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Distribution system state estimation: an overview of recent developments

Frontiers of Information Technology & Electronic engineering 2019年第1期20卷 4-17页

作者： Wang Gang Giannakis Georgios B Chen Jie Sun Jian Department of Electrical and Computer Engineering and Digital Technology Center University of Minnesota USA Minneapolis MN 55455 School of Automation Beijing Institute of Technology Beijing 100081 Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing 100081

In the envisioned smart grid, high penetration of uncertain renewables, unpredictable participation of (industrial) customers, and purposeful manipulation of smart meter readings, all highlight the need for accurate, fast, and robust power system state estimation (PSSE). Nonetheless, most real-time data available in the current and upcoming transmission/distribution systems are nonlinear in power system states (i.e., nodal voltage phasors). Scalable approaches to dealing with PSSE tasks undergo a paradigm shift toward addressing the unique modeling and computational challenges associated with those nonlinear measurements. In this study, we provide a contemporary overview of PSSE and describe the current state of the art in the nonlinear weighted least-squares and least-absolutevalue PSSE. To benchmark the performance of unbiased estimators, the Cramer-Rao lower bound is developed. Accounting for cyber attacks, new corruption models are introduced, and robust PSSE approaches are outlined as well. Finally, distribution system state estimation is discussed along with its current challenges. Simulation tests corroborate the effectiveness of the developed algorithms as well as the practical merits of the theory.

关键词： State estimation Cramer-Rao bound Feasible point pursuit Semidefinite relaxation Proximal linear algorithm Composite optimization Cyber attack Bad data detection

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Identification and modeling of a nonlinear vibrating beam for real-time control and estimation 25

Identification and modeling of a nonlinear vibrating beam fo...

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25th International Congress on Sound and Vibration 2018: Hiroshima Calling, ICSV 2018

作者： Mikuláš, Erik Takács, Gergely Gulan, Martin Abdollahpouri, Mohammad Rohal'-Ilkiv, Boris Institute of Automation Measurement and Applied Informatics Faculty of Mechanical Engineering Slovak University of Technology Bratislava Slovakia Systems and Control Electrical Engineering Chalmers University of Technology Gothenburg Sweden

ISBN: (纸本)9781510868458

The real-time implementation of control and estimation algorithms on microcontrollers with limited memory and computational power requires a model that describes the dynamics of the vibrating system in sufficient detail, yet makes real-time deployment on sampled systems feasible. While extracting a model from finite element analysis is always possible, this approach yields models that are too complex to be evaluated in sample timing that is typical for vibration phenomena. In case of nonlinear vibrations, this is even more critical as state-of-the-art optimal control and estimation algorithms will have to evaluate a non-convex objective function. This paper introduces the modeling and system identification procedure of a nonlinear vibrating beam that results a real-time feasible mathematical model. Position and velocity measurements are made on a slender vibrating beam mounted equipped with a tip mass on a linear excitation stage using non-contact laser Doppler vibrometry. The measurement results are then fitted to two model candidates by using genetic algorithms to identify unknown parameters. Models are verified in simulation and their outputs are compared to experimental measurements. © 25th International Congress on Sound and Vibration 2018, ICSV 2018: Hiroshima Calling. All rights reserved.

关键词： Genetic algorithms

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Multi-channel attention mechanism graph convolutional network considering cumulative effect and temporal causality for day-ahead wind power prediction

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Energy 2025年 332卷

作者： Mao Yang Renxian Jiang Bo Wang Guozhong Fang Yunpeng Jia Fulin Fan Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education (Northeast Electric Power University) Jilin 132012 China State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems China Electric Power Research Institute Beijing 100912 China State Grid Corporation of China Northeast Branch Liaoning 100031 China Grid Jilin Electric Power Co. Ltd. Jilin Power Supply Company of State Jilin 130021 China School of Electrical Engineering and Automation Harbin Institute of Technology Harbin 150001 China Institute for Energy and Environment University of Strathclyde Glasgow G1 1XW UK

Under the current situation where the proportion of wind power generation in the existing energy structure is gradually increasing, accurate short-term power prediction of wind farm cluster (WFC) plays an important auxiliary role in the formulation of regional power generation plans. However, it is difficult to clarify the correlation between wind farms in the power prediction of WFC, which leads to the difficulty of stable and accurate prediction. Therefore, this paper proposes a short-term power prediction method for WFC considering wind power cumulative effect (CE) and temporal causality (TC). Firstly, the two relationships (CE and TC) between wind farms are clarified and used to construct an adjacency matrix separately, then the error characteristics (EC) are used to form an adjacency matrix as well. Secondly, the adjacency matrix information with different attributes is fused by the multi-channel attention mechanism to obtain the wind power prediction results. Finally, the proposed method is applied to three WFCs in China, by which the universality and effectiveness of the method is verified. Compared with the traditional prediction method, its RMSE is reduced by 1.55 %, 1 % and 3.4 % on average.

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A Brief Research and Lookback of the Development of Iris Recognition

A Brief Research and Lookback of the Development of Iris Rec...

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IEEE International Conference on Service Operations and Logistics, and Informatics, SOLI

作者： Xiaoshuang Li Shenhua Hu Chengkan Lv Haojun Qin Fenghua Zhu Feiyue Wang State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Research Center of Precision Sensing and Control Institute of Automation Chinese Academy of Sciences Beijing China School of electrical engineering and aotumation Wuhan University Wuhan China

Personal identification has been used more and more widely in information society. Iris recognition, as one of numerous identification methods, has already been applied in many situations, because the iris patterns have stable, unique and non-invasive features. We analyze the general process of iris recognition in this paper, including image preprocessing, feature extraction, classification and recognition. We also study the progress in iris recognition brought by deep learning method. It is our belief that traditional approaches play a very significant role in iris recognition field, while deep learning methods will make a great difference to iris recognition.

关键词： Iris recognition Feature extraction Iris Image edge detection Wavelet transforms automation

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Process Monitoring System Design via the Closed-Loop Identified Data-Driven SKR

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IFAC-PapersOnLine 2018年第24期51卷 367-372页

作者： Luo, H. Li, K. Song, X. Yin, S. Ding, S.X. Li, L. Yang, X. School of Astronautics Harbin Institute of Technology Harbin150001 China Institute for Automatic Control and Complex Systems University of Duisburg-Essen Duisburg47057 Germany School of Automation and Electrical Engineering University of Science and Technology Beijing Beijing100083 China

This paper presents the research on the closed-loop data-driven design of the process monitoring system. The core of the study is the closed-loop identification of the data-driven stable kernel representation (SKR) of the system. The proposed method takes into account the effects of feedback controller and the noise information in the closed-loop is directly extracted from a single LQ decomposition. The main results and the proposed methods are verified and demonstrated through randomly generated numerical examples. © 2018

关键词： Monitoring

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A Modified Method of an Inverse Neural and Adaptive Correction Factor for Speed control of DC Motor

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Journal of Physics: Conference Series 2020年第1期1530卷

作者： Ali Reyadh Waheed Abbas Hussain Issa Mohammed Y. Hassan M.Sc. Electronics Engineering Department of Electrical Engineering University of Technology Baghdad Iraq PhD. Control and Automation Engineering Department of Electrical Engineering University of Technology Baghdad Iraq Department of Control and Systems Engineering University of Technology Baghdad Iraq

This Article Proposes a modified method of adaptive controlling for the DC motor and it is deriver circuit based on Inverse Neural controller. The proposed controller composed of two parts: the first is the inverse neural control that will control the speed of the direct current motor and, the second is adaptive correction factor that will act as an adaptive compensator to overcome the error (offset) in the steady state response of the motor (eliminate the steady state error). The obtained results prove that the new method successfully controlled the DC motor speed by eliminating the error in the steady state response, and letting the output correctly tracking the input set-point with minimum rising time and minimum peak overshoot. Simulation done using MATLAB SIMULINK. Results compared with the conventional Inverse Neural controller to demonstrate the impact of the proposed method also a load test had been done.

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Statistical Approach to Detection of Attacks for Stochastic Cyber-Physical systems

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IFAC-PapersOnLine 2018年第25期51卷 178-183页

作者： Marelli, Damián Sui, Tianju Fu, Minyue School of Automation Guandong University of Technology China French-Argentinean International Center for Information and Systems Sciences National Scientific and Technical Research Council Argentina Department of Control Science and Engineering Dalian University of Technology China School of Electrical Engineering and Computer Science University of Newcastle Australia

We study the problem of detecting an attack on a stochastic cyber-physical system. We start by proposing a detection criterion based on checking the statistics of the Kalman prediction error. To show the importance of the proposed criterion, we study certain attacking schemes which can be effectively detected by this criterion, but not by checking simpler conditions based on commonly used statistics. We then use the proposed criterion to derive a detection algorithm. This algorithm is based on a statistical confidence test, giving a confidence level for detecting an attack. We present simulation results to illustrate the performance of this algorithm. © 2018

关键词： Computer crime Cyber Physical System Embedded systems Error statistics Linear systems Statistics Stochastic systems Testing Attack detection Detection algorithm Detection of attacks Integrity attacks Statistical approach Statistical confidence Statistical hypothesis testing System security

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ANN based Interwell Connectivity Analysis in Cyber-Physical Petroleum systems

ANN based Interwell Connectivity Analysis in Cyber-Physical ...

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IEEE International Conference on Industrial Informatics (INDIN)

作者： Haibo Cheng Xiaoning Han Peng Zeng Haibin Yu Evgeny Osipov Valeriy Vyatkin Lab. of Networked Control Systems Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Department of Computer Science Electrical and Space Engineering Luleå University of Technology Luleå Sweden

In cyber-physical petroleum systems (CPPS), accurate estimation of interwell connectivity is an important process to know reservoir properties comprehensively, determine water injection rate scientifically, and enhance oil recovery effectively for oil and gas (O&G) field. In this study, an artificial neural network (ANN) based analysis method is proposed to estimate interwell connectivity. The generated neural network is used to define the mapping function between production wells and surrounding injection wells based on the historical water injection and liquid production data. Finally, the proposed method is applied to a synthetic reservoir model. Experimental results show that ANN based approach is an efficient method for analyzing interwell connectivity.

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Blockchain Technology Based Decentralized Energy Trading for Multiple-Microgrid systems

Blockchain Technology Based Decentralized Energy Trading for...

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IEEE Conference on Energy Internet and Energy System Integration (EI2)

作者： Ting Li Wei Zhang Ning Chen Minhui Qian Ying Xu School of Electrical Engineering and Automation Harbin Institute of Technology Harbin China State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems China EPRI Nanjing China Department of Electrical Engineering & Computer Science University of Central Florida Orlando USA

ISBN: (数字)9781728131375

ISBN: (纸本)9781728131382

With the emerging technology for distributed generation and urge of improving quality of service of power supply for energy users, more and more Microgrids (MGs) are integrated into the distributed networks to serve the energy users. These Microgrids are gradually formulating a Multi-Microgrid System (MMGS, Multi-Microgrid System), which will play an important role for the future energy supply. Building a centralized control center not only increases the expense of investment, but also brings the issues of maintaining fairness among energy users. To address these problems, this paper proposes a peer-to-peer method for energy trading of MMGS, based on the idea of decentralized trading. An auction-based trading mechanism suitable for peer-to-peer energy trading is proposed first. For this mechanism, the MGs firstly declare their energy buying bids or selling quotations. Then, the market-clearing price is determined by using a unified weight clearing algorithm in a decentralized manner. By applying the edge technology of Blockchain, the implementation of the proposed peer-to-peer energy trading method, including the architecture, procedures, security check, etc., is also discussed. The proposed Blockchain-based energy trading platform can realize the decentralized and autonomous energy trading of MGs within an MMGS. A case study with an MMGS with 10 MG units is provided to demonstrate the effectiveness of the proposed approach.

关键词： Peer-to-peer computing Microgrids Blockchain Distributed power generation Electronic commerce Power distribution economics Pricing

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A Blockchain-based Educational Digital Assets Management System

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IFAC-PapersOnLine 2020年第5期53卷 47-52页

作者： Junqing Li Mo Lan Ying Tang Shichao Chen Fei-Yue Wang Wei Wei Shandong University of Science and Technology Qingdao China 266590 The State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China 100190 Southwest University Chongqing China 400715 Beijing Achievelearn Education Technology Group Beijing China 100095 Electrical and Computer Engineering Rowan University Glassboro NJ 08003 USA Qingdao Academy of Intelligent Industries Qingdao China 266042 3E Smart Education Beijing China 100083

A variety of heterogeneous information is produced after the application of various emerging technologies in education, which is of great research value as educational assets. The traditional educational asset management system has emerged. In view of the disadvantages of traditional system centralization process, people begin to use decentralized blockchain technology for innovation. This paper proposes an educational digital asset management system architecture based on blockchain 3.0 technology system, which forms various data formed by students in and out of class learning process, courseware and experience data generated by teachers in the process of teaching into educational digital assets, and carries out the right confirmation and storage on the blockchain. The system can use a variety of heterogeneous data in digital assets to analyze the development status of school users, achieve the teaching purpose of teaching students according to their aptitude and different people.

关键词： blockchain blockchain system digital assets educational technology decentralized systems

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