Data Challenges and Data Analytics Solutions for Power Systems

L'abstract è presente nell'allegato / the abstract is in the attachmen

Big Data Analytics in Smart Grids for Renewable Energy Networks: Systematic Review of Information and Communication Technology Tools

El desarrollo industrial y económico de los países industrializados, a partir del siglo XIX, ha ido de la mano del desarrollo de la electricidad, del motor de combustión interna, de los ordenadores, de Internet, de la utilización de datos y del uso intensivo del conocimiento centrado en la ciencia y la tecnología. La mayoría de las fuentes de energía convencionales han demostrado ser finitas y agotables. A su vez, las diferentes actividades de producción de bienes y servicios que utilizan combustibles fósiles y energía convencional, han aumentado significativamente la contaminación del medio ambiente, y con ello, han contribuido al calentamiento global. El objetivo de este trabajo fue realizar una aproximación teórica a las tecnologías de análisis de datos e inteligencia de negocio aplicadas a las redes de sistemas eléctricos inteligentes con energías renovables. Para este trabajo se realizó una revisión bibliométrica y bibliográfica sobre Big Data Analytics, herramientas TIC de la industria 4.0 y Business intelligence en diferentes bases de datos disponibles en el dominio público. Los resultados del análisis indican la importancia del uso de la analítica de datos y la inteligencia de negocio en la gestión de las empresas energéticas. El trabajo concluye señalando cómo se está aplicando la inteligencia de negocio y la analítica de datos en ejemplos concretos de empresas energéticas y su creciente importancia en la toma de decisiones estratégicas y operativasThe industrial and economic development of the industrialized countries, from the nineteenth century, has gone hand in hand with the development of electricity, the internal combustion engine, computers, the Internet, data use and the intensive use of knowledge focused on science and the technology. Most conventional energy sources have proven to be finite and exhaustible. In turn, the different production activities of goods and services using fossil fuels and conventional energy, have significantly increased the pollution of the environment, and with it, contributed to global warming. The objective of this work was to carry out a theoretical approach to data analytics and business intelligence technologies applied to smart electrical-system networks with renewable energies. For this paper, a bibliometric and bibliographic review about Big Data Analytics, ICT tools of industry 4.0 and Business intelligence was carried out in different databases available in the public domain. The results of the analysis indicate the importance of the use of data analytics and business intelligence in the management of energy companies. The paper concludes by pointing out how business intelligence and data analytics are being applied in specific examples of energy companies and their growing importance in strategic and operational decision makinghttps://scienti.minciencias.gov.co/cvlac/visualizador/generarCurriculoCv.do?cod_rh=0000192503https://scholar.google.com/citations?user=9HLAZYUAAAAJ&hl=eshttps://scienti.minciencias.gov.co/gruplac/jsp/visualiza/visualizagr.jsp?nro=00000000005961https://orcid.org/0000-0003-1166-198

Big data analytics in smart grids: a review

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SET2023 : 20th International Conference on Sustainable Energy Technologies 15th to 17th August 2023, Nottingham, UK: Sustainable Energy Technologies 2023 Conference Proceedings. Volume 3

Papers #201 to #300 presented at SET 202

Advances in Sensors, Big Data and Machine Learning in Intelligent Animal Farming

Animal production (e.g., milk, meat, and eggs) provides valuable protein production for human beings and animals. However, animal production is facing several challenges worldwide such as environmental impacts and animal welfare/health concerns. In animal farming operations, accurate and efficient monitoring of animal information and behavior can help analyze the health and welfare status of animals and identify sick or abnormal individuals at an early stage to reduce economic losses and protect animal welfare. In recent years, there has been growing interest in animal welfare. At present, sensors, big data, machine learning, and artificial intelligence are used to improve management efficiency, reduce production costs, and enhance animal welfare. Although these technologies still have challenges and limitations, the application and exploration of these technologies in animal farms will greatly promote the intelligent management of farms. Therefore, this Special Issue will collect original papers with novel contributions based on technologies such as sensors, big data, machine learning, and artificial intelligence to study animal behavior monitoring and recognition, environmental monitoring, health evaluation, etc., to promote intelligent and accurate animal farm management

Dorsal stream : from algorithm to neuroscience

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 173-195).The dorsal stream in the primate visual cortex is involved in the perception of motion and the recognition of actions. The two topics, motion processing in the brain, and action recognition in videos, have been developed independently in the field of neuroscience and computer vision. We present a dorsal stream model that can be used for the recognition of actions as well as explaining neurophysiology in the dorsal stream. The model consists of a spatio-temporal feature detectors of increasing complexity: an input image sequence is first analyzed by an array of motion sensitive units which, through a hierarchy of processing stages, lead to position and scale invariant representation of motion in a video sequence. The model outperforms or on par with the state-of-the-art computer vision algorithms on a range of human action datasets. We then describe the extension of the model into a high-throughput system for the recognition of mouse behaviors in their homecage. We provide software and a very large manually annotated video database used for training and testing the system. Our system outperforms a commercial software and performs on par with human scoring, as measured from the ground-truth manual annotations of more than 10 hours of videos of freely behaving mice. We complete the neurobiological side of the model by showing it could explain the motion processing as well as action selectivity in the dorsal stream, based on comparisons between model outputs and the neuronal responses in the dorsal stream. Specifically, the model could explain pattern and component sensitivity and distribution [161], local motion integration [97], and speed-tuning [144] of MT cells. The model, when combining with the ventral stream model [173], could also explain the action and actor selectivity in the STP area. There exists only a few models for the motion processing in the dorsal stream, and these models were not be applied to the real-world computer vision tasks. Our model is one that agrees with (or processes) data at different levels: from computer vision algorithm, practical software, to neuroscience.by Hueihan Jhuang.Ph.D

Fiber Bragg Grating Based Sensors and Systems

This book is a collection of papers that originated as a Special Issue, focused on some recent advances related to fiber Bragg grating-based sensors and systems. Conventionally, this book can be divided into three parts: intelligent systems, new types of sensors, and original interrogators. The intelligent systems presented include evaluation of strain transition properties between cast-in FBGs and cast aluminum during uniaxial straining, multi-point strain measurements on a containment vessel, damage detection methods based on long-gauge FBG for highway bridges, evaluation of a coupled sequential approach for rotorcraft landing simulation, wearable hand modules and real-time tracking algorithms for measuring finger joint angles of different hand sizes, and glaze icing detection of 110 kV composite insulators. New types of sensors are reflected in multi-addressed fiber Bragg structures for microwave–photonic sensor systems, its applications in load-sensing wheel hub bearings, and more complex influence in problems of generation of vortex optical beams based on chiral fiber-optic periodic structures. Original interrogators include research in optical designs with curved detectors for FBG interrogation monitors; demonstration of a filterless, multi-point, and temperature-independent FBG dynamical demodulator using pulse-width modulation; and dual wavelength differential detection of FBG sensors with a pulsed DFB laser

A new operability and predictability enhanced riser control system for deepwater marine operation: an integrated riser hybrid tensioning system

This dissertation presents a novel riser hybrid tensioning system by integrating an electrically powered riser tensioning system into existing hydro-pneumatic tensioners. Compared to current passive hydro-pneumatic tensioners, this new riser hybrid tensioning system provides the capability of dynamically controlling the tension in the riser string. This feature opens a wide horizon of different active riser control strategies to achieve the systematic riser control solution. The objective of this study is to increase the predictability and safety of the whole riser system, and to extend the operability of the riser tensioning system into other operations. An overall structure framework of this novel hybrid riser tensioning system is proposed, comprising a direct driven electrical tensioners, hydro-pneumatic tensioners, a super-capacitor based energy storage system, power dissipaters, an overall tension controller and a power management controller. Hardware configurations are suggested. A riser data logging system is introduced, providing more comprehensive riser status data. A power management control strategy and overall coordination architecture to integrate the whole system are proposed. As the main functionality of the riser tensioning system, a new active heave compensation control strategy is analyzed in detail, by using this new riser hybrid tensioning system. A LQG controller and a H [subscript infinity symbol] controller are designed. The position chasing technique produces predictive and accurate tension commands for the electrical tensioners. Both Matlab simulation and hardware implementation confirm the feasibility of this concept, and further verifies that a more accurate control performance could be achieved by the electrical tensioners 180° compensating the tension fluctuation caused by the hydro-pneumatic tensioners. A novel testability and predictability enhanced anti-recoil control algorithm is implemented in the electrical tensioners. A position control strategy is proposed with the objective of moving the riser body to a desired elevation height in a predictive manner. A system model and a Kalman estimator are built, and a LQG controller is designed. The simulation demonstrates that the riser lifting height can adjust to any reasonable value for different test environment. This anti-recoil control concept reduces the risk of catastrophic damage, and allows us to perform maintenance tests much more frequently to bring back operator’s confidence. During harsh sea state, the VIV can be suppressed by using the dynamic control of the hybrid tensioning system, at frequencies and magnitudes made available by the electrical tensioning system. The objective is to achieve the VIV suppression by avoiding the excitation of the oscillation locking into the resonance conditions, and by reducing oscillation energy to be built in riser. A modal analysis of a tensioned Euler-Bernoulli beam is studied. Two control methods are proposed. Simulations results demonstrate that the oscillation is effectively reduced at the dominant lock-in frequency. Finally, this riser hybrid tensioning system opens the possibility to extend the tensioning system operability into other drilling operations. A motion stabilizer supporting the heave compensation of the drill pipes and the DST tools can be eliminated by connecting the drill pipes onto the telescopic joint. Another application would be that the electrical tensioners can run under position control mode after the riser is recoiled and soft hang-off on tensioners. The riser string position with respect to the seabed can still be controlled, during the vessel moving among different well heads.Electrical and Computer Engineerin