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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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Semi-Blind Channel Estimation and Achievable Rate Analysis for Uplink RIS-Enhanced Multi-User Networks

IEEE Open Journal of Vehicular Technology

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IEEE Open Journal of Vehicular Technology 2025年 6卷 1108-1139页

作者： Farghaly, Samar I. Ismail, Mohamed I. Fouda, Mostafa M. Alwakeel, Ahmed S. Tanta University Department of Electronics and Electrical Communications Engineering Faculty of Engineering Tanta31111 Egypt Idaho State University Department of Electrical and Computer Engineering College of Science and Engineering PocatelloID83209 United States Modern Academy for Engineering Department of Electronic Engineering and Communication Technology Cairo Governorate 4411602 Egypt Center for Advanced Energy Studies Idaho FallsID83401 United States Suez University Department of Electrical Engineering Faculty of Engineering Suez43221 Egypt

Future wireless networks could benefit from the energy-efficient, low-latency, and scalable deployments that Reconfigurable Intelligent Surfaces (RISs) offer. However, the creation of an effective low overhead channel estimate technique is a major obstacle in RIS-assisted systems, especially given the high number of RIS components and intrinsic hardware constraints. This research examines the uplink of a RIS-empowered multi-user MIMO communication system and presents a novel semi-blind channel estimate approach. Unlike current approaches, which rely on pilot-based channel estimation, our methodology uses data to estimate channels, considerably enhancing the achievable rate. We provide a closed-form deterministic expression for the uplink achievable rate in actual settings where the channel state information (CSI) must be estimated rather than assumed perfect. The results of the simulations show that the formula obtained is accurate, with a close alignment between the deterministic and actual achievable rates (generally between 2 5% deviations). The proposed approach outperforms traditional approaches, resulting in rate increases of up to 35–40%, especially in instances with more RIS elements. These findings illustrate RIS technology's tremendous potential to improve system capacity and coverage, providing useful insights for optimizing RIS adoption in future wireless networks. © 2020 IEEE.

关键词： Channel state information

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HIL Simulation and Testing of the Distribution Network's Automatic Reconfiguration

HIL Simulation and Testing of the Distribution Network's Aut...

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2024 IEEE PES/IAS PowerAfrica, PowerAfrica 2024

作者： Ntshiba, Sikho Krishnamurthy, Senthil Nomandela, Sinawo Department of Electrical Electronic and Computer Engineering Cape Town South Africa

ISBN: (纸本)9798350389388

Distribution system network reconfiguration involves the optimization of the configuration of electrical distribution networks to enhance their performance, reliability, and efficiency. In this research work, distribution networks can be designed to automatically reconfigure themselves in response to faults, load changes, or other disturbances. This automatic reconfiguration can help minimize outage durations and improve system reliability. The hardware-in-the-loop (HIL) simulation results can significantly improve distribution networks' flexibility, reliability, and efficiency. © 2024 IEEE.

关键词： distribution system Network reconfiguration overcurrent protection

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New Presentation System of the Tesla Long Island Tower Realized in Machine Language 11

New Presentation System of the Tesla Long Island Tower Reali...

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11th International Conference on Electrical, electronic and Computing engineering, IcETRAN 2024

作者： Vuckovic, Vladan University of Niš Faculty of Electronic Engineering Computer Department Niš Serbia

ISBN: (数字)9798350386998

ISBN: (纸本)9798350386998

This paper presents the chronological development of the Tesla's tower project on Long Island, from his first ideas and plans, the details of the realization of the plant itself, and finally the creation of a 3D model of the tower on Long Island realized by the new Polygene presentation system, written in x64 machine language by the author. This very long course of events covers a period of more than a century. The tower itself was built in the period 1901-1902, and the project of construction and improvement of the 3D model started in 2011 through several successive technological projects. The presentation Polygene system (2023-2024) is a modern continuation of this Tesla's 3D project. © 2024 IEEE.

关键词： Digital elevation model

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Axon Chess Engine Evaluation Function 11

Axon Chess Engine Evaluation Function

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11th International Conference on Electrical, electronic and Computing engineering, IcETRAN 2024

作者： Vuckovic, Vladan University of Nis Faculty of Electronic Engineering Computer Department Nis Serbia

ISBN: (数字)9798350386998

ISBN: (纸本)9798350386998

This paper presents the details of the evaluation function, which is an integral part of the latest version of the author's chess application Axon (version 2024). The evaluation function is the most complex part of the chess program, developed and tested over a long period of time. The heuristics, which are explained and discussed in detail in the paper, represent an excellent basis for the development of chess program evaluators of grandmaster strength. © 2024 IEEE.

关键词： computer circuits

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Towards Integrating MQTT with Time-Sensitive Networking 29

Towards Integrating MQTT with Time-Sensitive Networking

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29th IEEE International Conference on Emerging Technologies and Factory Automation, ETFA 2024

作者： Testa, Giuseppe Leonardi, Luca Bello, Lucia Lo Patti, Gaetano University of Catania Department of Electrical Electronic and Computer Engineering Catania Italy

ISBN: (纸本)9798350361230

While the MQTT protocol is widely adopted in IoT applications, its usage for Industrial IoT is prevented by the lack of support for time-critical transmissions. For this reason, recent work has proposed the Prioritized MQTT (PrioMQTT) protocol, i.e., an MQTT extension that introduces message prioritization and schedules messages according to their priority, which reflects their temporal constraints. PrioMQTT succeeds in reducing the latencies of time-critical messages, but it cannot guarantee bounded delays, as the message priorities are not used by the underlying network level. For this reason, this work explores the integration of PrioMQTT with the Time-Sensitive Networking family of standards, in particular with the IEEE 802.1Q-2022, to handle multiple flows with diverse real-time requirements. The work also presents a preliminary experimental assessment on commercial-off-the-shelf devices. © 2024 IEEE.

关键词： Commercial off-the-shelf

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Data-Driven Simulation Based Fault Detection in Automotive RISC-V Applications 17

Data-Driven Simulation Based Fault Detection in Automotive R...

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17th IEEE International Symposium on Embedded Multicore/Many-core Systems-on-Chip, MCSoC 2024

作者： Vinciguerra, Elio Russo, Enrico Palesi, Maurizio Ascia, Giuseppe University of Catania Electronic and Computer Engineering Department of Electrical Catania Italy

ISBN: (纸本)9798331530471

Early fault detection in automotive systems is critical for ensuring user safety and initiating corrective actions. This work proposes an Artificial Intelligence (AI) framework for automotive fault detection. The system monitors Hardware Performance Monitor (HPM) counters to identify anomalous behavior and trigger alerts. By evaluating various fault detection models, the study identifies a neural network-based approach achieving a high detection accuracy of 96%. The impact of inference latency on overall system performance is also assessed. © 2024 IEEE.

关键词： Artificial Intelligence Fault Injection gem5 Hardware Performance Monitor RISC-V

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Impact of Rain on Frequency Bands in 4G/5G Networks: Implications for Industrial Connectivity 8

Impact of Rain on Frequency Bands in 4G/5G Networks: Implica...

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8th IEEE International Forum on Research and Technologies for Society and Industry Innovation, RTSI 2024

作者： Avanzato, Roberta Beritelli, Francesco Borzì, Maria Grazia University of Catania Department of Electrical Electronic and Computer Engineering Catania Italy

ISBN: (纸本)9798350362138

In recent years, there has been a growing interest in understanding how rain affects frequency bands in 4G/5G networks, especially in outdoor industrial environments. Most studies focus on the use of frequencies above 10 GHz, while few address this issue using frequencies typical of 4G/5G systems. This study investigates the effects of rain on band variation in 4G/5G mobile radio networks. In particular, by hypothesizing a value of eNBID, the number of times a band change occurs with and without rain was calculated. From these data, an increment factor (Δ F), normalized over time, was calculated to define the occurrence of band changes with and without rain. Two CNN network trainings were conducted with two different datasets, the first characterized by the absence of band variation information and the second characterized by the presence of such information. In the first case, an accuracy of about 75% was obtained, and in the second case, the obtained result was around 71%. These findings suggest that the addition of band variation information seems to be not relevant in terms of network performance. Finally, a CTGAN network was introduced for the generation of synthetic data for smaller classes, which resulted in an increase in performance of about 10%, reaching an average accuracy of 85% © 2024 IEEE.

关键词： 4G mobile communication systems

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LIPSIM: A PROVABLY ROBUST PERCEPTUAL SIMILARITY METRIC 12

LIPSIM: A PROVABLY ROBUST PERCEPTUAL SIMILARITY METRIC

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12th International Conference on Learning Representations, ICLR 2024

作者： Ghazanfari, Sara Araujo, Alexandre Krishnamurthy, Prashanth Khorrami, Farshad Garg, Siddharth Department of Electronic and Computer Engineering New York University United States

Recent years have seen growing interest in developing and applying perceptual similarity metrics. Research has shown the superiority of perceptual metrics over pixel-wise metrics in aligning with human perception and serving as a proxy for the human visual system. On the other hand, as perceptual metrics rely on neural networks, there is a growing concern regarding their resilience, given the established vulnerability of neural networks to adversarial attacks. It is indeed logical to infer that perceptual metrics may inherit both the strengths and shortcomings of neural networks. In this work, we demonstrate the vulnerability of state-of-the-art perceptual similarity metrics based on an ensemble of ViT-based feature extractors to adversarial attacks. We then propose a framework to train a robust perceptual similarity metric called LipSim (Lipschitz Similarity Metric) with provable guarantees. By leveraging 1-Lipschitz neural networks as the backbone, LipSim provides guarded areas around each data point and certificates for all perturbations within an 2 ball. Finally, a comprehensive set of experiments shows the performance of LipSim in terms of natural and certified scores and on the image retrieval application. © 2024 12th International Conference on Learning Representations, ICLR 2024. All rights reserved.

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Leveraging Reinforcement Learning for a Novel Traffic-Aware Scheduler in 5G NR IIoT Networks 35

Leveraging Reinforcement Learning for a Novel Traffic-Aware ...

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35th IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC 2024

作者： Miuccio, Luciano Riolo, Salvatore Cuozzo, Giampaolo Marini, Riccardo University of Catania Department of Electrical Electronic and Computer Engineering Italy Italy

ISBN: (纸本)9798350362244

The integration of 5G New Radio (NR) into the manufacturing industry stands as a pivotal aspect of the Industrial Internet of Things (IIoT) paradigm, mitigating constraints posed by traditional wired communication technologies in terms of flexibility, mobility, and adaptability. However, ensuring comparable performance levels presents challenges in the scheduling design of 5G NR networks, particularly due to the emphasis on uplink transmissions within industrial applications. Indeed, current uplink schedulers proposed by the 3rd Generation Partnership Project (3GPP) exhibit performance trade-offs, forcing the network to acquire knowledge of uplink traffic and faltering in the presence of heterogeneous traffic sources, commonplace in industrial environments. In this paper, we thus propose a Reinforcement Learning (RL)-based approach that dynamically assigns users to the most suitable uplink scheduler without prior or acquired knowledge of the different traffic patterns. Through 3GPP-compliant network simulations, we demonstrate the effectiveness of our approach in optimizing network performance while addressing the complexities of heterogeneous IIoT environments and maintaining standard compliance. © 2024 IEEE.

关键词： 5G mobile communication systems

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