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2023 IEEE PES Innovative Smart Grid Technologies Europe, ISGT EUROPE 2023

作者： Hokmabad, Hossein Nourollahi Husev, Oleksandr Vinnikov, Dmitri Belikov, Juri Petlenkov, Eduard Department of Electrical Power Engineering and Mechatronics Tallinn University of Technology Tallinn Estonia Department of Software Science Tallinn University of Technology Tallinn Estonia Department of Computer Systems Tallinn University of Technology Tallinn Estonia

ISBN: (纸本)9798350396782

Recently, global photovoltaic (PV) system installations have surged. Precise forecasting is vital for their grid integration and carbon emission cuts. However, due to fluctuating solar radiation, predicting PV output is difficult. Machine learning models, notably Long Short-Term Memory (LSTM) networks, offer a solution. This study presents a novel framework using a boosted recursive Light Gradient Boosting Machine (LightGBM)-LSTM network to forecast daily PV output at hourly intervals. Conducted in Northern Europe—a region with significant solar radiation variability—the models trained on meteorological and historical data showed a 12% improvement in RMSE, a 13% reduction in MAPE, and a 5% increase in the R2 score compared to standalone LSTM models. © 2023 IEEE.

关键词： boosting ensemble method LightGBM LSTM numerical weather prediction Solar power forecasting

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Boosting Monolayer Transition Metal Dichalcogenides Growth by Hydrogen-Free Ramping during Chemical Vapor Deposition

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Nano Letters 2024年第27期24卷 8277-8286页

作者： Liu, Hongwei Zhang, Tianyi Wu, Peng Lee, Hae Won Liu, Zhenjing Tang, Tsz Wing Tang, Shin-Yi Kang, Ting Park, Ji-Hoon Wang, Jun Zhang, Kenan Zheng, Xudong Peng, Yu-Ren Chueh, Yu-Lun Liu, Yuan Palacios, Tomás Kong, Jing Luo, Zhengtang Department of Chemical and Biological Engineering Guangdong-Hong Kong-Macao Joint Laboratory for Intelligent Micro-Nano Optoelectronic Technology William Mong Institute of Nano Science and Technology and Hong Kong Branch of Chinese National Engineering Research Center for Tissue Restoration and Reconstruction The Hong Kong University of Science and Technology Kowloon999077 Hong Kong Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States Department of Materials Science and Engineering Massachusetts Institute of Technology CambridgeMA02139 United States Department of Materials Science and Engineering National Tsing-Hua University Hsinchu30013 Taiwan Department of Materials Science and Engineering Korea University Seoul02841 Korea Republic of Key Laboratory for Micro-Nano Optoelectronic Devices of Ministry of Education School of Physics and Electronics Hunan University Changsha410082 China

The controlled vapor-phase synthesis of two-dimensional (2D) transition metal dichalcogenides (TMDs) is essential for functional applications. While chemical vapor deposition (CVD) techniques have been successful for transition metal sulfides, extending these methods to selenides and tellurides often faces challenges due to uncertain roles of hydrogen (H2) in their synthesis. Using CVD growth of MoSe2 as an example, this study illustrates the role of a H2-free environment during temperature ramping in suppressing the reduction of MoO3, which promotes effective vaporization and selenization of the Mo precursor to form MoSe2 monolayers with excellent crystal quality. As-synthesized MoSe2 monolayer-based field-effect transistors show excellent carrier mobility of up to 20.9 cm2/(V·s) with an on-off ratio of 7 × 107. This approach can be extended to other TMDs, such as WSe2, MoTe2, and MoSe2/WSe2 in-plane heterostructures. Our work provides a rational and facile approach to reproducibly synthesize high-quality TMD monolayers, facilitating their translation from laboratory to manufacturing. © 2024 American Chemical Society.

关键词： Monolayers

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Proceedings of the 2023 IEEE Open Conference of electrical, Electronic and Information sciences (eStream' 2023): Organizers Foreword 10

Proceedings of the 2023 IEEE Open Conference of Electrical, ...

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10th IEEE Open Conference of electrical, Electronic and Information sciences, eStream 2023

作者： Navakauskas, Dalius Paulikas, Šarunas Sledevič, Tomyslav Udris, Dainius VILNIUS TECH Department of Electronic Systems Vilnius10223 Lithuania VILNIUS TECH Department of Computer Science and Communications Technologies Vilnius10223 Lithuania VILNIUS TECH Department of Electrical Engineering Vilnius10223 Lithuania

ISBN: (纸本)9798350303834

We are very glad to welcome our colleagues - young scientists, researchers and practitioners to the 10-th IEEE Open Conference of electrical, Electronic and Information sciences (eStream' 2023), held in Vilnius Gediminas Technical University (VILNIUS TECH), Vilnius, Lithuania, on 27 April 2023. The eStream conferences aim to disseminate the research achievements between worldwide groups of scientists and engineers working in different areas of science to reach more tight relationships and generate new ideas for joint projects or other means of collaboration. © 2023 IEEE.

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NS3-Based Communication Network Modeling for Multi-Microgrid systems: Design and Evaluation

NS3-Based Communication Network Modeling for Multi-Microgrid...

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IEEE Green Technologies Conference (IEEE-Green)

作者： Ola Ali Osama A. Mohammed Department of Electrical and Computer Engineering Energy Systems Research Laboratory Florida International University Miami FL USA

ISBN: (数字)9798331520182

ISBN: (纸本)9798331520199

This paper presents a communication emulation model for enhancing the efficiency of multi-microgrid (MMG) networks, employing Network Simulator 3 (ns3). MMG systems require robust communication frameworks for coordination, particularly under varying traffic conditions. The introduced model accommodates multiple local area networks (LANs) that support efficient communication across multiple autonomous AC microgrids. The developed model facilitates seamless bidirectional information exchange between the microgrids' local controllers and the MMG control center (MMGCC), employing TCP/IP protocol to ensure high data transmission integrity and low latency. A detailed design in C++ is demonstrated, including the configuration of the communication nodes, topology, communication links, and quality of service (QoS) analysis. The network performance is rigorously assessed across low and high traffic conditions, with performance metrics such as throughput, delay, and percentage packet loss at each node. Results confirm the effectiveness of the introduced model in sustaining minimal packet loss, high throughput, and low delays under dynamic operating scenarios. These findings establish the developed model as a viable solution for meeting the real-time communication requirements of MMG energy management systems.

关键词： Emulation Packet loss TCPIP Quality of service Microgrids C++ languages Throughput Real-time systems Delays Load modeling

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Observer-Based Control of Second-Order Multi-vehicle systems in Bearing-Persistently Exciting Formations 63

Observer-Based Control of Second-Order Multi-vehicle Systems...

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63rd IEEE Conference on Decision and Control, CDC 2024

作者： Tang, Zhiqi Fidan, Baris Johansson, Karl H. Martensson, Jonas Hamel, Tarek Kth Royal Institute of Technology Division of Decision and Control Systems School of Electrical Engineering and Computer Science StockholmSE-10044 Sweden University of Waterloo Mechanical and Mechatronics Engineering Department ON Canada I3S-UCA Cnrs France

ISBN: (纸本)9798350316339

This paper proposes an observer-based formation tracking control approach for multi-vehicle systems with second-order motion dynamics, assuming that vehicles' relative or global position and velocity measurements are unavailable. It is assumed that all vehicles are equipped with sensors capable of sensing the bearings relative to neighboring vehicles and only one leader vehicle has access to its global position. Each vehicle estimates its absolute position and velocity using relative bearing measurements and the estimates of neighboring vehicles received over a communication network. A distributed observer-based controller is designed, relying only on bearing and acceleration measurements. This work further explores the concept of the Bearing Persistently Exciting (BPE) formation by proposing new algorithms for bearing-based localization and state estimation of second-order systems in centralized and decentralized manners. It also examines conditions on the desired formation to guarantee the exponential stability of distributed observer-based formation tracking controllers. In support of our theoretical results, some simulation results are presented to illustrate the performance of the proposed observers as well as the observer-based tracking controllers. © 2024 IEEE.

关键词： Acceleration measurement

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Entropic and Operational Characterizations of Dynamic Quantum Resources

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IEEE Transactions on Information Theory 2025年

作者： Ji, Kaiyuan Chitambar, Eric Cornell University School of Electrical and Computer Engineering IthacaNY14850 United States University of Illinois at Urbana-Champaign Coordinated Science Laboratory Department of Electrical and Computer Engineering UrbanaIL61801 United States

We offer new methods for characterizing general closed and convex quantum resource theories, including dynamic ones, based on entropic concepts and operational tasks. We propose a resource-theoretic generalization of the quantum conditional min-entropy, termed the free conditional min-entropy (FCME), in the sense that it quantifies an observer's "subjective"degree of uncertainty about a quantum system given that the observer's information processing is limited to free operations of the resource theory. Using this generalized concept, we provide a complete set of entropic conditions for free convertibility between quantum states or channels in any closed and convex quantum resource theory. We also derive an information-theoretic interpretation for the resource global robustness of a state or a channel in terms of a mutual-information-like quantity based on the FCME. Apart from this entropic approach, we characterize dynamic resources by also analyzing their performance in operational tasks. We construct operationally meaningful and complete sets of resource monotones with these tasks, which enable faithful tests of free convertibility between quantum channels. Finally, we show that every well-defined robustness-based measure of a channel can be interpreted as an operational advantage of the channel over free channels in a communication task. © 1963-2012 IEEE.

关键词： Quantum channel

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Resilient Operation of DC Standalone Microgrids: Experimental Validation of Hybrid RNN-PI Control for Pulse Load Management

Resilient Operation of DC Standalone Microgrids: Experimenta...

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IEEE Green Technologies Conference (IEEE-Green)

作者： Ahmed Aghmadi Osama A. Mohammed Department of Electrical and Computer Engineering Energy Systems Research Laboratory Florida International University Miami FL USA

ISBN: (数字)9798331520182

ISBN: (纸本)9798331520199

Effective energy storage system (ESS) management is critical for enhancing the performance of standalone DC microgrids, particularly when integrating renewable energy sources such as photovoltaic (PV) or wind systems. This research describes a new hybrid control technique to improve DC microgrid operations' efficiency and resiliency, especially when handling critical loads. This research presents a hybrid closed-loop control technique that uses Recurrent Neural Networks (RNNs) and Proportional-Integral (PI) controllers to address the complex issues of dynamic load situations and transient disturbances. The RNN evaluates voltage errors to generate accurate reference currents, which the PI controllers then adjust to improve the performance of the bidirectional converter. Unlike standard PI-PI controls, our hybrid approach is particularly effective at regulating pulsed power loads (PPLs) and enhancing system response to transitory situations. The experimental results show that the RNN-PI control scheme significantly improves voltage regulation and transient responsiveness, exceeding conventional performance and resilience techniques. This approach provides a convincing solution for enhancing microgrid systems' stability and efficiency in various real-world applications.

关键词： Renewable energy sources Recurrent neural networks PI control Voltage fluctuations Microgrids Robustness Voltage control Transient analysis Standards Resilience

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RodNet: An Advanced Multidomain Object Detection Approach Using Feature Transformation With Generative Adversarial Networks

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IEEE Sensors Journal 2023年第15期23卷 17531-17540页

作者： Jaw, Da-Wei Huang, Shih-Chia Lin, I-Chuan Zhang, Cheng Huang, Ching-Chun Kuo, Sy-Yen National Taiwan University Department of Electrical Engineering Taipei106 Taiwan National Taipei University of Technology Department of Electronic Engineering Taipei106 Taiwan Ibaraki University College of Engineering Department of Mechanical Systems Engineering Mito Ibaraki310-8512 Japan National Yang Ming Chiao Tung University Department of Computer Science Hsinchu30010 Taiwan

Advanced object detection (OD) techniques have been widely studied in recent years and have been successfully applied in real-world applications. However, existing algorithms may struggle with nighttime image detection, especially in low-luminance conditions. Researchers have attempted to overcome this issue by collecting large amounts of multidomain data, but performance remains poor because these methods train images from both low- and sufficient-luminance domains without a specific training policy. In this work, we present a lightweight framework for multidomain OD using feature domain transformation with generative adversarial networks (GANs). The proposed GAN framework trains a generator network to transform features from the low-luminance domain to a sufficient-luminance domain, making the discriminator networks unable to distinguish whether the features were generated from a low-luminance or a normal image and thus achieving luminance-invariant feature extraction. To preserve semantic meaning in the transformed features, a training policy has been introduced for OD and feature transformation in various domains. The proposed method achieves the state-of-the-art performance with a 9.95 improvement in average precision without incurring additional computational costs. © 2001-2012 IEEE.

关键词： Feature extraction

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An Isomerism Learning Model to Solve Time-Varying Problems Through Intelligent Collaboration

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IEEE/CAA Journal of Automatica Sinica 2023年第8期10卷 1772-1774页

作者： Zhihao Hao Guancheng Wang Bob Zhang Leyuan Fang Haisheng Li the Department of Computer and Information Science University of MacaoMacao 999078China the School of Data Science the Chinese University of Hong KongShenzhen 518172 Shenzhen Institute of Artificial Intelligence and Robotics for Society Shenzhen 518000 China Industrial Control Systems Cyber Emergency Response Team Beijing 100040China IEEE the College of Electrical and Information Engineering Hunan UniversityChangsha 410082 the Peng Cheng Laboratory Shenzhen 518000China the Beijing Key Laboratory of Big Data Technology for Food Safety Beijing Technology and Business UniversityBeijing 100048 the School of Computer Science and Engineering Beijing Technology and Business UniversityBeijing 100048China

Dear Editor,This letter deals with a solution for time-varying problems using an intelligent computational(IC)algorithm driven by a novel decentralized machine learning approach called isomerism *** order to meet the challenges of the model’s privacy and security brought by traditional centralized learning models,a private permissioned blockchain is utilized to decentralize the model in order to achieve an effective coordination,thereby ensuring the credibility of the overall model without exposing the specific parameters and solution process.

关键词： ism thereby letter

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Energy Storage and Forecasting Error Impact Analysis in Photovoltaic Equipped Residential Nano-Grids 17

Energy Storage and Forecasting Error Impact Analysis in Phot...

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17th IEEE International Conference on Compatibility, Power Electronics and Power engineering, CPE-POWERENG 2023

作者： Hokmabad, Hossein Nourollahi Husev, Oleksandr Belikov, Juri Vinnikov, Dmitri Petlenkov, Eduard Tallinn University of Technology Department of Electrical Power Engineering and Mechatronics Tallinn Estonia Tallinn University of Technology Department of Software Science Tallinn Estonia Tallinn University of Technology Department of Computer Systems Tallinn Estonia

ISBN: (纸本)9798350300048

Battery energy storage systems (BESS) enable many applications for photovoltaic (PV) equipped nano-grids. Stored excessive energy is utilized for energy arbitrage, demand response during blackouts, and peak shaving. This technology helped utility service providers deal with the duck-curve-effect and intermittency of renewable energy systems. In this paper, we investigate the benefits of using energy storage systems in PV nano-grids for residential sectors and evaluate the relationship between battery presence and system performance. We also analyze the effects of battery degradation on energy independence and self-sufficiency and investigate the relationship between simple payback time and state of health (SoH) levels of nano-grid components. Additionally, we propose a simple rule-based energy supervision strategy and evaluate its performance under various forecasting error levels, highlighting the importance of high-performance forecasting methods for proper energy management systems. Our contributions will help select and optimize PV-battery solutions and energy management algorithms to achieve the highest benefit and minimize investment risks. © 2023 IEEE.

关键词： Energy management systems

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