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Recent advances on data-driven services for smart energy systems optimization and pro-active management

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Recent advances on data-driven services for smart energy sys...

Metrology for Living Environment (MetroLivEn), IEEE International Workshop on

作者： Tancredi Testasecca Marilena Lazzaro Elissaios Sarmas Stathis Stamatopoulos Dipartimento di Ingegneria Università degli Studi di Palermo Palermo Italy Research & Innovation Department Engineering Ingegneria Informatica S.p.A. Palermo Italy Decision Support Systems Laboratory School of Electrical and Computer Engineering National Technical University of Athens Athens Greece

Optimization and proactive management of energy systems are crucial for achieving sustainability, efficiency and resilience in future smart energy networks. Data-driven approaches offer promising solutions for tackling the complex and dynamic challenges of energy systems, such as uncertainty, variability, and heterogeneity. Meanwhile, recent advances in decreasing hardware costs and improving data accessibility have allowed for the collection of high-quality data, leading to the development of more accurate and robust data-driven models of different energy systems. In this study, a comprehensive overview of current and future trends in data-driven optimization for smart energy systems is presented. After introducing the motivation and the background of this research field, the potential applications and benefits of optimization in various domains is discussed, such as electric vehicles charge, district heating networks and energy districts. Subsequently this review focuses on different methods and techniques for data-driven optimization and proactive management, ranging from scientific models to machine learning algorithms. Finally, the novel European project, DigiBUILD, is introduced, where different case studies are tested in several pilots, including electric vehicle charging management for increasing renewable energy source consumption, district heating network operative costs optimization and building energy and comfort management.

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Codebook Design for Large Reconfigurable Refractive Surface Enabled Holographic MIMO systems

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Codebook Design for Large Reconfigurable Refractive Surface ...

GLOBECOM 2022 - 2022 IEEE Global Communications Conference

作者： Yutong Zhang Boya Di Hongliang Zhang Lingyang Song State Key Laboratory of Advanced Optical Communication Systems and Networks School of Electronics Peking University Beijing China Department of Electrical and Computer Engineering Princeton University Princeton NJ USA

ISBN: (纸本)9781665435413

Holographic multiple-input multiple-output (HMI-MO) has recently motivated its potential use to handle the exponentially increasing data transmission demands by achieving a spatially continuous aperture. With densely-packed metamaterial elements, the reconfigurable refractive surfaces (RRSs) serving as antennas emerge to enable HMIMO. In this paper, we consider a multi-user system where an RRS is employed as the transmit antenna array at the base station (BS). To avoid the high overhead of acquiring perfect channel state information (CSI), a codebook and beam training mechanism is required to develop the beamforming scheme. Given the large physical dimension of the RRS, users are likely to distribute in both the near field and the far field of the BS, making the codebook design more difficult. To address this issue, we design a hybrid near-far field codebook which applies to all users in any location with low overhead. To further reduce the training overhead, each codeword is designed to cover multiple spatial areas, enabling a multi-user beam training mechanism which can be performed for all users simultaneously. Under a general setting including both the near-field and far-field users, simulation results show that the proposed scheme significantly reduces the overhead and achieves a higher sum rate compared to the state-of-the-art codebooks, which performs very close to that of the perfect CSI case.

关键词： Training Simulation Transmitting antennas Metamaterials MIMO Global communication Data communication

ERASE-Net: Efficient Segmentation Networks for Automotive Radar Signals

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arXiv 2022年

作者： Fang, Shihong Zhu, Haoran Bisla, Devansh Choromanska, Anna Ravindran, Satish Ren, Dongyin Wu, Ryan Learning Systems Laboratory Department of Electrical and Computer Engineering New York University 370 Jay Street NY United States NXP Semiconductors San JoseCA United States

Among various sensors for assisted and autonomous driving systems, automotive radar has been considered as a robust and low-cost solution even in adverse weather or lighting conditions. With the recent development of radar technologies and open-sourced annotated data sets, semantic segmentation with radar signals has become very promising. However, existing methods are either computationally expensive or discard significant amounts of valuable information from raw 3D radar signals by reducing them to 2D planes via averaging. In this work, we introduce ERASE-Net, an Efficient RAdar SEgmentation Network to segment the raw radar signals semantically. The core of our approach is the novel detect-then-segment method for raw radar signals. It first detects the center point of each object, then extracts a compact radar signal representation, and finally performs semantic segmentation. We show that our method can achieve superior performance on radar semantic segmentation task compared to the state-of-the-art (SOTA) technique. Furthermore, our approach requires up to 20× less computational resources. Finally, we show that the proposed ERASE-Net can be compressed by 40% without significant loss in performance, significantly more than the SOTA network, which makes it a more promising candidate for practical automotive applications. Copyright © 2022, The Authors. All rights reserved.

关键词： Semantics

Spontaneous Emergence of Multitasking Robotic Swarms

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Spontaneous Emergence of Multitasking Robotic Swarms

IEEE International Conference on Robotics and Biomimetics

作者： Ji Zhang Yiming Liang Shiqiang Zhu Tian Xiang Hongwei Zhu Jason Gu Wei Song Tiefeng Li Zhejiang Lab Hangzhou China Department of Electrical and Computer Engineering Dalhousie Universit Halifax Canada State Key Laboratory of Fluid Power and Mechatronic Systems Zhejiang University Hangzhou China

ISBN: (纸本)9781665481106

Robot swarms promise to replace humans in complex scenarios like resource exploration, environmental monitoring, and military missions. These complex scenarios require robots to be able to complete multiple tasks at the same time adaptively. From the point of view of statistical mechanics, the phenomenon of the multiply states of a given system is a kind of partial synchronization. Inspired by biological groups such as flocks of birds and schools of fish, we model the robots as self-propelled particles with Kuramoto-Sakaguchi like interactions. We uncover the state of the robot swarm can be manipulated using the phase lag of the Kuramoto-Sakaguchi like interactions. The system is partially synchronized at the edge between order and disorder, and the robots present two distinguished motion patterns, one is completely periodic movement, and the other one is chaos. This study provides new insights into the collaboration of robot swarms.

关键词： Analytical models Collaboration Multitasking Fish Topology Synchronization Environmental monitoring

Capacity Optimization of Hydrogen Buffer Tanks in Renewable Power to Ammonia (P2A) System

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Capacity Optimization of Hydrogen Buffer Tanks in Renewable ...

2020 IEEE Power and Energy Society General Meeting, PESGM 2020

作者： Li, Jiarong Lin, Jin Song, Yonghua Tsinghua University State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Beijing China State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Beijing China Department of Electrical Engineering Department of Electrical and Computer Engineering Beijing China

ISBN: (纸本)9781728155081

Power to hydrogen is a promising method to consume surplus renewable energy existing in the world. However, due to bottlenecks in hydrogen storage and transportation, converting hydrogen into ammonia which is a kind of hydrogen carrier with satisfied quality in storage and transportation is considered. Industrial ammonia synthesis reactors always work in constant conditions with constant flow rate of the feed gas, while hydrogen output of electrolyzers may vary sharply across renewable energy, thus hydrogen buffer tanks are required between electrolyzers and reactors to eliminate the fluctuation to some extent. The capacity of the buffer needs to be optimized due to relatively expensive cost of tanks, and the optimal capacity of the buffer actually depends on the operation flexibility of the reactor which is rarely discussed in existing literatures. This paper studies operation flexibility of the reactor first and establishes operation model of ammonia synthesis system under variable working conditions, on this basis the capacity optimization model is proposed and verified by a P2A system. At last the operation performance and the economy of P2A system are discussed, and case studies show that about 24% of total investment cost can be reduced with the consideration of operation flexibility of the reactor. © 2020 IEEE.

关键词： Ammonia

Transformer-based Hand Gesture Recognition via High-Density EMG Signals: From Instantaneous Recognition to Fusion of Motor Unit Spike Trains

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arXiv 2022年

作者： Montazerin, Mansooreh Rahimian, Elahe Naderkhani, Farnoosh Atashzar, S. Farokh Yanushkevich, Svetlana Mohammadi, Arash Department of Electrical and Computer Engineering Concordia University MontrealQC Canada Concordia Institute for Information Systems Engineering Concordia University MontrealQC Canada Departments of Electrical & Computer Engineering and Mechanical & Aerospace Engineering New YorkNY10003 United States New YorkNY10003 United States Department of Electrical and Software Engineering Biometric Technologies Laboratory Schulich School of Engineering University of Calgary CalgaryAB Canada

Designing efficient and labor-saving prosthetic hands requires powerful hand gesture recognition algorithms that can achieve high accuracy with limited complexity and latency. In this context, the paper proposes a compact deep learning framework referred to as the CT-HGR, which employs a vision transformer network to conduct hand gesture recognition using high-density sEMG (HD-sEMG) signals. Taking advantage of the attention mechanism, which is incorporated into the transformer architectures, our proposed CT-HGR framework overcomes major constraints associated with most of the existing deep learning models such as model complexity;requiring feature engineering;inability to consider both temporal and spatial information of HD-sEMG signals, and;requiring a large number of training samples. The attention mechanism in the proposed model identifies similarities among different data segments with a greater capacity for parallel computations and addresses the memory limitation problems while dealing with inputs of large sequence lengths. CT-HGR can be trained from scratch without any need for transfer learning and can simultaneously extract both temporal and spatial features of HD-sEMG data. Additionally, the CT-HGR framework can perform instantaneous recognition using sEMG image spatially composed from HD-sEMG signals. A variant of the CT-HGR is also designed to incorporate microscopic neural drive information in the form of Motor Unit Spike Trains (MUSTs) extracted from HD-sEMG signals using Blind Source Separation (BSS). This variant is combined with its baseline version via a hybrid architecture to evaluate potentials of fusing macroscopic and microscopic neural drive information. The utilized HD-sEMG dataset involves 128 electrodes that collect the signals related to 65 isometric hand gestures of 20 subjects. The proposed CT-HGR framework is applied to 31.25, 62.5, 125, 250 ms window sizes of the above-mentioned dataset utilizing 32, 64, 128 electrode channels. The av

关键词： Electrodes

Distributed Prescribed-Time Observer for Nonlinear systems in Block-Triangular Form

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arXiv 2025年

作者： de Heij, Vincent Niazi, M.B. Umar Johansson, Karl H. Ahmed, Saeed Faculty of Science and Engineering University of Groningen Groningen9747 AG Netherlands Division of Decision and Control Systems Digital Futures KTH Royal Institute of Technology StockholmSE-100 44 Sweden Division of Decision and Control Systems Digital Futures KTH Royal Institute of Technology StockholmSE-100 44 Sweden Laboratory for Information and Decision Systems Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States

This paper proposes a distributed prescribed-time observer for nonlinear systems representable in a block-triangular observable canonical form. Using a weighted average of neighbor estimates exchanged over a strongly connected digraph, each observer estimates the system state despite the limited observability of local sensor measurements. The proposed design guarantees that distributed state estimation errors converge to zero at a user-specified convergence time, irrespective of observers’ initial conditions. To achieve this prescribed-time convergence, distributed observers implement time-varying local output injection gains that monotonically increase and approach infinity at the prescribed time. The theoretical convergence is rigorously proven and validated through numerical simulations, where some implementation issues due to increasing gains have also been clarified. Copyright © 2025, The Authors. All rights reserved.

关键词： Digital arithmetic

Secure Communication of Active RIS Assisted NOMA Networks

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arXiv 2024年

作者： Li, Xuehua Pei, Yingjie Yue, Xinwei Liu, Yuanwei Ding, Zhiguo The Key Laboratory of Information and Communication Systems Ministry of Information Industry The Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science and Technology University Beijing100101 China The School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China The School of Electronic Engineering and Computer Science Queen Mary University of London LondonE1 4NS United Kingdom Department of Electrical Engineering and Computer Science Khalifa University Abu Dhabi United Arab Emirates

As a revolutionary technology, reconfigurable intelligent surface (RIS) has been deemed as an indispensable part of the 6th generation communications due to its inherent ability to regulate the wireless channels. However, passive RIS (PRIS) still suffers from some pressing issues, one of which is that the fading of the entire reflection link is proportional to the product of the distances from the base station to the PRIS and from the PRIS to the users, i.e., the productive attenuation. To tackle this problem, active RIS (ARIS) has been proposed to reconfigure the wireless propagation condition and alleviate the productive attenuation. In this paper, we investigate the physical layer security of the ARIS assisted non-orthogonal multiple access (NOMA) networks with the attendance of external and internal eavesdroppers. To be specific, the closed-form expressions of secrecy outage probability (SOP) and secrecy system throughput are derived by invoking both imperfect successive interference cancellation (ipSIC) and perfect SIC. The secrecy diversity orders of legitimate users are obtained at high signal-to-noise ratios. Numerical results are presented to verify the accuracy of the theoretical expressions and indicate that: i) The SOP of ARIS assisted NOMA networks exceeds that of PRIS-NOMA, ARIS/PRIS-assisted orthogonal multiple access (OMA);ii) Due to the balance between the thermal noise and residual interference, introducing excess reconfigurable elements at ARIS is not helpful to reduce the SOP;and iii) The secrecy throughput performance of ARIS-NOMA networks outperforms that of PRIS-NOMA and ARIS/PRIS-OMA networks. Copyright © 2024, The Authors. All rights reserved.

关键词： Signal to noise ratio

Sliding Mode Control for a DC-DC Buck Converter Feeding a Constant Power Load: A Practical Implementation

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Sliding Mode Control for a DC-DC Buck Converter Feeding a Co...

Advanced Technology in Electronic and electrical engineering (ICATEEE), International Conference of

作者： Khalil Louassaa Aissa Chouder Mahdi Boukerdja Abdelhafid Cherifi Ali Aillane Electrical Engineering Department Electrical Engineering Laboratory University of M’sila M’sila Algeria Materials and Electronic Systems Laboratory University of Bordj Bou Arreridj Bordj Bou Arreridj Algeria Laboratory of Sciences and Techniques of Automatic Control and Computer Engineering (LabSTA) National School of Engineering of Sfax (ENIS) University of Sfax Sfax Tunisia

DC microgrids have gained in popularity in recent years due to features such as greater reliability, high efficiency, and control simplicity. Constant power loads (CPLs), on the other hand, are a problem and an effective cause of instability in DC MGs. To address the aforementioned issue, this paper discusses the stabilization of a buck power converter that supplies CPL via a regulated boost power converter. A robust sliding mode control is proposed, which stabilizes the output voltage and ensures the CPL's required power. The system is investigated in the context of external perturbations such as fluctuating input voltage and sudden change in the CPL. The robustness and efficacy of the proposed method have been demonstrated to confirm the system's overall stability. Simulation and experimentation are employed to verify the provided controller. The results verify the suggested controller's superiority.

关键词： Damping Voltage measurement Perturbation methods Microgrids Stability analysis Robustness Steady-state