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Hexagonally ordered microbowl arrays decorated with ultrathin CuInS_(2) nanosheets for enhanced photoelectrochemical performance

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Journal of Energy Chemistry 2020年第12期29卷 134-142页

作者： Ming Li Le Chen Yanjie Su Huan Yin Kexiang Hu State Key Laboratory of Transducer Technology Shanghai Institute of Microsystem and Information TechnologyChinese Academy of SciencesShanghai 200050China School of Electronic Engineering and Automation Guilin University of Electronic TechnologyKey Laboratory of Optoelectronic Information Processing of Guangxi Colleges and Uniy/ersitiesGuilin 541004GuangxiChina Key Laboratory for Thin Film and Microfabrication of the Ministry of Education Department of Micro/Nano ElectronicsSchool of ElectronicsInformation and Electrical EngineeringShanghai Jiao Tong UniversityShanghai 200240China National and Local Joint Engineering Laboratory of Internet Technology on Mine School of Information and Control EngineeringChina University of Mining and TechnologyXuzhou 221008JiangsuChina School of Physics and Telecommunication Engineering Guangxi Colleges and Universities Key Lab of Complex System Optimization and Big Data ProcessingYulin Normal UniversityYulin 537400GuangxiChina

This paper demonstrates the design and fabrication of three-dimensional(3 D) hexagonally ordered microbowl arrays(MBAs) decorated with Cu In S2 nanosheets for enhanced photoelectrochemical(PEC) performance. The 3 D MBAs are fabricated by a micro-fabrication technique. The ultrathin CuInS2 nanosheets are grown on the 3 D electrodes by solvothermal transformation of Cu film. The photocurrent density of 3 D photocathode(CuInS2@MBAs) is about two times higher than that of the planar counterpart(CuInS2@Planar). The improved PEC performance can be ascribed to the elevated light trapping ability and the increased surface area for loading photocatalysts. In addition, CdS quantum dots as cocatalysts are modified onto the Cu In S2 nanosheets to further enhance the PEC activity because the formed p-n heterojunction can accelerate the separation of photogenerated carriers. As a result, the 3 D photocathode of CuInS2/CdS@MBAs shows an optimal incident photon to current efficiency of 10% at the wavelength of400 nm. It is believed that this work can be generalized to design other hierarchical 3 D photoelectrodes for improved solar water splitting.

关键词： Microbowl array CuInS_(2) Nanosheet Photocathode Photoelectrochemical performance

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control STRATEGY FOR SUPPRESSING SUBMODULE CAPACITOR VOLTAGE FLUCTUATION IN CASCADED H-BRIDGE SOLIDSTATE TRANSFORMER

CONTROL STRATEGY FOR SUPPRESSING SUBMODULE CAPACITOR VOLTAGE...

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2021 Annual Meeting of CSEE Study Committee of HVDC and Power Electronics, HVDC 2021

作者： Liu, Linzhao Zhao, Le Zhang, Jianwen Xi, Dongmin Zhou, Jianqiao Zhang, Jiajie Feng, Xin Chen, Hongyu Zhang, Aozhe Wang, Zhida Tian, Chaohui Department of Electrical Engineering Inner Mongolia University of Technology Aimin St. 49 Hohhot China The Key Laboratory of Control of Power Transmission and Conversion of Ministry of Education Department of Electrical Engineering School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University No.800 Dongchuan Rd. Shanghai China Simon Fraser University Mechatronic Systems Engineering 250-13450 102 Ave Surrey Canada School of Information Sciences and Technology Donghua University No.2999 People North Rd. Shanghai China

ISBN: (纸本)9781839537035

Nowadays, with the vigorous development of smart grids, cascaded H-bridge solid-state transformers (CHB-SST) used in distribution network systems have gradually become an important research hotspot. The multiport CHB-SST serves as the interfacing device to interconnect different grids, which has the functions of bidirectional, power flow control, reactive power compensation, and voltage regulation. However, the power fluctuation of the power cells should be constrained by the large capacitors which in turn worsens the system power density. The second order current in the DC-link side of the CHB-SST will cause the fluctuation of the submodule (SM) capacitor voltage, affecting the capacitance value selection. Therefore, this paper proposes a method to suppress the SM capacitor voltage fluctuation of CHB-SST through fluctuating power control strategy. The control scheme passes the second order current component of the SM capacitor to the low-voltage side of the CHB-SST to reduce the voltage fluctuation of the SM capacitor, such that the capacitance can be optimized. The proposed method is verified via the MATLAB/Simulink model, proving that the fluctuation of the SM capacitor voltage can be effectively suppressed. © 2021 IET Conference Proceedings. All rights reserved.

关键词： Energy transfer

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Abstraction-Based Verification of Approximate Pre-Opacity for control systems

arXiv

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arXiv 2022年

作者： Hou, Junyao Liu, Siyuan Yin, Xiang Zamani, Majid Department of Automation Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University China Department of Electrical and Computer Engineering Technical University of Munich Germany Department of Computer Science LMU Munich Germany Department of Computer Science University of Colorado Boulder United States

In this paper, we consider the problem of verifying pre-opacity for discrete-time control systems. Preopacity is an important information-flow security property that secures the intention of a system to execute some secret behaviors in the future. Existing works on pre-opacity only consider non-metric discrete systems, where it is assumed that intruders can distinguish different output behaviors precisely. However, for continuous-space control systems whose output sets are equipped with metrics (which is the case for most real-world applications), it is too restrictive to assume precise measurements from outside observers. In this paper, we first introduce a concept of approximate pre-opacity by capturing the security level of control systems with respect to the measurement precision of the intruder. Based on this new notion of pre-opacity, we propose a verification approach for continuous-space control systems by leveraging abstraction-based techniques. In particular, a new concept of approximate pre-opacity preserving simulation relation is introduced to characterize the distance between two systems in terms of preserving pre-opacity. This new system relation allows us to verify pre-opacity of complex continuous-space control systems using their finite abstractions. We also present a method to construct pre-opacity preserving finite abstractions for a class of discrete-time control systems under certain stability assumptions. Copyright © 2022, The Authors. All rights reserved.

关键词： Opacity

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A GM-TCN based Hybrid Prediction Method for Ash Fouling Prediction in Coal-fired Power Plant Boiler

A GM-TCN based Hybrid Prediction Method for Ash Fouling Pred...

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Chinese Automation Congress (CAC)

作者： Yuanhao Shi Tianxiang Han Fangshu Cui Jie Wen Gangzhu Qiao School of Electrical and Control Engineering North University of China Taiyuan China Department of Automation Ministry of Education of China Shanghai Jiao Tong University and Key Laboratory of System Control and Information Processing Shanghai China School of Data Science and Technology North University of China Taiyuan China

In response to the problem that ash deposition in boilers has a great impact on production efficiency as well as production safety, a grey level theory prediction model based on time convolution networks (GM-TCN) is proposed to predict the degree of ash in boiler heated areas by using a cleaning factor to assess the ash deposition condition on the heated surfaces. The accuracy of the prediction model is improved by utilizing the features of grey level theory that can predict the developmental changes in system behavior, combined with the high-precision approximation capability of the time-convolutional network. The modelling prediction of the ash level in the heated area of boilers during the production of coal-fired power stations is investigated. Experiments demonstrate that the model can predict the cleanliness factor with high accuracy, and the predicted values are closest to the true values compared to the other two models, verifying the accuracy and reliability of the model.

关键词： Cogeneration Time series analysis Ash Production Predictive models Boilers Data models

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A Novel Engine and Battery Coupled Thermal Management Strategy for Connected Hevs Based on Switched Model Predictive control Under Low Temperature

SSRN

引用

SSRN 2022年

作者： Li, Kai Chen, Hong Hou, Shengyan Eriksson, Lars Gao, Jinwu State Key Laboratory of Automotive Simulation and Control Jilin University Changchun131022 China Department of Control Science and Engineering Jilin University Changchun131022 China School of Electronics and Information Engineering Tongji University Shanghai201804 China Department of Electrical Engineering Vehicular Systems Linkping University SE-581 83 Sweden

Under a low-temperature environment, electric vehicles face serious environmental adaptability problems, and efficient vehicle thermal management strategies are urgently needed. This paper presents a novel engine-battery coupled thermal management strategy for connected hybrid electric vehicles (HEVs). An improved system structure for an engine-battery coupled thermal management system (engine-battery CTMS) is designed to avoid unnecessary heat loss. The control requirements of the engine-battery CTMS include minimum engine fuel consumption, minimum power battery ageing damage and minimum system energy consumption, which constitutes a multi-objective optimal control problem in a finite time domain. Based on model predictive control (MPC) theory, a switched nonlinear MPC (NMPC) control strategy is proposed to solve the optimal control problem of the complex coupled multi-input multi-output system. To verify the effectiveness of the proposed strategy, a comparative experiment of the original system structure of the engine-battery CTMS combined with a centralized NMPC control strategy is designed. The results of the cosimulation experiment between MATLAB/Simulink and AMEsim under various driving cycles and different ambient temperatures show that the improved structure and switched control strategy confer great advantages in reducing the controller computation burden, engine fuel consumption, and power battery ageing damage. © 2022, The Authors. All rights reserved.

关键词： Model predictive control

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Green Routing Game: Strategic Logistical Planning using Mixed Fleets of ICEVs and EVs

arXiv

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arXiv 2022年

作者： Sasahara, Hampei Dán, György Amin, Saurabh Sandberg, Henrik The Department of Systems and Control Engineering School of Engineering Tokyo Institute of Technology Tokyo152-8552 Japan The Division of Network and Systems Engineering School of Electrical Engineering and Computer Science Kth Royal Institute of Technology StockholmSE-100 44 Sweden The Laboratory for Information and Decision Systems Massachusetts Institute of Technology CambridgeMA02139 United States The Division of Decision and Control Systems School of Electrical Engineering and Computer Science Kth Royal Institute of Technology StockholmSE-100 44 Sweden

This paper introduces a "green" routing game between multiple logistic operators (players), each owning a mixed fleet of internal combustion engine vehicle (ICEV) and electric vehicle (EV) trucks. Each player faces the cost of delayed delivery (due to charging requirements of EVs) and a pollution cost levied on the ICEVs. This cost structure models: 1) limited battery capacity of EVs and their charging requirement;2) shared nature of charging facilities;3) pollution cost levied by regulatory agency on the use of ICEVs. We characterize Nash equilibria of this game and derive a condition for its uniqueness. We also use the gradient projection method to compute this equilibrium in a distributed manner. Our equilibrium analysis is useful to analyze the trade-off faced by players in incurring higher delay due to congestion at charging locations when the share of EVs increases versus a higher pollution cost when the share of ICEVs increases. A numerical example suggests that to increase marginal pollution cost can dramatically reduce inefficiency of equilibria. © 2022, CC BY-NC-ND.

关键词： Economic and social effects

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Structural Robustness of Complex Networks: A Survey of A Posteriori Measures

arXiv

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arXiv 2023年

作者： Lou, Yang Wang, Lin Chen, Guanrong The Graduate School of Information Science and Technology Osaka University Osaka Suita565-0871 Japan The Department of Computer Science National Yang Ming Chiao Tung University Hsinchu300 Taiwan The Department of Automation Shanghai Jiao Tong University Shanghai200240 China The Key Laboratory of System Control and Information Processing Ministry of Education Shanghai200240 China The Department of Electrical Engineering City University of Hong Kong Hong Kong

Network robustness is critical for various industrial and social networks against malicious attacks, which has various meanings in different research contexts and here it refers to the ability of a network to sustain its functionality when a fraction of the network fail to work due to attacks. The rapid development of complex networks research indicates special interest and great concern about the network robustness, which is essential for further analyzing and optimizing network structures towards engineering applications. This comprehensive survey distills the important findings and developments of network robustness research, focusing on the a posteriori structural robustness measures for single-layer static networks. Specifically, the a posteriori robustness measures are reviewed from four perspectives: 1) network functionality, including connectivity, controllability and communication ability, as well as their extensions;2) malicious attacks, including conventional and computation-based attack strategies;3) robustness estimation methods using either analytical approximation or machine learning-based prediction;4) network robustness optimization. Based on the existing measures, a practical threshold of network destruction is introduced, with the suggestion that network robustness should be measured only before reaching the threshold of destruction. Then, a posteriori and a priori measures are compared experimentally, revealing the advantages of the a posteriori measures. Finally, prospective research directions with respect to a posteriori robustness measures are recommended. © 2023, CC BY.

关键词： Complex networks

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Asynchronous Decentralized Federated Learning for Collaborative Fault Diagnosis of PV Stations

arXiv

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arXiv 2022年

作者： Liu, Qi Yang, Bo Wang, Zhaojian Zhu, Dafeng Wang, Xinyi Ma, Kai Guan, Xinping The Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China School of Electrical Engineering Yanshan University Qinhuangdao066004 China

Due to the different losses caused by various photovoltaic (PV) array faults, accurate diagnosis of fault types is becoming increasingly important. Compared with a single one, multiple PV stations collect sufficient fault samples, but their data is not allowed to be shared directly due to potential conflicts of interest. Therefore, federated learning can be exploited to train a collaborative fault diagnosis model. However, the modeling efficiency is seriously affected by the model update mechanism since each PV station has a different computing capability and amount of data. Moreover, for the safe and stable operation of the PV system, the robustness of collaborative modeling must be guaranteed rather than simply being processed on a central server. To address these challenges, a novel asynchronous decentralized federated learning (ADFL) framework is proposed. Each PV station not only trains its local model but also participates in collaborative fault diagnosis by exchanging model parameters to improve the generalization without losing accuracy. The global model is aggregated distributedly to avoid central node failure. By designing the asynchronous update scheme, the communication overhead and training time are greatly reduced. Both the experiments and numerical simulations are carried out to verify the effectiveness of the proposed method. © 2022, CC BY.

关键词： Failure analysis

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Energy Management for Zones-Based Isolated DC Multi-microgrids 3rd

Energy Management for Zones-Based Isolated DC Multi-microgri...

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3rd EAI International Conference on Smart Grid and Internet of Things, SGIoT 2019

作者： Nawaz, Arshad Wu, Jing Long, Chengnian Lin, Yi Bing Department of Automation School of Electronic Information and Electrical Engineering Key Laboratory of System Control and Information Processing Ministry of China Shanghai Jiao Tong University Shanghai China Department of Computer Science and Information Engineering National Chiao Tung University Hsinchu300 Taiwan

ISBN: (纸本)9783030496098

In this paper, zones based distributed energy management for isolated multi-microgrids is proposed. Loads are categorized into different zones to form zonal multi-microgrids. Each microgrid has own energy management system which can locally manages the supply and demand of its zonal load and minimize the operational cost. Distributed Network Operator (DNO) act as central controller to facilitate the energy exchange between zonal microgrids and balancing the overall system-wide supply and demand in economic way. Demand Response Program (DRP) is also utilized for peak load shifting within the scheduling horizon. In addition to minimization of operation cost, the utilization of DR will also assure the reliability of supply. In the proposed distributed energy management, each microgrid balances its supply and demand locally and exchange surplus and deficit power with other microgrids through DNO. The performance of proposed scheme is demonstrated through case study simulation of radial multi-microgrid structure. © 2020, ICST Institute for Computer Sciences, Social Informatics and Telecommunications engineering.

关键词： Energy management

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Mixture of Experts for Network Optimization: A Large Language Model-enabled Approach

arXiv

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arXiv 2024年

作者： Du, Hongyang Liu, Guangyuan Lin, Yijing Niyato, Dusit Kang, Jiawen Xiong, Zehui Kim, Dong In The School of Computer Science and Engineering Nanyang Technological University Singapore639798 Singapore The State Key Laboratory of Networking and Switching Technology Beijing University of Posts and Telecommunications Beijing100876 China The School of Automation Guangdong University of Technology Key Laboratory of Intelligent Information Processing and System Integration of IoT Ministry of Education Guangzhou510006 China Guangdong-HongKong-Macao Joint Laboratory for Smart Discrete Manufacturing Guangzhou510006 China The Pillar of Information Systems Technology and Design Singapore University of Technology and Design Singapore487372 Singapore The Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of

Optimizing various wireless user tasks poses a significant challenge for networking systems because of the expanding range of user requirements. Despite advancements in Deep Reinforcement Learning (DRL), the need for customized optimization tasks for individual users complicates developing and applying numerous DRL models, leading to substantial computation resource and energy consumption and can lead to inconsistent outcomes. To address this issue, we propose a novel approach utilizing a Mixture of Experts (MoE) framework, augmented with Large Language Models (LLMs), to analyze user objectives and constraints effectively, select specialized DRL experts, and weigh each decision from the participating experts. Specifically, we develop a gate network to oversee the expert models, allowing a collective of experts to tackle a wide array of new tasks. Furthermore, we innovatively substitute the traditional gate network with an LLM, leveraging its advanced reasoning capabilities to manage expert model selection for joint decisions. Our proposed method reduces the need to train new DRL models for each unique optimization problem, decreasing energy consumption and AI model implementation costs. The LLM-enabled MoE approach is validated through a general maze navigation task and a specific network service provider utility maximization task, demonstrating its effectiveness and practical applicability in optimizing complex networking systems. © 2024, CC BY.

关键词： Reinforcement learning

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