347 research outputs found
Power Converter of Electric Machines, Renewable Energy Systems, and Transportation
Power converters and electric machines represent essential components in all fields of electrical engineering. In fact, we are heading towards a future where energy will be more and more electrical: electrical vehicles, electrical motors, renewables, storage systems are now widespread. The ongoing energy transition poses new challenges for interfacing and integrating different power systems. The constraints of space, weight, reliability, performance, and autonomy for the electric system have increased the attention of scientific research in order to find more and more appropriate technological solutions. In this context, power converters and electric machines assume a key role in enabling higher performance of electrical power conversion. Consequently, the design and control of power converters and electric machines shall be developed accordingly to the requirements of the specific application, thus leading to more specialized solutions, with the aim of enhancing the reliability, fault tolerance, and flexibility of the next generation power systems
Alternative Sources of Energy Modeling, Automation, Optimal Planning and Operation
An economic development model analyzes the adoption of alternative strategy capable of leveraging the economy, based essentially on RES. The combination of wind turbine, PV installation with new technology battery energy storage, DSM network and RES forecasting algorithms maximizes RES integration in isolated islands. An innovative model of power system (PS) imbalances is presented, which aims to capture various features of the stochastic behavior of imbalances and to reduce in average reserve requirements and PS risk. Deep learning techniques for medium-term wind speed and solar irradiance forecasting are presented, using for first time a specific cloud index. Scalability-replicability of the FLEXITRANSTORE technology innovations integrates hardware-software solutions in all areas of the transmission system and the wholesale markets, promoting increased RES. A deep learning and GIS approach are combined for the optimal positioning of wave energy converters. An innovative methodology to hybridize battery-based energy storage using supercapacitors for smoother power profile, a new control scheme and battery degradation mechanism and their economic viability are presented. An innovative module-level photovoltaic (PV) architecture in parallel configuration is introduced maximizing power extraction under partial shading. A new method for detecting demagnetization faults in axial flux permanent magnet synchronous wind generators is presented. The stochastic operating temperature (OT) optimization integrated with Markov Chain simulation ascertains a more accurate OT for guiding the coal gasification practice
Recognizing Frustration of Drivers From Face Video Recordings and Brain Activation Measurements With Functional Near-Infrared Spectroscopy
Experiencing frustration while driving can harm cognitive processing, result in aggressive behavior and hence negatively influence driving performance and traffic safety. Being able to automatically detect frustration would allow adaptive driver assistance and automation systems to adequately react to a driver’s frustration and mitigate potential negative consequences. To identify reliable and valid indicators of driver’s frustration, we conducted two driving simulator experiments. In the first experiment, we aimed to reveal facial expressions that indicate frustration in continuous video recordings of the driver’s face taken while driving highly realistic simulator scenarios in which frustrated or non-frustrated emotional states were experienced. An automated analysis of facial expressions combined with multivariate logistic regression classification revealed that frustrated time intervals can be discriminated from non-frustrated ones with accuracy of 62.0% (mean over 30 participants). A further analysis of the facial expressions revealed that frustrated drivers tend to activate muscles in the mouth region (chin raiser, lip pucker, lip pressor). In the second experiment, we measured cortical activation with almost whole-head functional near-infrared spectroscopy (fNIRS) while participants experienced frustrating and non-frustrating driving simulator scenarios. Multivariate logistic regression applied to the fNIRS measurements allowed us to discriminate between frustrated and non-frustrated driving intervals with higher accuracy of 78.1% (mean over 12 participants). Frustrated driving intervals were indicated by increased activation in the inferior frontal, putative premotor and occipito-temporal cortices. Our results show that facial and cortical markers of frustration can be informative for time resolved driver state identification in complex realistic driving situations. The markers derived here can potentially be used as an input for future adaptive driver assistance and automation systems that detect driver frustration and adaptively react to mitigate it
RSME 2011. Transfer and Industrial Mathematics. Proceedings of the RSME Conference on Transfer and Industrial Mathematics. Santiago de Compostela, July 12-14, 2011
[EN] The RSME Conference on Transfer and Industrial Mathematics is supported by the
Royal Spanish Mathematical Society, a scientific society for the promotion of mathematics
and its applications as well as the encouragement of research and teaching
at all educational levels. The three-day conference presents successful experiences
in the field of mathematical knowledge transfer to industry and focuses
on the following issues:
— Showing how collaboration with industry has opened up new lines of
research in the field of mathematics providing high quality contributions to
international journals and encouraging the development of doctoral theses.
— How the promotion of existing infrastructures has contributed to enhance
the transfer of mathematical knowledge to industry.
— The presentation of postgraduate programs offering training in mathematics
with industrial applications.
The conference includes talks from researchers and industry representatives who
present their different points of view and experiences with regards to the transfer
of mathematical knowledge to industry
Assessment of Renewable Energy Resources with Remote Sensing
The development of renewable energy sources plays a fundamental role in the transition towards a low carbon economy. Considering that renewable energy resources have an intrinsic relationship with meteorological conditions and climate patterns, methodologies based on the remote sensing of the atmosphere are fundamental sources of information to support the energy sector in planning and operation procedures. This Special Issue is intended to provide a highly recognized international forum to present recent advances in remote sensing to data acquisition required by the energy sector. After a review, a total of eleven papers were accepted for publication. The contributions focus on solar, wind, and geothermal energy resource. This editorial presents a brief overview of each contribution.About the Editor .............................................. vii
Fernando Ramos Martins
Editorial for the Special Issue: Assessment of Renewable Energy Resources with
Remote Sensing
Reprinted from: Remote Sens. 2020, 12, 3748, doi:10.3390/rs12223748 ................. 1
André R. Gonçalves, Arcilan T. Assireu, Fernando R. Martins, Madeleine S. G. Casagrande, Enrique V. Mattos, Rodrigo S. Costa, Robson B. Passos, Silvia V. Pereira, Marcelo P. Pes, Francisco J. L. Lima and Enio B. Pereira
Enhancement of Cloudless Skies Frequency over a Large Tropical Reservoir in Brazil
Reprinted from: Remote Sens. 2020, 12, 2793, doi:10.3390/rs12172793 ................. 7
Anders V. Lindfors, Axel Hertsberg, Aku Riihelä, Thomas Carlund, Jörg Trentmann and Richard Müller
On the Land-Sea Contrast in the Surface Solar Radiation (SSR) in the Baltic Region
Reprinted from: Remote Sens. 2020, 12, 3509, doi:10.3390/rs12213509 ................. 33
JoaquĂn Alonso-Montesinos
Real-Time Automatic Cloud Detection Using a Low-Cost Sky Camera
Reprinted from: Remote Sens. 2020, 12, 1382, doi:10.3390/rs12091382 ................. 43
Román MondragĂłn, JoaquĂn Alonso-Montesinos, David Riveros-Rosas, Mauro ValdĂ©s, HĂ©ctor EstĂ©vez, Adriana E. González-Cabrera and Wolfgang Stremme
Attenuation Factor Estimation of Direct Normal Irradiance Combining Sky Camera Images and Mathematical Models in an Inter-Tropical Area
Reprinted from: Remote Sens. 2020, 12, 1212, doi:10.3390/rs12071212 ................. 61
Jinwoong Park, Jihoon Moon, Seungmin Jung and Eenjun Hwang
Multistep-Ahead Solar Radiation Forecasting Scheme Based on the Light Gradient Boosting Machine: A Case Study of Jeju Island
Reprinted from: Remote Sens. 2020, 12, 2271, doi:10.3390/rs12142271 ................. 79
Guojiang Xiong, Jing Zhang, Dongyuan Shi, Lin Zhu, Xufeng Yuan and Gang Yao
Modified Search Strategies Assisted Crossover Whale Optimization Algorithm with Selection Operator for Parameter Extraction of Solar Photovoltaic Models
Reprinted from: Remote Sens. 2019, 11, 2795, doi:10.3390/rs11232795 ................. 101
Alexandra I. Khalyasmaa, Stanislav A. Eroshenko, Valeriy A. Tashchilin, Hariprakash Ramachandran, Teja Piepur Chakravarthi and Denis N. Butusov
Industry Experience of Developing Day-Ahead Photovoltaic Plant Forecasting System Based on Machine Learning
Reprinted from: Remote Sens. 2020, 12, 3420, doi:10.3390/rs12203420 ................. 125
Ian R. Young, Ebru Kirezci and Agustinus Ribal
The Global Wind Resource Observed by Scatterometer
Reprinted from: Remote Sens. 2020, 12, 2920, doi:10.3390/rs12182920 ................. 147
Susumu Shimada, Jay Prakash Goit, Teruo Ohsawa, Tetsuya Kogaki and Satoshi Nakamura
Coastal Wind Measurements Using a Single Scanning LiDAR
Reprinted from: Remote Sens. 2020, 12, 1347, doi:10.3390/rs12081347 ................. 165
Cristina Sáez Blázquez, Pedro Carrasco GarcĂa, Ignacio MartĂn Nieto, MiguelAngel ´ MatĂ©-González, Arturo Farfán MartĂn and Diego González-Aguilera
Characterizing Geological Heterogeneities for Geothermal Purposes through Combined Geophysical Prospecting Methods
Reprinted from: Remote Sens. 2020, 12, 1948, doi:10.3390/rs12121948 ................. 189
Miktha Farid Alkadri, Francesco De Luca, Michela Turrin and Sevil Sariyildiz
A Computational Workflow for Generating A Voxel-Based Design Approach Based on Subtractive Shading Envelopes and Attribute Information of Point Cloud Data
Reprinted from: Remote Sens. 2020, 12, 2561, doi:10.3390/rs12162561 ................. 207Instituto do Ma
Computational intelligence approaches to robotics, automation, and control [Volume guest editors]
No abstract available
ProducciĂł cientĂfica de l'ETSEIB a Futur. Articles publicats per investigadors de l'ETSEIB l'any 2017
Postprint (author's final draft
Advanced Operation and Maintenance in Solar Plants, Wind Farms and Microgrids
This reprint presents advances in operation and maintenance in solar plants, wind farms and microgrids. This compendium of scientific articles will help clarify the current advances in this subject, so it is expected that it will please the reader
Energy: A continuing bibliography with indexes, issue 15
This bibliography lists 1112 reports, articles, and other documents introduced into the NASA scientific and technical information system from July 1, 1977 through September 30, 1977
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