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2024 IEEE Power and Energy Society General Meeting, PESGM 2024

作者： Hu, Yuxiao Li, Jiangtao Xu, Yang Jin, Yan Ma, Hui Ekanayake, Chandima Li, Junyao School of Electrical Engineering Xi'an Jiaotong University Xi'an China School of Electrical Engineering and Computer Science The University of Queensland Brisbane Australia

A bipolar VSC-HVDC system with multiple operation modes can improve the reliability of power grids. However, the overvoltage level is different for multiple HVDC links, which may lead to inadaptability of the existing insulation coordination. This paper proposes an improved cable transient model with the multi-layer structure and taking the effects of temperature and frequency on the wave propagation into account. Based on the proposed model, a bipolar system with dedicated metallic return cable (MRC) is established. Then, the magnitude and spatial dependency of the overvoltage on both cable core and sheath are analyzed. The results reveal that, compared with other operation modes, the bipolar configuration with MRC can attain desirable performance to limit overvoltage level. The results also indicate a high transient overvoltage exists on the core and sheath of the MRC which should be considered in operation. © 2024 IEEE.

关键词： Cable sheathing

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Incremental Weighted Ensemble for Data Streams With Concept Drift

IEEE Transactions on Artificial Intelligence

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IEEE Transactions on Artificial Intelligence 2024年第1期5卷 92-103页

作者： Jiao, Botao Guo, Yinan Yang, Cuie Pu, Jiayang Zheng, Zhiji Gong, Dunwei School of Electromechanical and Information Engineering Beijing100083 China China University of Mining and Technology School of Information and Control Engineering Xuzhou221116 China Victoria University of Wellington School of Engineering and Computer Wellington6140 New Zealand Electromechanical and Information Engineering Beijing100083 China Qingdao University of Science and Technology School of Information Science and Technology Qingdao266061 China

As a popular strategy to tackle concept drift, chunk-based ensemble method adapts a new concept by adjusting the weights of historical classifiers. However, most previous approaches normally evaluate the historical classifier based on an entire chunk newly arrived, which may cause delayed adaptation. To address the issue, two novel ensemble models, named incremental weighted ensemble (IWE) and incremental weighted ensemble for multi-classification (IWE-M), are proposed. At each time step, all base classifiers are incrementally updated on a newly arrived instance. Following that, the instance is collected into a cache array. Once a data chunk is formed, a new base classifier is created. More specially, a forgetting mechanism based on variable-size window is designed to adjust the weight of each base classifier in IWE in terms of its classification accuracy on the latest instances in an online manner. IWE-M, an extension of IWE, aims to solve multiclass problems with local concept drifts. In IWE-M, the weight of a base classifier is expanded to a weight vector. In this way, this ensemble model can retain specific historical information about nondrift regions from a local drift. Experimental results show that the proposed ensemble frameworks outperform six competitive approaches on accuracy and G-mean. © 2020 IEEE.

关键词： Classifiers

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Cache Allocation in Multi-tenant Edge Computing: an Online Model-based Reinforcement Learning Approach

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IEEE Transactions on Cloud Computing 2025年第02期13卷 459-472页

作者： Ben-Ameur, Ayoub Araldo, Andrea Chahed, Tijani Dan, Gyorgy SAMOVAR Telecom SudParis Institut Polytechnique de Paris France KTH Royal Institute of Technology Division of Network and Systems Engineering School of Electrical Engineering and Computer Science Sweden

We consider a Network Operator (NO) that owns Edge Computing (EC) resources, virtualizes them and lets third party Service Providers (SPs) run their services, using the allocated slice of resources. We focus on one specific resource, i.e., cache space, and on the problem of how to allocate it among several SPs in order to minimize the backhaul traffic. Due to confidentiality guarantees, the NO cannot observe the nature of the traffic of SPs, which is encrypted. Allocation decisions are thus challenging, since they must be taken solely based on observed monitoring information. Another challenge is that not all the traffic is cacheable. We propose a data-driven cache allocation strategy, based on Reinforcement Learning (RL). Unlike most RL applications, in which the decision policy is learned offline on a simulator, we assume no previous knowledge is available to build such a simulator. We thus apply RL in an online fashion, i.e., the model and the policy are learned by directly perturbing and monitoring the actual system. Since perturbations generate spurious traffic, we thus need to limit perturbations. This requires learning to be extremely efficient. To this aim, we devise a strategy that learns an approximation of the cost function, while interacting with the system. We then use such an approximation in a Model-Based RL (MB-RL) to speed up convergence. We prove analytically that our strategy brings cache allocation boundedly close to the optimum and stably remains in such an allocation. We show in simulations that such convergence is obtained within few minutes. We also study its fairness, its sensitivity to several scenario characteristics and compare it with a method from the state-of-the-art. © 2013 IEEE.

关键词： Contrastive Learning

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Optimized Temporary Frequency Support for Wind Power Plants Considering Expanded Operational Region of Wind Turbines

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CSEE Journal of Power and Energy Systems 2025年第1期11卷 51-64页

作者： Zhengyang Hu Bingtuan Gao Zhao Xu Sufan Jiang School of Electrical Engineering Southeast UniversityNanjing210096China Department of Electrical and Electronic Engineering The Hong Kong Polytechnic UniversityHong Kong SARChina Department of Electrical Engineering and Computer Science The University of TennesseeKnoxvilleTN 37996 USA

Wind power plants(WPPs)are increasingly mandated to provide temporary frequency support to power systems during contingencies involving significant power ***,the frequency support capabilities of WPPs under derated operations remain insufficiently investigated,highlighting the potential for further improvement of the frequency *** paper proposes a bi-level optimized temporary frequency support(OTFS)strategy for a *** implementation of the OTFS strategy is collaboratively accomplished by individual wind turbine(WT)controllers and the central WPP ***,to exploit the frequency support capability of WTs,the stable operational region of WTs is expanded by developing a novel dynamic power control approach in WT *** approach synergizes the WTs'temporary frequency support with the secondary frequency control of synchronous generators,enabling WTs to release more kinetic energy without causing a secondary frequency ***,a model predictive control strategy is developed for the WPP *** strategy ensures that multiple WTs operating within the expanded stable region are coordinated to minimize the magnitude of the frequency drop through efficient kinetic energy ***,comprehensive case studies are conducted on a real-time simulation platform to validate the effectiveness of the proposed strategy.

关键词： Active power control model predictive control optimized temporary frequency support wind power plant wind turbine

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Optimizing Crisis Management with Advanced UAV Imaging Technology 4

Optimizing Crisis Management with Advanced UAV Imaging Techn...

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4th International Conference on Sustainable Expert Systems, ICSES 2024

作者： Reddy, Jambula Snehith Mathi, Sri Chaithanya Reddy, Polu Sai Nadh Mateti, Vedha Pranava Yadav, Sudha Amrita School of Engineering Department of Electrical and Electronics Engineering Bengaluru India Amrita School of Engineering Department of Computer Science and Engineering Bengaluru India

ISBN: (纸本)9798331540364

The UAV systems that are fitted with current technology have helped in boosting the crisis management activities such as disaster relief operations, search and rescues, and policing. This paper integrates the developmental function of advanced detective UAVs into episodes of crises. These UAVs are capable of quickly and effectively assessing the damage, find people and observe post-disaster occurrences through with the help of complicated image analysis. It incorporates cameras with HD resolutions, thermal imagery systems, and numerous ML algorithms that allow entities and people to be identified besides detecting heat through barriers and thus increase the operational effectiveness during response operations. Indeed, the social implication as noticed with detective UAVs is highly useful in that it provides support services in disaster, bringing relief directly to the affected groups and guaranteeing the security of the rescue squads. Therefore, these UAVs enhance crisis consequence management, reducing death rates, the number of casualties and the extent of property damage. They do also help in safety and security to the public through assisting the police in surveillance and the fight against crime. Analyzing UAV's physical and virtual units, the challenges describe the UAV's use cases in different kinds of crises, such as natural ones, industrial failures, and criminal events. It also deals with issues such as restrictive policies, data security, and the requirement of professional personnel. From case studies and more personal accounts, detective UAVs' potential of crisis management is revolutionary: loss of life is avoided, damage to property is limited, and order is maintained. If further developed and properly integrated into the emergency management systems, UAVs will be the part of the equipment of the future for enhancing the efficiency of response to critical situations. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Energy Efficient Dual User Association for Large Scale IRS-Aided mmWave Communication Networks

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China Communications 2025年第1期22卷 182-195页

作者： Chen Guolin Deng Yiqin Huang Xiaoxia Fang Yuguang School of Electronics and Communication Engineering Sun Yat-sen UniversityShenzhen 518107China School of Control Science and Engineering Shandong UniversityJinan 250100China Department of Computer Science City University of Hong KongHong Kong 999077China

The deployment of multiple intelligent reflecting surfaces(IRSs)in blockage-prone millimeter wave(mmWave)communication networks have garnered considerable attention *** the remarkably low circuit power consumption per IRS element,the aggregate energy consumption becomes substantial if all elements of an IRS are turned on given a considerable number of IRSs,resulting in lower overall energy efficiency(EE).To tackle this challenge,we propose a flexible and efficient approach that individually controls the status of each IRS ***,the network EE is maximized by jointly optimizing the associations of base stations(BSs)and user equipments(UEs),transmit beamforming,phase shifts of IRS elements,and the associations of individual IRS elements and *** problem is efficiently addressed in two ***,the Gale-Shapley algorithm is applied for BS-UE association,followed by a block coordinate descent-based algorithm that iteratively solves the subproblems related to active beamforming,phase shifts,and element-UE *** reduce the tremendous dimensionality of optimization variables introduced by element-UE associations in large-scale IRS networks,we introduce an efficient algorithm to solve the associations between IRS elements and *** results show that the proposed elementwise control scheme improves EE by 34.24% compared to the network with IRS-all-on scheme.

关键词： energy efficiency intelligent reflecting surface,millimeter-wave communication

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Dynamic Wireless Charging of UAVs in 6G Enabled ITS 10

Dynamic Wireless Charging of UAVs in 6G Enabled ITS

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10th IEEE World Forum on Internet of Things, WF-IoT 2024

作者： Shaikh, Palwasha Waheed Mouftah, Hussein T. University of Ottawa School of Electrical Engineering and Computer Science Ottawa Canada

ISBN: (纸本)9798350373011

The intersection of 6G technology, the Internet of Things (IoT), and Intelligent Transportation System (ITS) to address the persistent challenge of Unmanned Aerial Vehicles (UAVs) with limited battery life is explored. Despite the proliferation and versatility of UAVs, their mission time is hampered due to battery constraints. This paper highlights the role of dynamic wireless charging (DWC) for UAVs in enabling charging automation, ease of use, and prolonged mission lifetimes. A literature review underscores the shortcomings of traditional charging methods and advocates for the use of laser beaming technology as an efficient DWC solution. The proposed system design leverages 6 G technology to enable real-time communication and seamless connectivity for optimizing UAV charging and operational efficiency. Simulation results demonstrate the efficiency of DWC and propel UAVs towards increased autonomy and efficiency, paving the way for newer applications of UAVs in the 6G-enabled ITS of smart cities. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Global Color-Aware Arbitrary Style Transfer with Discrete Wavelet Transform 20th

Global Color-Aware Arbitrary Style Transfer with Discrete W...

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20th IFIP WG 10.3 International Conference on Network and Parallel Computing, NPC 2024

作者： Chen, Bochao Tan, Junhao Li, Xiaoqiang Pei, Songwen School of Computer Engineering and Science Shanghai University Shanghai200444 China School of Optical-Electrical and Computer Engineering University of Shanghai for Science and Technology Shanghai200093 China

ISBN: (纸本)9789819628292

The purpose of image arbitrary style transfer is to apply a given artistic or photorealistic style to a target content image. While existing methods can effectively transfer style information, the variability in color brightness features between the style and content images can significantly impact the quality of the style transfer. Specifically, traditional arbitrary style transfer relies on an encoder-decoder architecture of spatial-aware neural networks operating in the RGB domain, which typically preserves only local color brightness information and lacks a global color perception compared to the wavelet frequency domain. In this paper, we address the issue of insufficient global color perception in images from the perspective of image enhancement. We propose Global Color-aware Arbitrary Style Transfer with Discrete Wavelet Transform (GCAST), which achieves a balance between the global color characteristics of style images and the local details of content images. Our approach involves an encoder that integrates preliminary feature encoding through cross-layer attention fusion, while the decoder modifies frequency features using a wavelet-based adjustment block. To maintain a balance between content and style in the stylized images, we design a comprehensive loss function that incorporates multiple restoration loss, double style loss, and noise regularization loss. Extensive experiments comparing our method with state-of-the-art techniques demonstrate that our proposed model generates stylized images with superior results in terms of global color perception and human perceptual studies. © IFIP International Federation for Information Processing 2025.

关键词： Decoding

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Autonomous WSNs node powered by a thermal energy harvester for temperature monitoring

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International Journal of Ambient Energy 2023年第1期44卷 1058-1066页

作者： Zhang, Zhijuan Ji, Xiaoming Zhang, Qunjun Hou, Liqun School of Electrical and Electronic Engineering North China Electric Power University Baoding China School of Control and Computer Engineering North China Electric Power University Baoding China

An autonomous wireless sensor networks (WSNs) node powered by a thermal energy harvester with MPPT is proposed in this paper for temperature monitoring. Two commercial TEG modules are used to build up the thermoelectric collector, while an energy management circuit with a DC/DC converter is employed to boost the TEG output voltage. The harvested energy is stored in a supercapacitor. The feasibility of the presented self-powered WSNs node is verified by a series of experiments with various node sleep periods and temperature differences across the thermoelectric generator (ΔT TEG). The results show that the proposed thermal energy harvester can work at its maximum power point and autonomously power a commercial WSN node when ΔT TEG is above 13.3°C and node sleep period is not less than 1.5 s. In addition, the designed self-powered WSNs node can monitor the temperature of industrial devices successfully. © 2023 Informa UK Limited, trading as Taylor & Francis Group.

关键词： Thermal energy

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A Grid-Based Random Erasing Approach for Enhanced Image Classification 4

A Grid-Based Random Erasing Approach for Enhanced Image Clas...

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4th IEEE International Conference on Data science and computer Application, ICDSCA 2024

作者： Li, Qingyi School of Electrical Engineering and Computer Science The University of Queensland Brisbane Australia

ISBN: (纸本)9798350368239

In modern image classification tasks, the data is insufficient due to time or money cost constraints, which affects the generalization and accuracy of the model. This paper proposes a random erasure method based on gridded images, aiming to expand the dataset to improve the generalization ability and classification accuracy of the model while reducing the damage to the original structure of the image caused by continuous erasure. This paper uses YOLOv8n-cls, YOLOv8mcls, and ResNet50 as models and selects CIFAR-10, CIFAR-100, FER2013, and mini-ImageNet as datasets for comparative experiments. The Top-1 accuracy, Top-5 accuracy, and loss function curves on the validation set are used to analyze the effect of random erasing on each model's performance on various datasets. The findings demonstrate that lightweight models greatly increase accuracy on simple datasets like CIFAR-10. However, to effectively use the enhancing effect of random erasing on complicated datasets, more sophisticated models are required. This study shows the impact of random erasing based on gridded images on improving the generalization ability and classification accuracy of the model in image classification tasks. It points out the limitations of this method and potential future optimization directions to better handle more complex classification tasks. ©2024 IEEE.

关键词： Image classification

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