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2024 IEEE PES Innovative Smart Grid Technologies Europe Conference, ISGT EUROPE 2024

作者： Dindar, Burak Saner, Can Berk Polat, Dogukan Yigit Çakmak, Huseyin Kemâl Hagenmeyer, Veit Institute for Automation and Applied Informatics Karlsruhe Institute of Technology Germany National University of Singapore Department of Electrical and Computer Engineering Singapore National University of Singapore School of Computing Singapore

ISBN: (纸本)9789531842976

In order to achieve the goal of a carbon-neutral power system, significant changes to the power grid are underway, necessitating enhanced interoperability between Transmission System Operators (TSOs) and Distribution System Operators (DSOs) for effective grid operation, particularly in light of the growing number of distributed generators (DGs). Data privacy concerns, however, complicate decision-making processes, particularly when integrating DGs into system-wide dispatch decisions. In this paper, we propose a machine-learning (ML)-based method to incorporate DGs located within the distribution system (DS) into dispatch decisions, adhering to data privacy by mitigating the exchange of sensitive data, such as system topology and demand profiles, between TSOs and DSOs. The methodology involves training three ML models to represent the behavior of the DS, thereby replacing the standard power flow model that contains sensitive information. Notably, we utilize a novel tailored neural network (NN) architecture to enhance computational efficiency in mapping the feasible region of the DS. Additionally, we employ open-source data to construct the Baden-Wü rttemberg (Germany) electricity grid, allowing to test our method not only on standard systems but also on a model that more accurately represents real-world power systems. The numerical case studies verify that the proposed method achieves results comparable to standard AC optimal power flow (AC-OPF) in both cost-optimality and computational time. © 2024 IEEE.

关键词： Differential privacy

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A novel deep domain-adversarial method based on DRN-DATL for rolling bearing 43

A novel deep domain-adversarial method based on DRN-DATL for...

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43rd Chinese Control Conference, CCC 2024

作者： Li, Zhuorui Wang, Xiaodong Ma, Bao Kunming University of Science and Technology Faculty of Information Engineering and Automation Kunming650500 China Yunnan University Yunnan Key Laboratory of Intelligent Systems and Computing Kunming650500 China

ISBN: (纸本)9789887581581

In recent years, a variety of rolling bearing fault diagnosis methods based on deep learning has become an emerging research orientation. However, there is still a gap between the existing diagnostic model and the practical application, i.e., 1) due to the variability of working conditions, the domain shift problem between source domain and the target domain have led to the obvious degradation of the diagnostic performance. 2) It is time-consuming and expensive to label a mass of monitoring data in practical situation. To address this problem, a domain-adversarial transfer learning method based on deep residual network (DRN-DATL) for rolling bearing fault diagnosis is proposed. Firstly, DRN is designed to extract features from raw vibration signal, which can avoid gradient problems. Then, the APReLU activation function is adopted to improved diagnostic accuracy under different working conditions. Meanwhile, domain-adversarial training is utilized to minimize distribution differences between source domain and target domain. Finally, seven comparison methods are selected for systematic analysis, and the results show that the proposed method can effectively improve the overall performance of the diagnosis model, which has achieved higher classification accuracy. © 2024 Technical Committee on Control Theory, Chinese Association of automation.

关键词： Adversarial machine learning

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Simplified Control Strategies for Power Converters in a Grid-Connected Hybrid DC-AC Microgrid

Simplified Control Strategies for Power Converters in a Grid...

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2023 International Conference on Future Energy Solutions, FES 2023

作者： Busarello, Tiago Davi Curi Simões, Marcelo Godoy Laaksonen, Hannu Kauhaniemi, Kimmo Federal University of Santa Catarina Department of Control Automation and Computing Engineering Blumenau Brazil University of Vaasa School of Technology and Innovations Vaasa Finland

ISBN: (纸本)9798350332308

Many typical converter control strategies used in microgrids are complex or require modifications in the power structure. The complexities are due coupling effects among controllers and time-delay caused in exchanging information in the system. This paper proposes simplified control strategies for power converters in a grid-connected hybrid DC-AC microgrid, aiming to ensure precise voltage and current regulation. The used controllers are proportional-resonant, integral-double-lead, proportional-integral and single integral controller. In this paper, the methodology for tuning each controller is carefully described in detail and recommendation for choosing their bandwidth is given. Then, the designed controllers are discretized through the Backward-Euler approximation. The power converters of the microgrid are an inverter, a Buck, a Boost and a bidirectional DC-DC. A case study is conducted through simulations with Matlab/Simulink. Results show that the controlled variables follow their reference signals with negligible steady-state error, proving the efficacy of the simplified control strategies and allowing an stable operation of the microgrid. © 2023 IEEE.

关键词： Controllers

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Sensorless Synchronization Method for a Grid-Side Converter with an LCL Filter Based on a Sliding Mode Observer and Discontinuous Operating Mode

Sensorless Synchronization Method for a Grid-Side Converter ...

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2022 International Conference on Electrical Machines, ICEM 2022

作者： Jukić, Filip Pravica, Luka Stipetić, Stjepan University of Zagreb Faculty of Electrical Engineering and Computing Department of Electric Machines Drives and Automation Croatia

ISBN: (数字)9781665414326

ISBN: (纸本)9781665414326

When the grid-side converter (GSC) is switched on, a large inrush current may occur if the synchronization between the grid and the GSC is not performed well. Hence, a grid voltage and GSC output voltage vectors must be synchronized before the GSC is switched on. This study proposes a novel sensorless synchronization method based on discontinuous currents induced by the grid voltage after applying a series of controlled short circuits to the GSC terminals. Grid voltage angle is estimated using sampled current, a discrete sliding mode observer, and a double generalized second-order integrator with frequency locked loop in both discontinuous and continuous mode. The proposed method ensures the proper synchronization and GSC operation in the continuous operating mode under load conditions. The effectiveness of the proposed method is verified by simulations in Plexim PLECS. © 2022 IEEE.

关键词： Synchronization

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A Unified Arbitrary Style Transfer Framework via Adaptive Contrastive Learning

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ACM Transactions on Graphics 2023年第5期42卷 1-16页

作者： Zhang, Yuxin Tang, Fan Dong, Weiming Huang, Haibin Ma, Chongyang Lee, Tong-Yee Xu, Changsheng MAIS Institute of Automation China and School of Artificial Intelligence CAS UCAS China Institute Of Computing Technology CAS China Kuaishou Technology China Department of Computer Science and Information Engineering National Cheng-Kung University Taiwan

This work presents Unified Contrastive Arbitrary Style Transfer (UCAST), a novel style representation learning and transfer framework, that can fit in most existing arbitrary image style transfer models, such as CNN-based, ViT-based, and flow-based methods. As the key component in image style transfer tasks, a suitable style representation is essential to achieve satisfactory results. Existing approaches based on deep neural networks typically use second-order statistics to generate the output. However, these hand-crafted features computed from a single image cannot leverage style information sufficiently, which leads to artifacts such as local distortions and style inconsistency. To address these issues, we learn style representation directly from a large number of images based on contrastive learning by considering the relationships between specific styles and the holistic style distribution. Specifically, we present an adaptive contrastive learning scheme for style transfer by introducing an input-dependent temperature. Our framework consists of three key components: a parallel contrastive learning scheme for style representation and transfer, a domain enhancement (DE) module for effective learning of style distribution, and a generative network for style transfer. Qualitative and quantitative evaluations show the results of our approach are superior to those obtained via state-of-the-art methods. The code is available at https://***/zyxElsa/CAST_pytorch. © 2023 Copyright held by the owner/author(s).

关键词： Deep neural networks

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Zero Current Detection Circuit based on Saturable Transformer Application in GaN based DC-DC Converter with Triple-Mode Switching 64

Zero Current Detection Circuit based on Saturable Transforme...

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64th IEEE Annual International Scientific Conference on Power and Electrical engineering of Riga Technical University, RTUCON 2023

作者： Kroics, Kaspars Gaspersons, Kristians Makar, Martin Riga Technical University Institute of Industrial Electronics and Electrical Engineering Riga Latvia University of Zagreb Faculty of Electrical Engineering and Computing Department of Electric Machines Drives and Automation Zagreb Croatia

ISBN: (纸本)9798350317732

This paper analyzes application of saturable transformer for zero current detection in GaN based converter at a switching frequency above 100 kilohertz. The design of the transformer is discussed in a simplified way, development of experimental prototype of the transformer has been given. Zero current detection (ZCD) has been tested on experimental prototype of DC-DC converter. Delay times introduced by the transformer, detection circuit and digital control system have been analyzed. The efficiency of the converter by introducing triple-mode switching with ZCD circuit has been investigated. The results show that the summary delay is at least 250 nanoseconds and at such frequencies the core heats up significantly and lowers efficiency which limits the application of the circuit for switching frequencies above 250 kilohertz. © 2023 IEEE.

关键词： DC-DC converters

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Bioinspired Polarized Skylight Orientation Determination Artificial Neural Network

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Journal of Bionic engineering 2023年第3期20卷 1141-1152页

作者： Huaju Liang Hongyang Bai Ke Hu Xinbo Lv School of Energy and Power Engineering Nanjing University of Science and TechnologyNanjing210094China Neuromorphic Computing Laboratory China Nanhu Academy of Electronics and Information TechnologyJiaxing314001China Guidance Radar General Department Xi’an Electronic Engineering Research InstituteXi’an710100China School of Automation Nanjing University of Science and TechnologyNanjing210094China

This paper proposes an artificial neural network to determine orientation using polarized skylight. This neural network has specific dilated convolution, which can extract light intensity information of different polarization directions. Then, the degree of polarization (DOP) and angle of polarization (AOP) are directly extracted in the network. In addition, the exponential function encoding of orientation is designed as the network output, which can better reflect the insect’s encoding of polarization information and improve the accuracy of orientation determination. Finally, training and testing were conducted on a public polarized skylight navigation dataset, and the experimental results proved the stability and effectiveness of the network.

关键词： Polarized light navigation Orientation determination Artificial neural network

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On Measures Resulting from the Choquet Integration 20th

On Measures Resulting from the Choquet Integration

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20th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2024

作者： Ontkovičová, Zuzana Torra, Vicenç Department of Computing Science Umeå University Umeå Sweden Institute of Information Engineering Automation and Mathematics Faculty of Chemical and Food Technology Slovak University of Technology in Bratislava Bratislava Slovakia

ISBN: (纸本)9783031739996

In this paper, we study measures arising as a result of the Choquet integration with respect to a particular class of measures. The initial insight is provided with several classes of additive and fuzzy measures. It can be seen that some classes are closed regarding the integration, e.g. probabilities, while some are not, such as distorted Lebesgue measures. Knowing both an integration measure and a resulting measure after the Choquet integration directly leads to a fuzzy analogue of the Radon-Nikodym derivatives. For them, a completely different possible approach to their existence is presented for a specific pair of measures. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Integration

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Sizing of Supercapacitor-based Energy Storage System for Elevator Applications 1

Sizing of Supercapacitor-based Energy Storage System for Ele...

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1st IEEE Industrial Electronics Society Annual On-Line Conference, ONCON 2022

作者： Godec, Damjan Pravica, Luka Kutija, Martina Makar, Martin Drives and Automation University of Zagreb Faculty of Electrical Engineering and Computing Department of Electric Machines Zagreb Croatia

ISBN: (纸本)9798350398069

Energy storage systems based on supercapacitors have become attractive solutions for improving elevator efficiency. Electrical energy is stored while the elevator drive is running in generator mode and used when needed. The energy storage system can also be charged in standby mode and used to reduce power peaks during start-up. Therefore, the energy storage system should be appropriately sized, which is not trivial since elevator usage is stochastic in nature. In this paper, the effect of energy storage system size on the efficiency of regenerative energy reuse is analyzed based on a measurement study. Measurements were performed for one week on faculty elevators under real conditions. The data obtained from the measurements were analyzed, and the results of the analysis of energy consumption, elevator starts, and potential energy savings were presented for all three elevators and the group. The elevator energy storage system was emulated in MATLAB with and without energy consumption balancing which is used to reduce peak power. The efficiency of regenerative energy reuse is calculated for a wide range of energy storage sizes, both with and without energy consumption balancing, for all individual elevators and the group. © 2022 IEEE.

关键词： Elevators

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Temperature distribution measurement of a battery pack's segment in a controlled testing environment 7

Temperature distribution measurement of a battery pack's seg...

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7th IEEE International Energy Conference, ENERGYCON 2022

作者： Premec, Antun Magas, Lovro Kristek, Hrvoje Vrazic, Mario University of Zagreb Drives and Automation Faculty of Electrical Engineering and Computing Department of Electric Machines Zagreb Croatia

ISBN: (纸本)9781665479820

To ensure operational safety and effective utilization of a battery pack it is important to determine temperature level and temperature distribution across its battery cells. This paper as the first of a series of papers, presents a battery pack segment ls7p testing environment for the purpose of measuring, not only the temperature of each cell, but also the voltage and current of the entire segment. The segment's cells are thoroughly monitored with three temperature sensors per cell to get the most accurate thermal distribution available. After developing and building the battery pack segment, it is placed in a temperature controlled test chamber, so it can be tested at different temperature levels. Future articles, will describe the segment's thermal image during charging and discharging. The goal of this paper is to present the accuracy of this testing environment, this must be done without charging or discharging the segment. It is necessary to measure and calculate the temperature sensor's characteristics, accuracy and offsets, as well as the monitoring system's sampling time, lag time and any lag time that is generated in the data processing step. With this information, certain measurement compensations can be made (if necessary) for future tests and experiments. © 2022 IEEE.

关键词： Temperature measurement

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