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IEEE International Conference on Real-time Computing and Robotics (RCAR)

作者： Jinghao Zhang Zhe Chen Ning Li Department of Automation Shanghai Jiao Tong University Shanghai P. R. China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai P. R. China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai P. R. China Department of Automation Tsinghua University Beijing P. R. China

Genetic algorithm (GA) is an effective method for path planning problems. As a powerful variant of GA, island genetic algorithm (IGA) has considerable improvement in performance. In this paper, a new island model of GA is proposed to avoid the premature phenomenon and achieve better efficiency. First, a new method of creating subpopulations is presented based on K-means to expand the searching area for the optima. Meanwhile, recombining subpopulations is proposed as a new strategy to improve the diversity of populations and save computational time. Moreover, a method is designed based on Monte Carlo sampling to handle the uncertainty of maps. Comparative experiments are presented to verify the efficiency of the proposed algorithm. Then, a proper number of samples is found by simulation to balance the accuracy and the time cost of Monte Carlo sampling.

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A Novel Fault Elements Location Algorithm Based on Wide Area Fault Recorder Data for HV Transmission system

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IOP Conference Series: Earth and Environmental Science 2018年第1期133卷

作者： Juntao He Renfei Che Xiaocheng Meng Qingmeng Meng Key Laboratory of Power System Intelligent Dispatch and Control School of Electrical Engineering Shandong University Jinan China

After a large-scale grid failure, it is important for dispatchers to know the faulty components and causes and to develop the correct scheduling strategy. In this paper, a new fault diagnosis scheme is presented based on widely configured fault recorders. The proceeded algorithm using the wide-area recorder data to locate the fault components such as transmission lines, busbars and transformers. Different indicators are given for different components on the grid. A variety of criterion indexes are deduced for the transmission line using the distributed parameter model. The credibility of the judgment is improved by using multiple criteria. A search scheme based on the initial adjacency matrix is used to locate fault component on the grid. The fault area is defined according to the uploaded recorder data. The fault components are searched in the wide defined fault area according to the proposed scheme. The element with the greatest probability of failure is found. The three faulty elements simulation models based on PSCAD/EMDTC are established and studied, what's more, the power system model is also established to test the algorithm. The simulation results verify the effectiveness of the proposed method.

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Reactive Power and Voltage Optimization control Strategy in Active Distribution Network Based on the Determination of the Key Nodes

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IOP Conference Series: Materials Science and engineering 2017年第1期199卷

作者： Qingmeng Meng Renfei Che Shi Gao Key Laboratory of Power System Intelligent Dispatch and Control School of Electrical Engineering Shandong University Jinan China

The distributed generation which is integrated in the active distribution network changes power flow, bringing new challenges to the voltage control. When voltage limit violation happens, in order to make the voltage return to normal range and improve the voltage quality, a novel voltage control strategy is proposed. Considering the voltage quality and node importance, the electrical closeness centrality and key node contribution degree are defined, and the key nodes are determined by the orders of the key node contribution degree. This paper uses the reactive power compensation devices which are installed at the key nodes coordinated with the reactive power output of the distributed generation to realize the voltage optimization control. The voltage optimization control model is established by taking the minimum power loss as an objective function. Using the particle swarm optimization algorithm solves the model. The simulation results of the improved IEEE-33 bus system verify the effectiveness of the proposed method.

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A Computationally Efficient Target Localization Algorithm in Underwater Wireless Sensor Networks

A Computationally Efficient Target Localization Algorithm in...

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International Conference on Computers, Communications, and systems (ICCCS)

作者： Xiaojun Mei Huafeng Wu Dezhi Han Xinqiang Chen Jiangfeng Xian Bing Han College of Information Engineering Shanghai Maritime University National Engineering Research Center of Ship & Shipping Control System Shanghai Ship and Shipping Research Institute Co. Ltd Shanghai China Merchant Marine College Shanghai Maritime University Shanghai China Institute of Logistics Science and Engineering Shanghai Maritime University Shanghai China Hubei Key Laboratory of Inland Shipping Technology Wuhan University of Technology Wuhan China

Localization is of paramount importance for underwater wireless sensor networks (UWSNs). However, achieving accurate location is infeasible, especially in the highly dynamic underwater environment. The acoustic signal may suffer hybrid loss, including path and absorption loss, which dramatically degrades the localization accuracy. Even though some localization methods have been proposed, the trade-off between accuracy and computational complexity cannot be well balanced. In this context, the paper proposes a computationally efficient method that investigates the localization problem in the alternating nonnegative constrained least squares (ANCLS) framework after linearization operation. The potential solutions are divided into two groups, wherein the optimal one is filtered under the constraint by exchanging the variables from one to another. A block principal pivoting-based localization (BPPL) method is then presented to estimate the target's location. Simulations reveal that the computational complexity and the localization accuracy of BPPL are competitive compared with the state-of-the-art methods in different scenarios.

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Photovoltaic plant operating statuses identification model based on support vector machine using loss quantity of electricity feature parameters

Photovoltaic plant operating statuses identification model b...

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International Conference on Renewable Power Generation (RPG 2015)

作者： Kangping Li Fei Wang Zhao Zhen Yujing Sun Zengqiang Mi Hongbin Sun Chun Liu Bo Wang Jing Lu State Key Laboratory of Alternate Electrical Power System With Renewable Energy Sources (North China Electric Power University) Baoding 071003 Hebei Province China State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment (Department of Electrical Engineering Tsinghua University) Haidian District Beijing 100084 China China Electric Power Research Institute Haidian District Beijing 100192 China)

ISBN: (纸本)9781510821415

Operating Statuses Identification (OSI) can help operators to find fault timely and minimize the loss. So it is of great significance for optimal operation of photovoltaic (PV) plants. The loss quantity of electricity (LQOE) is defined as that should have been generated but actually not, which is caused by inverter fault, PV modules fault, dust stratification or combinations of them. Firstly, mathematical models of PV cells are proposed to figure out the LQOE of each PV module. Secondly, after analysing the relation between LQOE and operating statuses, an index set of LQOE describing the distinction of different operating statuses are defined including four statistical feature parameters and a user-defined index. Thirdly, Support Vector Classification models for OSI (OSI-SVC) are built with input features extracted from the index set. Lastly, simulations are carried out to verify the effectiveness and evaluate the performance of the OSI-SVC models. The results indicated that the operating statuses can be effectively recognized by the proposed model.

关键词： Feature Extraction Loss quantity of electricity Operating Statuses Identification Support Vector Machine

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Enhanced Precipitation Responses Over the Tibetan Plateau Following Future Tambora-Size Volcanic Eruption

SSRN

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SSRN 2024年

作者： Gan, Xin-Jun Yang, Lin-Shan Zuo, Meng Liu, Fei Gao, Chao-Chao College of Environmental and Resource Science Zhejiang University Hangzhou310058 China Zhejiang Provincial Key Laboratory of Organic Pollution Process and Control Hangzhou310058 China State Key Laboratory of Severe Weather Institute of Tibetan Plateau Meteorology Chinese Academy of Meteorological Sciences Beijing100081 China School of Atmospheric Sciences Sun Yat-Sen University Key Laboratory of Tropical Atmosphere-Ocean System Ministry of Education Southern Marine Science and Engineering Guangdong Laboratory Zhuhai519082 China

Summer precipitation over the Tibetan Plateau (TP) sustains the "Water tower of Asia" and has notable influences on the climate and subsequently eco-environment of the Northern Hemisphere. Due to its high elevation and complex topography, hydroclimate in TP is found to be highly sensitive to anthropogenic warming, and a recent study shows volcanism during the past millennium caused substantial rainfall reduction over southern TP. How would a future eruption affect TP precipitation under an anthropogenic warming climate, however, remains largely untackled. Here we show, based on the Community Earth system Model ensemble simulations under the preindustrial and RCP8.5 scenarios, that a Tambora-size volcanic perturbation leads to severe rainfall reduction over south TP in the following summer (June - August). Evaporation response contributes a minor and relatively constent share of precipitation reduction following the Clausius-Clapeyron scaling, whereas dynamic processes play the essential role by triggering an El Niño-like response in eastern equatorial Pacific, which suppresses Walker and Hadley circulation and contributes to the drying anomalies in south TP. Global Warming renders the hydroclimatic responses 30% more severe, due to the increased climatological moisture content and intensified El Niño response which enhancing hydroclimate sensitivity and attenuating the monsoon circulation. Our results demonstrate the high climate sensitivity of TP and the importance of climate internal modes and feedbacks in modulating the system responses to external forcing. © 2024, The Authors. All rights reserved.

关键词： Rain

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Rapid Response and Recovery Performance of NO2 Gas Sensor Based on Gan Hexagonal Pits at Room Temperature

SSRN

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SSRN 2022年

作者： Han, Xiaomei Han, Dan Liu, Xiaoru Chen, Yi Liu, Lulu Liu, Zhihua Li, Donghui Sang, Shengbo Shanxi Key Laboratory of Micro Nano Sensors & Artificial Intelligence Perception College of Information and Computer Taiyuan University of Technology Taiyuan030024 China Key Lab of Advanced Transducers and Intelligent Control System The Ministry of Education Taiyuan University of Technology Taiyuan030024 China Key Laboratory of Interface Science and Engineering in Advanced Materials Taiyuan University of Technology Ministry of Education Taiyuan030024 China

Although fantastic milestones of Gallium nitride (GaN)-based materials in optoelectronic devices had been reached, the focus on the optimization of their geometrical structure for gas-sensing applications was relatively scarce. In this work, we demonstrated NO2 gas sensor based on p-type GaN hexagonal pits (GaN-HP) with high surface-to-volume ratio by wet etching method. The fabricated NO2 gas sensor had high sensitivity, high selectivity, fast response/recovery times. The response of p-type GaN-HP with etching time for 10 min to 2 ppm NO2 gas was 6.2%, which also have quick response and recovery time at room temperature. UV light drastically enhanced the response of p-type GaN-HP sensor by 1.3 times to 100 ppm NO2 . The gas sensing mechanism of p-type GaN-HP gas sensor was explored, which provided a theoretical and experimental basis for further research and development of high-performance gas sensors based on GaN material. © 2022, The Authors. All rights reserved.

关键词： Gallium nitride

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Distributed Prescribed-Time Convex Optimization: Cascade Design and Time-Varying Gain Approach

arXiv

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arXiv 2024年

作者： Zuo, Gewei Zhu, Lijun Wang, Yujuan Chen, Zhiyong School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430072 China Key Laboratory of Imaging Processing and Intelligence Control Huazhong University of Science and Technology Wuhan430074 China The State Key Laboratory of Power Transmission Equipment & System Security and New Technology School of Automation Chongqing University Chongqing400044 China School of Engineering The University of Newcastle CallaghanNSW2308 Australia

In this paper, we address the distributed prescribed-time convex optimization (DPTCO) problem for a class of high-order nonlinear multi-agent systems (MASs) under undirected connected graphs. A cascade design framework is proposed, dividing the DPTCO implementation into two parts: distributed optimal trajectory generator design and local reference trajectory tracking controller design. The DPTCO problem is then transformed into the prescribed-time stabilization problem of a cascaded system. Changing Lyapunov function and time-varying state transformation methods together with the sufficient conditions are proposed to prove the prescribed-time stabilization of the cascaded system as well as the uniform boundedness of internal signals in the closed-loop MASs. The proposed framework is then utilized to solve robust DPTCO problem for a class of chain-integrator MASs with external disturbances by constructing a novel sliding-mode variables and exploiting the property of time-varying gains. The proposed framework is further utilized to solve the adaptive DPTCO problem for a class of strict-feedback MASs with parameter uncertainty, in which backstepping method with prescribed-time dynamic filter is adopted. The descending power state transformation is introduced to compensate the growth of increasing rate induced by the derivative of time-varying gains in recursive steps and the high-order derivative of local reference trajectory is not required. Finally, theoretical results are verified by two numerical examples. Copyright © 2024, The Authors. All rights reserved.

关键词： Stabilization

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Fast Adaptive Auto-Reclosing Strategy of Mmc-Hvdc Transmission Line Based on Half-Bridge Pathway Injection Signal

SSRN

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SSRN 2022年

作者： Deng, Xiangli Wang, Peng Liao, Yuelin Zhao, Jinbin Liu, Shiming School of Electric Engineering Shanghai University of Electric Power Yangpu District Shanghai 200090 China State Grid Wenzhou Power Supply Company Zhejiang Province Wenzhou325000 China Key Laboratory of Power System Intelligent Dispatch and Control Shandong University Ministry of Education Ji’nan Shandong Province 250061 China

The probability of instantaneous grounding fault during overhead line transmission is high, and it is necessary to configure an efficient restart plan to restore the system. The traditional reclosing strategy is easy to cause secondary overcurrent shock when the permanent fault is reclosed. The conventional scheme based on active injection signal for fault identification during the reclosing period only considers single-pole identification and will affect the normal operation of the power grid. Aiming at the above problems, a fault identification method based on half-bridge modular multilevel converter (MMC) injection signal is proposed. The proposed method completes the identification of multiple types of faults during reclosing without affecting the normal operation of the sound pole line by adding a control strategy to the valve controller to cooperate with the dc circuit breaker to actively inject characteristic signals. The method has no special requirements for the topology of the MMC sub-module, improves the detection accuracy of the transition resistance, quickly identifies the fault, and has little impact on the power grid operation. The four-terminal MMC-HVDC simulation model is built on PSCAD/EMTDC, and the simulation results verify the effectiveness of the proposed method. © 2022, The Authors. All rights reserved.

关键词： Poles

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Memory-Based Contrastive Learning with Optimized Sampling for Incremental Few-Shot Semantic Segmentation

Memory-Based Contrastive Learning with Optimized Sampling fo...

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IEEE International Symposium on Circuits and systems (ISCAS)

作者： Yuxuan Zhang Miaojing Shi Taiyi Su Hanli Wang Department of Computer Science & Technology Tongji University Shanghai P. R. China Key Laboratory of Embedded System & Service Computing Ministry of Education Tongji University Shanghai P. R. China Department of Control Science & Engineering Tongji University Shanghai P. R. China

ISBN: (数字)9798350330991

ISBN: (纸本)9798350331004

Incremental few-shot semantic segmentation (IFSS) aims to incrementally expand a semantic segmentation model’s ability to identify new classes based on few samples. However, it grapples with the dual challenges of catastrophic forgetting (due to feature drift in old classes) and overfitting (triggered by inadequate samples in new classes). To address these issues, a novel approach is proposed to integrate pixel-wise and region-wise contrastive learning, complemented by an optimized example and anchor sampling strategy. The proposed method incorporates a region memory and pixel memory designed to explore the high-dimensional embedding space more effectively. The memory, retaining the feature embeddings of known classes, facilitates the calibration and alignment of seen class features during the learning process of new classes. To further mitigate overfitting, the proposed approach implements an optimized example and anchor sampling strategy. Extensive experiments show the competitive performance of the proposed method. The source code of this work can be found in https://***.

关键词： Circuits and systems Semantic segmentation Source coding Semantics Calibration

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