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2023 IEEE International Conference on Environment and electrical engineering and 2023 IEEE Industrial and Commercial Power systems Europe, EEEIC / I and CPS Europe 2023

作者： Ali, Ola Mohammed, Osama A. Florida International University Energy Systems Research Laboratory Department of Electrical and Computer Engineering MiamiFL33174 United States

ISBN: (纸本)9798350347432

Power system dynamics have significantly changed with the global integration of renewable energy sources (RESs). Traditionally, the stored kinetic energy is used for compensating the generation mismatch using the rotating mass of the Synchronous Generators (SGs). With the increase in RESs penetration, SGs are being replaced by inverter-based RESs generation systems which are decoupled from the power systems through power converters. Therefore, the total inertia of the system has decreased, and the system's stability is significantly impacted as the value of the rate of change of frequency (ROCOF) and frequency deviations will be increased. To overcome these challenges, inertia emulation from various energy storage systems (ESS) is used to act as a virtual source of inertia power. This work presents an isolated microgrid (MG) that includes conventional power generation sources and RESs, and an optimal virtual inertia (VI) control loop is proposed for frequency stability enhancement. Supercapacitors (SC) bank with a PID controller presents the VI control loop and acts as a supplementary source for inertia power to support the frequency stability of the system. A genetic algorithm (GA) is used as an optimization technique to get the optimal values of the PID controller gains. The performance of the islanded MG with the proposed optimal control scheme is examined under different operating conditions with varying levels of RESs penetration and system parameters uncertainties. The proposed technique showed its effectiveness and robustness over the system's operation without VI control for keeping the system stable under different operating conditions. © 2023 IEEE.

关键词： Genetic algorithms

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Controlled Islanding Strategy Considering Uncertainty of Renewable Energy Sources Based on Chance-constrained Model

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Journal of Modern Power systems and Clean Energy 2022年第2期10卷 471-481页

作者： Shengyuan Liu Tianhan Zhang Zhenzhi Lin Yilu Liu Yi Ding Li Yang the School of Electrical Engineering Zhejiang UniversityHangzhou 310027China the Department of Electrical Engineering and Computer Science University of TennesseeKnoxvilleTN 37996USA the School of Electrical Engineering Shandong UniversityJinan 250061China Electrical and Electronics Systems Research Division Oak Ridge National LaboratoryOak RidgeTN 37830USA

Controlled islanding plays an essential role in preventing the blackout of power *** there are several studies on this topic in the past,no enough attention is paid to the uncertainty brought by renewable energy sources(RESs)that may cause unpredictable unbalanced power and the observabilit>T of power systems after islanding that is essential for back-up black-start ***,a novel controlled islanding model based on mixed-integer second-order cone and chance-constrained programming(MISOCCP)is proposed to address these ***,the uncertainty of RESs is characterized by their possibility distribution models with chance constraints,and the requirements,e.g.,system observability,for rapid back-up black-start measures are also ***,a law of large numbers(LLN)based method is em-ployed for converting the chance constraints into deterministic ones and reformulating the non-convex model into convex ***,case studies on the revised IEEE 39-bus and 118-bus power systems as well as the comparisons among different models are given to demonstrate the effectiveness of the proposed *** results show that the proposed model can result in less unbalanced power and better observability after islanding compared with other models.

关键词： Controlled islanding second-order cone chance-constrained programming renewable energy source(RES) black-start observability.

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Enhancing DC Microgrid Stability under Pulsed Load Conditions through Hybrid Energy Storage Control Strategy

Enhancing DC Microgrid Stability under Pulsed Load Condition...

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2023 IEEE Industry Applications Society Annual Meeting, IAS 2023

作者： Aghmadi, Ahmed Ali, Ola Mohammed, Osama A. Florida International University Energy Systems Research Laboratory Department of Electrical and Computer Engineering MiamiFL33174 United States

ISBN: (纸本)9798350320169

Despite the increasing prevalence of DC microgrids, they encounter instability issues due to imbalances in supply and demand, especially when dealing with specific loads such as pulse load or variable pulse load. The system faces severe changes which reduce the effectiveness of typical PV-Battery control systems. The solution to this problem frequently involves the use of energy storage devices such as supercapacitors SCs. When exposed to transients, batteries risk having their lifespans shortened and are challenged in keeping the stability of DC bus voltage and reducing overall transients. In order to increase the stability of DC microgrids and thereby increase their reliability and resilience, it is possible to combine the advantages of batteries and supercapacitors. Integrating both batteries and supercapacitors effectively enables DC microgrids to manage both steady-state and transient conditions. The main goal of this research paper is to investigate how the hybrid energy storage system (HESS) improves the stability of DC microgrids. According to sets of results, the proposed scheme has successfully reduced DC bus voltage variations regardless of variations in solar irradiance and the different pulsed load profiles. © 2023 IEEE.

关键词： Supercapacitor

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Heterogeneous Statistical QoS Provisioning for Scalable Software-Defined 6G Mobile Networks 57

Heterogeneous Statistical QoS Provisioning for Scalable Soft...

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57th Annual Conference on Information Sciences and systems, CISS 2023

作者： Zhang, Xi Zhu, Qixuan Poor, H. Vincent Texas AandM University Networking and Information Systems Laboratory Department of Electrical and Computer Engineering College StationTX77843 United States Princeton University Department of Electrical and Computer Engineering PrincetonNJ08544 United States

ISBN: (纸本)9781665451819

Due to the explosively increasing number of mobile users and the new types of data demands in the fifth generation (5G) mobile wireless network, research in wireless networks has shifted toward the development of the sixth-generation (6G) wireless network. Although the research for software-defined network (SDN) architectures in 5G mainly focuses on the dynamic programming for the internet backbone, these software programming techniques can be also applied at the network edge to support the exponentially increasing demands from mobile users under constrained wireless resources. In order to study the interference problem resulted by massive mobile users, the scaling law is a powerful tool to show how fast the levels of network imperfections can be tolerated as the number of mobile users increases. In this paper, we investigate the scaling behavior of software-defined architectures over 6G wireless networks. We consider the wireless channel in three scenarios: single-input-single-output (SISO), multiple-input-single-output (MISO), and multiple-input-multiple-output (MIMO), where we derive the corresponding scaling law for each scenario, respectively. Our derived scaling law shows how the network performance scales with the number of mobile users in a wireless network. Then, we propose a software-defined network slicing scheme to select the optimal mobile users and derive their optimal resource allocations, according to our derived scaling law, under SISO, MISO, and MIMO wireless channel, respectively. Finally, we validate and evaluate the derived scaling behavior of the software-defined architecture over 6G wireless networks through numerical analyses. © 2023 IEEE.

关键词： Wireless networks

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Massive-MIMO Based RSMA Under Nakagami-m Channel Over 6G mURLLC Wireless Networks 57

Massive-MIMO Based RSMA Under Nakagami-m Channel Over 6G mUR...

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57th Annual Conference on Information Sciences and systems, CISS 2023

ISBN: (纸本)9781665451819

The sixth generation (6G) mobile wireless networks are expected to provide massive ultra-reliable and low-latency communications (mURLLC) for data services, which require extremely stringent quality-of-services (QoS) with massive connectivity. Rate splitting (RS) multiple access schemes have been proposed recently for tackling the difficulty of the massive access yielded by a large number of mobile users (MUs) requesting to connect to a single base station. Massive multiple-input and multiple-output (massive-MIMO) communication is considered a promising solution to serve massive MUs in 6G wireless networks. However, how to apply RS schemes into massive-MIMO techniques to support the massive access has not been sufficiently studied. In this paper, we propose to integrate RS schemes with massive-MIMO techniques to achieve mURLLC transmissions under a Nakagamir $m$ fading wireless channel. First, we establish the system model for the integrated RS and massive-MIMO schemes. Then, we derive closed-form expressions for the signal-to-interference-plus-noise ratios (SINRs) under a Nakagami- $-m$ fading channel and obtain the channel capacity. Finally, we use numerical analyses to validate and evaluate our proposed RS and massive-MIMO integrated schemes. © 2023 IEEE.

关键词： Wireless networks

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Bi-level Optimal Planning of Voltage Regulator in Distribution systems Considering Maximization of Incentive-based Photovoltaic Energy Integration

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CSEE Journal of Power and Energy systems 2023年第6期9卷 2008-2017页

作者： Xu Xu Youwei Jia Chun Sing Lai Minghao Wang Zhao Xu Department of Electrical and Electronic Engineering Southern University of Science and TechnologyShenzhenChina Department of Electrical Engineering The Hong Kong Polytechnic UniversityHung HomHong Kong SARChina Department of Electrical and Electronic Engineering University Key Laboratory of Advanced Wireless Communications of Guangdong ProvinceSouthern University of Science and TechnologyShenzhen 515100China Department of Electronic and Computer Engineering Brunel Institute of Power SystemsBrunel University LondonLondonUB83PH United Kingdom Department of Electrical Engineering Shenzhen Research InstituteThe Hong Kong Polytechnic UniversityHung HomHong Kong SARChina

This paper focuses on optimal voltage regulator(VR)planning to maximize the photovoltaic(PV)energy integration in distribution *** describe the amount of dynamic PV energy that can be integrated into the power system,the concept of PV accommodation capability(PVAC)is introduced and modeled with *** proposed planning model is formulated as a Benders decomposition based bi-level stochastic optimization *** the upper-level problem,VR planning decisions and PVAC are determined via mixed integer linear programming(MILP)before considering *** in the lower-level problem,the feasibility of first-level results is checked by critical network constraints(*** magnitude constraints and line capacity constraints)under uncertainties considered by time-varying loads and PV *** this paper,these uncertainties are represented in the form of operational scenarios,which are generated by the Gaussian copula theory and reduced by a well-studied backward-reduction *** modified IEEE 33-node distribution grid is utilized to verify the effectiveness of the proposed *** results demonstrate that a PV energy integration can be significantly enhanced after optimal voltage regulator planning.

关键词： Bi-level stochastic optimization problem critical network constraints photovoltaic energy integration uncertainties voltage regulator planning

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The ϵ-Effective Capacity for Statistical Delay and Error-Rate Bounded QoS Provisioning Over 6G CF M-MIMO Wireless Networks Using HARQ-IR 57

The ϵ-Effective Capacity for Statistical Delay and Error-Ra...

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57th Annual Conference on Information Sciences and systems, CISS 2023

作者： Zhang, Xi Wang, Jingqing Poor, H. Vincent Texas AandM University Networking and Information Systems Laboratory Department of Electrical and Computer Engineering College StationTX77843 United States Princeton University Department of Electrical and Computer Engineering PrincetonNJ08544 United States

ISBN: (纸本)9781665451819

Significant effort has been devoted to the problem of guaranteeing stringent ultra-reliable and low-latency communications (URLLC) while introducing new requirements for better quality-of-services (QoS) over next generation wireless networks. One of the major design issues raised by URLLC is how to support explosively growing demands for delay-sensitive multimedia applications while guaranteeing ultra-reliability. Towards this end, there have been a wide spectrum of promising techniques, including statistical delay and error rate-bounded QoS provisioning, cell-free (CF) massive multiple-input-multiple-output (m-MIMO), finite blocklength coding (FBC), hybrid automatic repeat request with incremental redundancy (HARQ-IR) protocol, etc. However, when being integrated with FBC, how to rigorously and efficiently characterize the dynamics of mobile wireless networks in terms of statistical delay and error-rate bounded QoS provisioning for CF m-MIMO has imposed many new challenges not encountered before. To overcome these challenges, in this paper we develop statistical delay and error-rate bounded QoS analytical modeling schemes to characterize the FBC-based ϵ-effective capacity over 6G CF m-MIMO wireless networks using HARQ-IR. In particular, first we establish CF m-MIMO based system architecture models. Second, we apply a HARQ-IR protocol for deriving the channel coding rate, outage probability, and FBC based ϵ-effective capacity function using the Mellin transform. Finally, we conduct a set of simulations to validate and evaluate our proposed schemes. © 2023 IEEE.

关键词： Wireless networks

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A Robust Polyscale Length Complexity Measure for Stochastic Self-Affine Processes 20

A Robust Polyscale Length Complexity Measure for Stochastic ...

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20th IEEE International Conference on cognitive Informatics and cognitive Computing, ICCI*CC 2021

作者： Kinsner, Witold University of Manitoba Cognitive Systems Laboratory Department of Electrical and Computer Engineering Winnipeg Canada

ISBN: (纸本)9781665421195

cognitive and other nonlinear systems often involve deterministic differentiable processes and stochastic non-differentiable processes. Measuring the complexity of such processes is important when extracting objective features from the processes for their classification in either reactive, or adaptive, or predictive control. This applies to classifiers based not only to the traditional neural networks, but also to deep learning systems, and particularly in cognitive systems. This paper describes a robust algorithm to measure the length complexity of a self-Affine time series using multiscale and polyscale analyses, and provides new insight in the theoretical and practical aspects of extracting the measure. © 2021 IEEE.

关键词： Signal analysis

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Real-time binaural speech reproduction with deep neural networks and dynamic head tracking 156

Real-time binaural speech reproduction with deep neural netw...

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AES Madrid 2024: 156th Audio engineering Society Convention

作者： Papavasileiou, Ioannis Thoidis, Iordanis Sevastiadis, Christos Vryzas, Nikolaos Papanikolaou, George Laboratory of Electroacoustics and TV Systems School of Electrical and Computer Engineering Faculty of Engineering Aristotle University of Thessaloniki Thessaloniki Greece Laboratory of Electronic Media Department of Journalism and Mass Media Aristotle University of Thessaloniki Thessaloniki Greece

This study examines the efficacy of a deep learning-based binaural speech reproduction system via headphones that integrates real-time head tracking to simulate a stable speech source in a virtual environment. We developed a binaural speech reproduction system that operates in real time using a custom head-tracking device based on the Arduino platform and a pre-trained neural network model for binaural speech synthesis. The system dynamically adapts audio output based on the head orientation of the listener, operating with an overall latency of 70 ms on standard computing hardware. We conducted a subjective speech localization task with 15 young, normal-hearing participants. Initial results showed a 40% accuracy in localizing a static speech source, which significantly improved with dynamic head movements. Participants reported minimal dizziness and distortion, indicating good tolerability and sound quality. Despite some limitations, such as non-personalized settings and perceivable latency, the findings demonstrate the potential of deep learning approaches to enhance realism in virtual auditory environments. Further research is needed to refine these technologies for broader applications in immersive audio settings. © AES Madrid 2024: 156th Audio engineering Society Convention. All rights reserved.

关键词： Deep neural networks

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ETAG: An Energy-Neutral Ear Tag for Real-Time Body Temperature Monitoring of Dairy Cattle 23

ETAG: An Energy-Neutral Ear Tag for Real-Time Body Temperatu...

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29th Annual International Conference on Mobile Computing and Networking, MobiCom 2023

作者： Vu, Hien Chung, Hanwook Choi, Christopher Kim, Younghyun Department of Electrical and Computer Engineering College of Engineering Wisconsin Embedded Systems and Computing Laboratory University of Wisconsin-Madison MadisonWI60032179 United States

ISBN: (纸本)9781450399906

Heat stress, caused by a warming climate and the increasingly high milk-producing dairy cattle, is one of the major threats to the well-being of dairy cattle as well as the economic, environmental, and social sustainability of dairy farming around the world. Timely identification of cows under heat stress is crucial to improving animal welfare, preventing milk production losses, and preserving water and energy for *** paper presents a smart ear tag, named eTag, and an associated system that can read a passive microchip temperature sensor subcutaneously injected into the animal with minimal discomfort. It features a lightweight design using a single coil shared for microchip scanning and wireless charging. eTag is autonomously recharged by a wireless charger over the head during daily milking sessions, enabling perpetual operation without battery replacement after deployment. The real-world performance of the proposed system was examined intensively in a three-week deployment on seven lactating Holstein cows. We demonstrate that eTag can reliably collect accurate body temperature in real time while maintaining a positive energy flow. The deployment of eTag will enable the timely detection of heat stress and facilitate precision control of barn cooling systems. © 2023 ACM.

关键词： Energy harvesting

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