检索结果-内蒙古大学图书馆

Real-Time Harmonic Pollution Evaluation Considering Multiple Dynamic Customers

CSEE Journal of Power and Energy Systems 2023年第3期11卷 1093-1106页

作者： Shaohua Yang Keng-Weng Lao Hongxun Hui Yulin Chen Ningyi Dai Department of Electrical and Computer Engineering State Key Laboratory of Internet of Things for Smart City University of Macau Macao China

The widespread deployment of renewable energies and non-linear loads has led to serious harmonic pollution in electrical distribution networks. Evaluation of the harmonic contribution (HC) of each customer is a significant task for power quality management. Most previous studies focus on periodic evaluation methods, where numerous data have to be collected in advance over a period (e.g., one day). However, customer behaviors are time-varying and would lead to dynamic HCs, which can not be captured by traditional periodic evaluation methods. To address this issue, this paper presents a novel real-time HC evaluation method considering multiple dynamic customers. First, a two-stage iteration estimator is proposed based on the information fusion technique to quantify real-time HC of each customer. Then, to mitigate the negative effect of unknown background harmonics, a dominant index method is developed to determine credibility of the measurement data. On this basis, an adaptive gain selection strategy is proposed to improve accuracy of real-time HC evaluation. By doing so, the major harmonic contributor can be identified for implementing harmonic suppression and improving power quality. Finally, a typical IEEE system is utilized to verify the proposed methods. The results show that using the proposed method, evaluation errors can be reduced from about 10% to 2.5%. Moreover, the total harmonic distortion of voltage can be suppressed from 5.564% to 0.702%. Therefore, this research provides practical insights for addressing harmonic problems in power systems.

关键词： Harmonic analysis Power system harmonics Real-time systems Distribution networks Behavioral sciences Voltage measurement Impedance

来源：评论

学校读者我要写书评

暂无评论

DEEP-iot: Downlink-Enhanced Efficient-Power Internet of Things

arXiv

引用

arXiv 2024年

作者： Shao, Yulin State Key Laboratory of Internet of Things for Smart City The Department of Electrical and Computer Engineering University of Macau China

At the heart of the Internet of Things (iot) – a domain witnessing explosive growth – the imperative for energy efficiency and the extension of device lifespans has never been more pressing. This paper presents DEEP-iot, an innovative communication paradigm poised to redefine how iot devices communicate. Through a pioneering feedback channel coding strategy, DEEP-iot challenges and transforms the traditional transmitter (iot devices)-centric communication model to one where the receiver (the access point) play a pivotal role, thereby cutting down energy use and boosting device longevity. We not only conceptualize DEEP-iot but also actualize it by integrating deep learning-enhanced feedback channel codes within a narrow-band system. Simulation results show a significant enhancement in the operational lifespan of iot cells – surpassing traditional systems using Turbo and Polar codes by up to 52.71%. This leap signifies a paradigm shift in iot communications, setting the stage for a future where iot devices boast unprecedented efficiency and durability. Copyright © 2024, The Authors. All rights reserved.

关键词： Energy utilization

来源：评论

学校读者我要写书评

暂无评论

A Modified Data-driven Power Flow Model for Power Estimation with Incomplete Bus Data 12

A Modified Data-driven Power Flow Model for Power Estimation...

引用

12th International Conference on Power, Energy and electrical engineering, CPEEE 2022

作者： Xing, Zheng Lao, Keng-Weng Gao, Hongjun Dai, Ningyi University of Macau State Key Laboratory of Internet of Things for Smart City Department of Electrical and Computer Engineering Macao China Sichuan University College of Electrical Engineering Sichuan China

ISBN: (纸本)9781665420495

For power estimation in power systems, the power flow formulation is the most commonly used method. Data-driven approach is a newly proposed technology, unlike traditional model-driven power flow calculations, it can bypass circuit parameters and environmental variables to obtain results from global bus data. However, with the development of renewable energy, more complex power grids make it difficult to obtain complete data and reduce performance. Therefore, this paper proposes a method of estimating power from incomplete bus data. The method is based on a modified data-driven power flow model, and its core is to derive and induce a regressive model through the physical model. The simulation results on IEEE standard bus 30 show that this method has higher accuracy than other models in incomplete bus data power estimation. © 2022 IEEE.

关键词： Buses

来源：评论

学校读者我要写书评

暂无评论

AnycostFL: Efficient On-Demand Federated Learning over Heterogeneous Edge Devices 42

AnycostFL: Efficient On-Demand Federated Learning over Heter...

引用

42nd IEEE International Conference on computer Communications, INFOCOM 2023

作者： Li, Peichun Cheng, Guoliang Huang, Xumin Kang, Jiawen Yu, Rong Wu, Yuan Pan, Miao Guangdong University of Technology School of Automation Guangzhou China University of Macau State Key Laboratory of Internet of Things for Smart City China University of Houston Department of Electrical and Computer Engineering Houston United States

ISBN: (纸本)9798350334142

In this work, we investigate the challenging problem of on-demand federated learning (FL) over heterogeneous edge devices with diverse resource constraints. We propose a cost-adjustable FL framework, named AnycostFL, that enables diverse edge devices to efficiently perform local updates under a wide range of efficiency constraints. To this end, we design the model shrinking to support local model training with elastic computation cost, and the gradient compression to allow parameter transmission with dynamic communication overhead. An enhanced parameter aggregation is conducted in an element-wise manner to improve the model performance. Focusing on AnycostFL, we further propose an optimization design to minimize the global training loss with personalized latency and energy constraints. By revealing the theoretical insights of the convergence analysis, personalized training strategies are deduced for different devices to match their locally available resources. Experiment results indicate that, when compared to the state-of-the-art efficient FL algorithms, our learning framework can reduce up to 1.9 times of the training latency and energy consumption for realizing a reasonable global testing accuracy. Moreover, the results also demonstrate that, our approach significantly improves the converged global accuracy. © 2023 IEEE.

关键词： Energy utilization

来源：评论

学校读者我要写书评

暂无评论

Optimal Operation and Economic Analysis of Ice Thermal Energy Storage in District Cooling System

Optimal Operation and Economic Analysis of Ice Thermal Energ...

引用

IEEE General Meeting Power& Energy Society

作者： Xiangyu Wei Hongcai Zhang Chi Kong Wong Department of Electrical and Computer Engineering State Key Laboratory of Internet of Things for Smart City University of Macau Macao China

ISBN: (数字)9798350381832

ISBN: (纸本)9798350381849

Ice thermal energy storage (ITES) is a type of cooling thermal energy storage. It can shift the daytime peak cooling load to nighttime, thereby enhancing the economic benefit of the cooling system and enabling peak load shifting in the power grid. Although ITES has been widely utilized in district cooling systems (DCSs), the economic assessment of its implementation in DCS remains inadequate due to the thermal dynamics and operation strategy. This paper first presents an ITES-equipped DCS optimal operation model integrated with the time of use electricity price and demand charge. The proposed model can provide the economically optimal operation scheme considering the ITES dynamic charging/discharging process, and the change of the chiller's coefficient of performance, which depends on the ambient temperature and partial load rates. Then the economy of the ITES in a real DCS is assessed based on the proposed operation model. A comprehensive case study is employed to evaluate its benefit in comparison with the DCS equipped with battery energy storage. The case study indicates that the DCS with ITES outperforms in the economy, whereas DCS with battery energy storage surpasses in reducing demand charge.

关键词： Temperature dependence Costs Cooling Electricity Power system dynamics Ice Real-time systems Batteries Thermal energy Load modeling

来源：评论

学校读者我要写书评

暂无评论

Enhancing Simulation Precision of Modular Multilevel Converters Through Hardware-Informed Digital Twin

Enhancing Simulation Precision of Modular Multilevel Convert...

引用

Energy Storage and Conversion (ISESC), CPSS & IEEE International Symposium on

作者： Zhipeng Zhou Ning Yi Dai State Key Laboratory of Internet of Things for Smart City and Department of Electrical and Computer Engineering University of Macau Macao China

ISBN: (数字)9798350380514

ISBN: (纸本)9798350380521

In many scenarios, most power electronics simulation tools cannot accurately track the output performance of modular multilevel converters (MMCs) during experimental verification. Therefore, this paper presents a digital twin (DT)-driven method leveraging hardware information to improve the simulation precision of MMCs. This DT model, which is developed on the Python/PSCAD co-simulation platform, not only facilitates the processing of experimental data, but also realizes the automatic control of simulation. The design principle of the proposed model is demonstrated using a physical three-phase MMC with carrier phase-shifted pulsewidth modulation (CPS-PWM). The results prove that compared with the traditional simulation model, the voltage and current performance of the DT model aligns more closely with that of the physical system.

关键词： Multilevel converters Process control Pulse width modulation Harmonic analysis Data models Real-time systems Power electronics Hardware Digital twins Energy storage

来源：评论

学校读者我要写书评

暂无评论

Incentive Mechanism Design for Electricity Data Trading With Data Valuation-Aware Contract

Incentive Mechanism Design for Electricity Data Trading With...

引用

IEEE General Meeting Power& Energy Society

作者： Liya Ma Hongxun Hui Yonghua Song Department of Electrical and Computer Engineering State Key Laboratory of Internet of Things for Smart City University of Macau Macao China

ISBN: (数字)9798350381832

ISBN: (纸本)9798350381849

With more generation fluctuations from the high penetration of renewable energies, dispatching large-scale demand-side resources becomes crucial in maintaining the power system balance between supply-side and demand-side. It puts forth significantly greater data requirements compared with traditional power systems, e.g. explosive data volume and highly frequent data collection between the data aggregators (DAs) and the data service operator (DTSO). Preferred by the DTSO, higher-value data with better data quality and timeliness will bring more benefits to the real-time dispatching of the demand-side resources than lower-value data. Thus, the data should be collected, transmitted, and traded in accordance with their varying values across different DAs. To resolve this issue, this paper proposes an incentive mechanism for electricity data trading between DAs and the DTSO, incorporating a data valuation-aware contract. First, we develop a data valuation model considering the data quality and timeliness. Then, taking into account the diverse value of data across DAs, we design a trading volume-reward bundled contract for DAs. The DTSO provides DAs with varying rewards to obtain higher-value data. Finally, the effectiveness of the proposed mechanism is validated using realistic data.

关键词： Data privacy Renewable energy sources Electricity Data integrity Dispatching Data models Real-time systems Power systems Contracts Cost accounting

来源：评论

学校读者我要写书评

暂无评论

Operational Reliability Evaluation of Urban Multi-Energy Systems With Equivalent Energy Storage

引用

IEEE Transactions on Industry Applications 2022年第2期59卷 1-15页

作者： Wang S. Hui H. Ding Y. Ye C. Zheng M. State Key Laboratory of Internet of Things for Smart City the Department of Electrical and Computer Engineering University of Macau MacaoChina College of Electrical Engineering Zhejiang University Hangzhou China College of Energy Engineering Zhejiang University Hangzhou China

With the coordination of multiple energies at the city level, the complexity of the urban energy system is ever-increasing. Securing the reliable operation of the urban multi-energy system (UMES) has become a challenging task. This paper focuses on the operational reliability evaluation of the UMES considering the incorporation of equivalent energy storages. First, a novel concept of dynamic energy hub is proposed, as a unified tool to characterize the dynamic relationships of the operating conditions of diverse components in the UMES. Then, the temperature-controlled load (TCL) is modeled as the equivalent energy storage considering the thermal dynamics. Its operational reliabilities, as well as multiple other components, are modeled using the reliability equivalent technique to reduce the dimension of uncertainties. Moreover, a contingency management scheme of the UMES is developed in an optimal control framework considering the comfort costs of equivalent energy storages. To deal with the time-dependency of the optimal control problem, a simplified Benders decomposition procedure is devised and embedded in the Time-sequential Monte Carlo simulation to improve the computation efficiency of the reliability evaluation. Finally, a practical case of a UMES in southern China is used to validate the proposed technique. IEEE

关键词： Cogeneration Costs dynamic energy hub Energy storage equivalent energy storage Indexes operational reliability Reliability Resistance heating simplified Benders decomposition Urban areas urban multi-energy systems

来源：评论

学校读者我要写书评

暂无评论

Deep Joint Source-Channel Coding Over the Relay Channel

Deep Joint Source-Channel Coding Over the Relay Channel

引用

Machine Learning for Communication and Networking (ICMLCN), IEEE International Conference on

作者： Chenghong Bian Yulin Shao Haotian Wu Deniz Gündüz The Department of Electrical and Electronic Engineering Imperial College London The Department of Electrical and Computer Engineering State Key Laboratory of Internet of Things for Smart City University of Macau

ISBN: (数字)9798350343199

ISBN: (纸本)9798350343205

This paper presents a novel deep joint source-channel coding (DeepJSCC) scheme for image transmission over a half-duplex cooperative relay channel. Specifically, we apply DeepJSCC to two basic modes of cooperative communications, namely amplify-and-forward (AF) and decode-and-forward (DF). In DeepJSCC-AF, the relay simply amplifies and forwards its received signal. In DeepJSCC-DF, on the other hand, the relay first reconstructs the transmitted image and then re-encodes it before forwarding. Considering the excessive computation overhead of DeepJSCC-DF for recovering the image at the relay, we propose an alternative scheme, called DeepJSCC-PF, in which the relay processes and forwards its received signal without necessarily recovering the image. Simulation results show that the proposed DeepJSCC-AF, DF, and PF schemes are superior to the digital baselines with BPG compression with polar codes and provide a graceful performance degradation with deteriorating channel quality. Further investigation shows that the PSNR gain of DeepJSCC-DF/PF over DeepJSCC-AF improves as the channel condition between the source and relay improves. Moreover, the DeepJSCC-PF scheme achieves similar performance to DeepJSCC-DF with lower computational complexity.

关键词： Degradation Image coding Protocols Image communication Simulation Half-duplex system Machine learning

来源：评论

学校读者我要写书评

暂无评论

Wireless Federated Learning With Hybrid Local and Centralized Training: A Latency Minimization Design

引用

IEEE Journal on Selected Topics in Signal Processing 2023年第1期17卷 248-263页

作者： Huang, Ning Dai, Minghui Wu, Yuan Quek, Tony Q. S. Shen, Xuemin State Key Lab of Internet of Things for Smart City China University of Macau Department of Computer and Information Science China University of Macau State Key Laboratory of Internet of Things for Smart City The Department of Computer and Information Science China Zhuhai Um Science and Technology Research Institute Zhuhai519031 China Singapore University of Technology and Design Information Systems Technology and Design Pillar 487372 Singapore National Cheng Kung University Taiwan University of Waterloo Department of Electrical and Computer Engineering WaterlooONN2L 3G1 Canada

Wireless federated learning (FL) is a collaborative machine learning (ML) framework in which wireless client-devices independently train their ML models and send the locally trained models to the FL server for aggregation. In this paper, we consider the coexistence of privacy-sensitive client-devices and privacy-insensitive yet computing-resource constrained client-devices, and propose an FL framework with a hybrid centralized training and local training. Specifically, the privacy-sensitive client-devices perform local ML model training and send their local models to the FL server. Each privacy-insensitive client-device can have two options, i.e., (i) conducting a local training and then sending its local model to the FL server, and (ii) directly sending its local data to the FL server for the centralized training. The FL server, after collecting the data from the privacy-insensitive client-devices (which choose to upload the local data), conducts a centralized training with the received datasets. The global model is then generated by aggregating (i) the local models uploaded by the client-devices and (ii) the model trained by the FL server centrally. Focusing on this hybrid FL framework, we firstly analyze its convergence feature with respect to the client-devices' selections of local training or centralized training. We then formulate a joint optimization of client-devices' selections of the local training or centralized training, the FL training configuration (i.e., the number of the local iterations and the number of the global iterations), and the bandwidth allocations to the client-devices, with the objective of minimizing the overall latency for reaching the FL convergence. Despite the non-convexity of the joint optimization problem, we identify its layered structure and propose an efficient algorithm to solve it. Numerical results demonstrate the advantage of our proposed FL framework with the hybrid local and centralized training as well as our proposed alg

关键词： Information management

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：