generator. Rotor imbalance is a mechanical disturbance related problem. It is a condition where there is more weight distributed on one side of a rotating part of the rotor than on the other side. It might be caused by wind wheel unbalances, shaft imbalances, or mechanical looseness. This kind of event will directly cause oscillation on the output signal of the generator such as generated output power, current, and voltage. The proposed control method will improve the performance of the DFIG control system by reducing the oscillation of the generator output and allowing the system to operate during the slightly unbalanced condition. To suppress the vibration and minimize the oscillation of the generated output, in addition to reducing the stresses on the wind turbine, the rotor side inverter controller is designed and tested by way of a digital simulation on the Matlab/Simulink platform. The wireless health monitoring system for wind turbine based on vibration detection shows the validity and distinct advantages in such a condition based monitoring system. The severity level of rotor imbalance is successfully estimated by using machine vibration analysis. Moreover, the systematic control design of the proposed vibration suppression by means of a rotor side inverter controller is explored and discussed. The real wind speed data of four different cases from the ERCOT system were used as input to test the performance and capabilities of the control scheme. The simulation results of the generator output show the effectiveness of this proposed rotor side inverter controller. It effectively reduces the oscillation of power, current, and torque output of the DFIG wind turbine.

Energy and Sustainable Futures

Author : Iosif Mporas
Publisher : Springer Nature
ISBN 13 : 3030639169
Total Pages : 274 pages
Book Rating : 4.0/5 (36 download)

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Book Synopsis Energy and Sustainable Futures by : Iosif Mporas

Download or read book Energy and Sustainable Futures written by Iosif Mporas and published by Springer Nature. This book was released on 2021-04-29 with total page 274 pages. Available in PDF, EPUB and Kindle. Book excerpt: This open access book presents papers displayed in the 2nd International Conference on Energy and Sustainable Futures (ICESF 2020), co-organised by the University of Hertfordshire and the University Alliance DTA in Energy. The research included in this book covers a wide range of topics in the areas of energy and sustainability including: • ICT and control of energy;• conventional energy sources;• energy governance;• materials in energy research;• renewable energy; and• energy storage. The book offers a holistic view of topics related to energy and sustainability, making it of interest to experts in the field, from industry and academia.

Data Science for Wind Energy

Author : Yu Ding
Publisher : CRC Press
ISBN 13 : 0429956517
Total Pages : 400 pages
Book Rating : 4.4/5 (299 download)

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Book Synopsis Data Science for Wind Energy by : Yu Ding

Download or read book Data Science for Wind Energy written by Yu Ding and published by CRC Press. This book was released on 2019-06-04 with total page 400 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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