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Utilization of distributed energy resources’ flexibility in power system operation – Evaluation of today’s status and description of a future concept

Utilization of distributed energy resources’ flexibility in...

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International Universities Power engineering Conference (UPEC)

作者： Hanne Sæle Andrei Z. Morch Evangelos Rikos Silvia M. Canevese Silvia Maria Michał Kosmecki IEN SINTEF Energi AS Trondheim NO Dept. of Energy Systems SINTEF Energy Research Trondheim Norway Dept. of PVs and DG CRES Athens Greece Energy Sys. Development Dept. RSE S.p.A. Milan Italy System Analysis Department Institute of Power Engineering (IEn) Gdansk Poland

In the future power system the massive amounts of distributed generation, in particular at low-voltage level, will increase the need for distributed monitoring and control, and for improved resource management in the distribution grid. This paper is based on research from two projects: EU (FP7) ELECTRA IRP (2013-2018) and FME CINELDI (2016-2024). ELECTRA proposes a future (2030+) decentralized control architecture (Web-of-Cells) for balance (including frequency) and voltage control, as opposed to the current centralized control approach typical of Transmission system Operators (TSOs). CINELDI, based on today's status, is exploring the needs for, and the possibilities of, exploitation of flexible resources for power system control towards 2030/2040. In cooperation these research projects can give a contribution to achieve future effective coordination among the stakeholders, in particular between TSOs and Distribution system Operators (DSOs).

关键词： Voltage control Time-frequency analysis Frequency control Power system stability Distributed power generation Monitoring

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Wind farm active voltage regulation strategy of transient support improvement

Wind farm active voltage regulation strategy of transient su...

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8th Renewable Power Generation Conference (RPG 2019)

作者： Cui Yang Song Peng Cheng Xuekun Qiao Ying Wang Xiaosheng Liu Jingbo State Grid Jibei Electric Power Co. Ltd. Research Institute North China Electric Power Research Institute Co. Ltd. Xicheng District Beijing China Grid-connected Operation Technology For Wind-Solar-Storage Hybrid System State Grid Corporation Key Laboratory Xicheng District Beijing China State Key Lab of Control and Simulation of Power Systems and Generation Equipment Dept. of Electrical Engineering Tsinghua University Haidian District Beijing China

ISBN: (数字)9781839531248

ISBN: (纸本)9781839531255

The cumulative installed capacity of wind power worldwide has grown rapidly in recent years. Fixed reactive power control is adopted by wind turbines (WTs) to receive cycle instruction of wind farm (WF) automatic voltage control system (AVCS). It does not have active voltage regulation (AVR) capability, which reduces the reliability of power system operation. Firstly, two ways of WTs AVR which QV droop control and Vac control mode are introduced in this paper. On the basis, the problems of reactive power circulation and control points inconsistency during multi-WTs voltage regulation are discussed. The problems are solved by coordination of WTs of WF AVR strategy. WF voltage transient support capability is promoted by the strategy. Effectiveness is verified by simulation case of the proposed method.

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A neural network for predicting unintentional lane departures

A neural network for predicting unintentional lane departure...

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2017 IEEE International Conference on Industrial Technology, ICIT 2017

作者： Ambarak, Jamaa M. Ying, Hao Syed, Fazal Filev, Dimitar Dept. of Electrical and Computer Engineering Wayne State University DetroitMI United States Hybrid Electric Vehicle Control System Ford Motor Company DearbornMI United States

ISBN: (纸本)9781509053209

Unintended lane departure accidents are due to driver's inattention, incapacitation, and drowsiness. Lane departure warning systems have been developed to enhance traffic safety by predicting/detecting driving situation and alerting drivers to avoid or mitigate traffic accidents. This paper explores effectiveness of a three-layer perceptron neural network in predicting an unintentional lane departure, which to the best of our knowledge has not been reported in the literature. This study used driver experiment data generated by VIRTTEX, a hydraulically powered 6-degrees-of-freedom moving base driving simulator at Ford Motor Company. The experimental data represented 16 drowsy drivers who drove a simulated 2000 Volvo S80 (three hours per driver), which consisted of a total of 3,508 lane departure occurrences. Two-third of the lane departures were randomly selected to generate training examples for the network (82,040 examples for a 0.2-second prediction horizon and 171,112 for a 0.5-second horizon). The number of hidden neurons as well as the input vehicle variables were optimized experimentally through the training process. The optimized network was then used to predict lane departure by processing the entire driving time series of the 16 drivers one by one after all the training data was removed from the time series. The network made a prediction at each sampling moment of the time series and there were over 6.3 million predictions. The overall recall and precision of the optimized network for the 0.2-second horizon were 99.74% and 99.66%, respectively, which degraded to 99.23% and 85.49%, respectively, when the horizon increased to 0.5 s. © 2017 IEEE.

关键词： Forecasting

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Performance Evaluation of Lazy and Decision Tree Classifier: A Data Mining Approach for Global Celebrity's Death analysis

Performance Evaluation of Lazy and Decision Tree Classifier:...

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International Conference on Research in Intelligent and Computing in engineering (RICE)

作者： Vivek Kumar Roman Zinovyev Abhishek Verma Prayag Tiwari Dept. of Automated Control System National University of Science & Technology-MiSiS Moscow Russian Federation Dept.of Semiconductor Electronic National University of Science & Technology-MiSiS Moscow Russian Federation Dept.of CSE Malaviya National Institute of Technology Jaipur India Dept.of Information Engineering University of PaPadova Italy

In present world data is a valuable asset. The best utilization of this asset by means of technology gives an upper hand to an organization. Technologies like machine learning, data mining, and artificial intelligence are no exception to this either. Celebrities influence common people behaviors through biological, psychological and social processes to a great extent. Simultaneously there is vast disparity amongst their demise over the cause, region, and age. Therefore, it is a challenging and interesting endorsement to work upon. The objective of this work is to come up with the comprehensive result to understand the celebrity deaths by investigating the incidence happened over the decade. The database for training is created from the public and open access databases for years 2006-2016 comprising of 11, 200 reported deaths over the globe. Findings of the work are year by year extraction of death, the cause behind it, age, gender, and place. Lazy and decision tree classifier model of data mining is being used for the analysis based on the profession as evaluation class.

关键词： Decision trees Entropy Support vector machines Text mining Information retrieval Machine learning

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Tribology property in oil-impregnated porous carbon materials made from rice hull

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International Journal of the Society of Material engineering for Resources 2018年第1期23卷 59-63页

作者： Honma, Kento Masuyama, Tomoya Takahashi, Takeshi Iizuka, Hiroshi Shishido, Michiaki Dept. of Mechanical and Control Engineering National Institute of Technology Tsuruoka College 104 Sawada-Inooka Tsuruoka Yamagata997-8511 Japan Department of Creative Engineering National Institute of Technology Tsuruoka College Japan Sanwa Yushi Co. Ltd Tendo994-0044 Japan Department of Mechanical System Engineering Faculty of Engineering Yamagata University 4-3-16 Jonan Yonezawa Yamagata992-8510 Japan

Rice hull, which is one of the agricultural waste in Japan, has been required for reuse from the viewpoint of environment protection. Rice hull has the porous structure that originates from plants. Rice hull silica carbon (RHSC) material is manufactured by mixing and impregnating the rice hull with a phenol resin, and then carbonizing it in a nitrogen gas atmosphere at high temperatures. RHSC has core competencies such as low friction coefficient and water resistance, and it is expected to be applied to linear guide elements and sliding bearing. Moreover, an improvement in friction property is expected by keeping the lubricating oil in the natural porous structure. In this study, the friction and wear mechanisms of RHSC are discussed from the tribology properties obtained by block-on-ring test and the worn surfaces observed with a laser microscope. © 2018 Society of Materials engineering for Resources of Japan. All rights reserved.

关键词： Carbon

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Higher-order finite element modeling of material degradation due to cutting

Higher-order finite element modeling of material degradation...

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2017 IEEE International Electric Machines and Drives Conference, IEMDC 2017

作者： Sundaria, Ravi Lehikoinen, Antti Hannukainen, Antti Arkkio, Antero Dept. of Electrical Engineering and Automation Aalto University Espoo Finland Dept. of Mathematics and System Analysis Aalto University Espoo Finland

ISBN: (纸本)9781509042814

Numerical modeling of energy efficient electrical machines requires accurate and fast calculation of losses. One such loss component is core losses related to magnetic material degradation due to the cutting of electrical sheets. This paper analyzes the application of higher order finite elements for precise and computationally efficient modeling of these cutting related losses. The accuracy of higher order elements is compared with highly dense first order elements. Finally, a time-harmonic model of an induction machine with presented higher order elements is simulated and effect of cutting on performance parameters has been analyzed. © 2017 IEEE.

关键词： Finite element method

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Development of Constrained Predictive Functional control using Laguerre Function Based Prediction

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IFAC-PapersOnLine 2017年第1期50卷 10705-10710页

作者： Abdullah M. Rossiter J.A. Haber R. Department of Automatic Control and System Engineering University of Sheffield Mappin StreetS1 3JD United Kingdom Dept. of Mech. Engin. International Islamic University Malaysia Institute of Process Engineering and Plant Design Cologne University of Applied Sciences Köln D-50679 Germany

This work presents a novel constraint handling strategy for Predictive Functional control (PFC). First, to improve prediction consistency, the constant input assumption of nominal PFC approaches is replaced with Laguerre based prediction. This substitution improves the effectiveness of using a constrained solution to prevent long-term constraint violations. Secondly, for state constraints, a simpler single regulator approach is proposed instead of switching between regulators, an approach common in the PFC literature. Simulation results verify that the proposed method manages the constraints better than the traditional approach. Moreover, despite all the modifications, the controller formulation and framework remain simple and straightforward which thus are in line with the key ethos of PFC. © 2017

关键词： Constrained PFC Effective Constraint Technique Predictive control

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Synchronized Cell-Balancing Charging of Supercapacitors

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IFAC-PapersOnLine 2017年第1期50卷 3338-3343页

作者： Li H. Peng J. He J. Huang Z. Pan J. School of Information Science and Engineering Central South University Changsha 410087 China Department of Computer Science University of Victoria Victoria V8P5C2 Canada Dept. of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Shanghai 200240 China

As a classical cell balancing solution in low-power supercapacitor applications, the switched resistor circuit is vulnerable to resistance deviation effects with existing cell balancing methods. In this paper, we propose a synchronized cell balancing method for switched resistor circuits based on the consensus theory and a cyber-physical approach, with the aim of synchronizing cell voltages before they are fully charged. It is shown that the proposed cell-balancing algorithm is robust to resistance deviation effects. Extensive simulations are provided to show the effectiveness of the proposed method. © 2017

关键词： Cell balancing Charging Consensus Cyber-physical systems Supercapacitors

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Linking Symptom Inventories using Semantic Textual Similarity

arXiv

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arXiv 2023年

作者： Kennedy, Eamonn Vadlamani, Shashank Lindsey, Hannah M. Peterson, Kelly S. O'Connor, Kristen Dams Murray, Kenton Agarwal, Ronak Amiri, Houshang H. Andersen, Raeda K. Babikian, Talin Baron, David A. Bigler, Erin D. Caeyenberghs, Karen Delano-Wood, Lisa Disner, Seth G. Dobryakova, Ekaterina Eapen, Blessen C. Edelstein, Rachel M. Esopenko, Carrie Genova, Helen M. Geuze, Elbert Goodrich-Hunsaker, Naomi J. Grafman, Jordan Håberg, Asta K. Hodges, Cooper B. Hoskinson, Kristen R. Hovenden, Elizabeth S. Irimia, Andrei Jahanshad, Neda Jha, Ruchira M. Keleher, Finian Kenney, Kimbra Koerte, Inga K. Liebel, Spencer W. Livny, Abigail Løvstad, Marianne Martindale, Sarah L. Max, Jeffrey E. Mayer, Andrew R. Meier, Timothy B. Menefee, Deleene S. Mohamed, Abdalla Z. Mondello, Stefania Monti, Martin M. Morey, Rajendra A. Newcombe, Virginia Newsome, Mary R. Olsen, Alexander Pastorek, Nicholas J. Pugh, Mary Jo Razi, Adeel Resch, Jacob E. Rowland, Jared A. Russell, Kelly Ryan, Nicholas P. Scheibel, Randall S. Schmidt, Adam T. Spitz, Gershon Stephens, Jaclyn A. Tal, Assaf Talbert, Leah D. Tartaglia, Maria Carmela Taylor, Brian A. Thomopoulos, Sophia I. Troyanskaya, Maya Valera, Eve M. van der Horn, Harm Jan Van Horn, John D. Verma, Ragini Wade, Benjamin S.C. Walker, Willian S.C. Ware, Ashley L. Werner, J. Kent Yeates, Keith Owen Zafonte, Ross D. Zeineh, Michael M. Zielinski, Brandon Thompson, Paul M. Hillary, Frank G. Tate, David F. Wilde, Elisabeth A. Dennis, Emily L. Department of Neurology University of Utah School of Medicine Salt Lake CityUT United States George E. Wahlen Veterans Affairs Medical Center Salt Lake CityUT United States Division of Epidemiology University of Utah Salt Lake CityUT United States Office of Analytics and Performance Integration [VHA United States Department of Rehabilitation and Human Performance Icahn School of Medicine at Mount Sinai New YorkNY United States Department of Neurology Icahn School of Medicine at Mount Sinai New YorkNY United States Human Language Technologies Center of Excellence Johns Hopkins University BaltimoreMD United States Neuroscience Research Center Institute of Neuropharmacology Kerman University of Medical Sciences Kerman Iran Department of Radiology and Nuclear Medicine Vrije Universiteit Amsterdam Amsterdam UMC Location VUmc Amsterdam Netherlands Crawford Research Institute Shepherd Center AtlantaGA United States Department of Sociology Georgia State University AtlantaGA United States Department of Psychiatry and Biobehavioral Sciences Semel Institute for Neuroscience and Human Behavior UCLA Los AngelesCA United States UCLA BrainSPORT Program Los AngelesCA United States Center for Behavioral Health and Sport Dept. of Psychiatry Western University of Health Sciences Lebanon OR PomonaCA United States Department of Psychology Neuroscience Center Brigham Young University ProvoUT United States Department of Psychiatry University of Utah Salt Lake CityUT United States Cognitive Neuroscience Unit School of Psychology Deakin University Geelong Australia VA San Diego Healthcare System Center of Stress and Mental Health Department of Psychiatry UC San Diego School of Medicine San DiegoCA United States Department of Psychiatry UC San Diego School of Medicine San DiegoCA United States Minneapolis VA Health Care System MinneapolisMN United States Department of Psychiatry University of Minnesota MinneapolisMN United States Center for Traumatic Brain

An extensive library of symptom inventories has been developed over time to measure clinical symptoms, but this variety has led to several long standing issues. Most notably, results drawn from different settings and studies are not comparable, which limits reproducibility. Here, we present an artificial intelligence (AI) approach using semantic textual similarity (STS) to link symptoms and scores across previously incongruous symptom inventories. We tested the ability of four pre-trained STS models to screen thousands of symptom description pairs for related content - a challenging task typically requiring expert panels. Models were tasked to predict symptom severity across four different inventories for 6,607 participants drawn from 16 international data sources. The STS approach achieved 74.8% accuracy across five tasks, outperforming other models tested. This work suggests that incorporating contextual, semantic information can assist expert decision-making processes, yielding gains for both general and disease-specific clinical assessment. © 2023, CC BY-NC-SA.

关键词： Decision making

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Preserving data-privacy with added noises: Optimal estimation and privacy analysis

arXiv

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arXiv 2017年

作者： He, Jianping Cai, Lin Guan, Xinping Dept. of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai China Dept. of Electrical & Computer Engineering University of Victoria BC Canada

Networked systems often relies on distributed algorithms to achieve a global computation goal with iterative local information exchanges between neighbor nodes. To preserve data privacy, a node may add a random noise to its original data for information exchange at each iteration. Nevertheless, a neighbor node can estimate other’s original data based on the information it received. The estimation accuracy and data privacy can be measured in terms of (ϵ, δ)-data-privacy, defined as the probability of ϵ-accurate estimation (the difference of an estimation and the original data is within ϵ) is no larger than δ (the disclosure probability). How to optimize the estimation and analyze data privacy is a critical and open issue. In this paper, a theoretical framework is developed to investigate how to optimize the estimation of neighbor’s original data using the local information received, named optimal distributed estimation. Then, we study the disclosure probability under the optimal estimation for data privacy analysis. We further apply the developed framework to analyze the data privacy of the privacy-preserving average consensus algorithm and identify the optimal noises for the algorithm. Copyright © 2017, The Authors. All rights reserved.

关键词： Iterative methods

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