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International Conference on power Drives systems (ICPDS)

作者： Alecksey Anuchin Valentina Podzorova Mario Hirz Christoph Datlinger Lassi Aarniovuori Viktoriya Popova Galina Demidova Chen Hao Moscow Power Engineering Institute Moscow Russia Institute of Automotive Engineering Graz University of Technology Graz Austria Electrical Drives Laboratory LUT University Lappeenranta Finland Ogarev Mordova State University Saransk Russia Faculty of Control System and Robotics ITMO University Saint-Petersburg Russia School of Electrical and Power Engineering China University of Mining & Technology Xuzhou China

ISBN: (数字)9781728165387

ISBN: (纸本)9781728165394

The problem of torque pulsation and its stabilization by means of control is typical for switched reluctance drives. This drives usually controlled using hysteresis current regulators, which produce audible noise and torque ripple. The method of model predictive control with reduced integration step size was introduced in order to implement precise torque stabilization using pulse width modulation. Active thermal control was developed as well to increase the continuous output power of the drive. The developed control strategy was simulated and shows accurate torque regulation even when only few integration steps inside single PWM cycle are used for duty cycle evaluation. Active thermal control reduced the temperature of the hottest power module by 7.4%, which allows to increase the continuous output power of the drive.

关键词： Torque Multichip modules Switches Pulse width modulation control systems power generation Predictive control

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Unified resilience model using deep learning for assessing power system performance

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Heliyon 2025年第4期11卷 e42802页

作者： Artemchuk, Volodymyr Garbuz, Iurii Jamil Alsayaydeh, Jamil Abedalrahim Shkarupylo, Vadym Oliinyk, Andrii Bin Yusof, Mohd Faizal Herawan, Safarudin Gazali Department of Mathematical and Econometric Modelling G.E. Pukhov Institute for Modelling in Energy Engineering of the NAS of Ukraine Kyiv Ukraine Department of Environmental Protection Technologies and Radiation Safety Center for Information-analytical and Technical Support of Nuclear Power Facilities Monitoring of the NAS of Ukraine Kyiv Ukraine Department of Іnformation Systems in Economics Kyiv National Economic University Named After Vadym Hetman Kyiv Ukraine Department of Computerized Control System National Aviation University Kyiv Ukraine Department of Engineering Technology Fakulti Teknologi Dan Kejuruteraan Elektronik Dan Komputer (FTKEK) Universiti Teknikal Malaysia Melaka (UTeM) Melaka 76100 Malaysia Department of Computer Systems Networks and Cybersecurity of the National University of Life and Environmental Sciences of Ukraine Kyiv Ukraine Department of Software Tools Faculty of Computer Science and Technology Zaporizhzhia Polytechnic National University Zaporizhzhia Ukraine Research Section Faculty of Resilience Rabdan Academy Abu Dhabi United Arab Emirates Industrial Engineering Department Faculty of Engineering Bina Nusantara University Jakarta 11480 Indonesia

Energy resilience in renewable energy sources dissemination components such as batteries and inverters is crucial for achieving high operational fidelity. Resilience factors play a vital role in determining the performance of power systems, regardless of their operating environment and interruptions. This article introduces a Unified Resilience Model (URM) using Deep Learning (DL) to enhance power system performance. The proposed model analyzes environmental factors impacting the resilience of batteries and energy storage devices. This deep learning approach trains performance-impacting factors using previously known low resilience drain data. The learning output is utilized to augment various strengthening factors, thereby improving resilience. Drain mitigation and performance improvements are combined for direct impact verification. This process validates the model's fidelity in enhancing power system performance, with a specific focus on the impact of weather factors. © 2025 The Authors

关键词： Deep learning Energy resilience Fidelity Weather impact

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Development and test research of 10kv DC circuit breaker based on the principle of coupled negative voltage

Development and test research of 10kv DC circuit breaker bas...

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The 16th IET International Conference on AC and DC power Transmission (ACDC 2020)

作者： W. Li B. Liu F. Xiao H. Wang Y. Wang W. Xie Z. Yu Shandong Taikai High-Voltage Switchgear Co. Ltd. Tai’an China China Electric Power Research Institute Beijing China Tsinghua University State Key Laboratory of Control and Simulation of Power System and Generation Equipment (Department of Electrical Engineering Beijing China

With the increase of multi-terminal flexible DC distribution network projects, medium-voltage DC circuit breaker, as the key equipment to remove DC short-circuit fault, plays a key role in the operation reliability of the whole DC distribution network. In order to meet the engineering needs of DC distribution network, a 10kV hybrid DC circuit breaker based on the coupling negative voltage principle is developed in this paper. Firstly, the topology and working principle of the DC circuit breaker are introduced. Furthermore, the design scheme of key components including fast mechanical switch, power electronic switch and coupling negative voltage device is given. Finally, a 10kV hybrid DC circuit breaker prototype is developed and tested. The results show that the 10kV hybrid DC circuit breaker can break 15kA short circuit current within 2ms, and has the characteristics of low loss and high reliability.

关键词： circuit breakers short-circuit currents DC distribution systems power distribution faults power distribution reliability

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Oxygen Vacancy-Induced Spin Polarization of Tungsten Oxide Nanowires for Efficient Photocatalytic Reduction and Immobilization of Uranium(Vi) Under Simulated Solar Light

SSRN

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SSRN 2022年

作者： Yang, Xudong Li, Fan Liu, Wen Chen, Long Qi, Juanjuan Sun, Weiliang Duan, Tao Sun, Fengbin College of Environmental Sciences and Engineering The Key Laboratory of Water and Sediment Sciences Ministry of Education Peking University Beijing100871 China The Key Laboratory of Resources and Environmental System Optimization Ministry of Education College of Environmental Science and Engineering North China Electric Power University Beijing102206 China International Joint Laboratory for Regional Pollution Control Ministry of Education Peking University Beijing100871 China Department of Civil and Environmental Engineering Louisiana State University Baton RougeLA70803 United States State Key Laboratory of Environment-friendly Energy Materials Southwest University of Science and Technology Sichuan Mianyang621010 China Institute of Urban Meteorology China Meteorological Administration Beijing100089 China

Tungsten oxide nanowires (WO3-x) with rich oxygen vacancies (OVs) were fabricated through a facile hydrothermal method, which had both high adsorptive capability and photocatalytic activity. 95.1% of total U(VI) (C0 = 10 mg/L) was removed by WO3-x at pH 5, and 79.9% was transformed to U(IV) to achieve reductive immobilization after photocatalysis under simulated solar light. Band structure and optical characterizations indicated WO3-x had narrower band gap energy, but higher charger carrier separation and transfer rates compared with conventional WO3. Density functional theory (DFT) calculations further demonstrate the spin polarization state electrons of W 5d in WO3-x due to the construction of OVs, thus greatly inhibiting recombination of electron-hole pairs. In addition, the electron density increases in WO3-x and the photogenerated e– in the conduction band of WO3-x has higher reduction ability than WO3, leading to more efficient electron transfer from WO3-x to UO22+ after photo-excitation for U(VI) reduction. © 2022, The Authors. All rights reserved.

关键词： Tungsten compounds

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A Hierarchical Fine-Tuning Based Approach for Multi-label Text Classification

A Hierarchical Fine-Tuning Based Approach for Multi-label Te...

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IEEE International Conference on Cloud Computing and Big Data Analysis (ICCCBDA)

作者： Qiang Zhang Bo Chai Bochuan Song Jingpeng Zhao Artificial Intelligence on Electric Power System State Grid Corporation Joint Laboratory (GEIRI) Global Energy Interconnection Research Institute Co. Ltd SGCC-HUST Future Grid Research Institute Beijing China School of Control and Computer Engineering North China Electric Power University Changpin District Beijing China

ISBN: (数字)9781728160245

ISBN: (纸本)9781728160252

Hierarchical Text classification has recently become increasingly challenging with the growing number of classification labels. In this paper, we propose a hierarchical fine-tuning based approach for hierarchical text classification. We use the ordered neurons LSTM (ONLSTM) model by combining the embedding of text and parent category for hierarchical text classification with a large number of categories, which makes full use of the connection between the upper-level and lower-level labels. Extensive experiments show that our model outperforms the state-of-the-art hierarchical model at a lower computation cost.

关键词： Training Text categorization Logic gates Neurons Computational modeling Mathematical model Taxonomy

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Research on collaborative frequency regulation control strategy of wind farm based on decentralized exit 8

Research on collaborative frequency regulation control strat...

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8th Renewable power Generation Conference, RPG 2019

作者： Ren, Y.H. Song, P. Wang, X.S. Shi, R.F. School of Control and Computer Engineering North China Electric Power University Beijing102206 China State Grid Jibei Electric Power Research Institute North China Electric Power Research Institute Co.Ltd. Beijing100045 China Grid-connected Operation Technology for Wind-Solar Storage Hybrid System State Grid Corporation Key Laboratory Beijing100045 China

ISBN: (纸本)9781839531255

When the wind turbine adopts the rotor inertia control to participate in grid frequency regulation, it is easy to cause the second frequency drop, which will be more serious when applied to the wind farm. To solve this problem, the influence of wind speed on the unit's ultimate support time under the constant power support mode is analyzed quantitatively and wind turbine recovery time is defined. The functional relationship between the unit's support time and recovery time suitable for engineering application is given. A wind farm frequency regulation optimization model aiming at the longest supporting time of all units in the whole station is established, and the wind farm coordinated frequency regulation control strategy based on decentralized exit is proposed, taking full account of capacity differences of units under different working conditions. Simulation examples show that the real-time coordination of the exit of the wind turbine frequency regulation can effectively alleviate the secondary frequency drop problem of a wind farm. © 2019 Institution of engineering and Technology. All rights reserved.

关键词： Wind turbines

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A novel method to increase energy density of permanent magnet machine based on multi-physical field analysis

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UPB Scientific Bulletin, Series D: Mechanical engineering 2020年第4期82卷 79-92页

作者： Zheng, Qingchun Zhao, Yangyang Zhu, Peihao Wang, Sen Liu, Jingna Ma, Wenpeng Li, Xiang Xiao, Yinhong Wang, Naixin Tianjin Key Laboratory for Advanced Mechatronic System Design and Intelligent Control School of Mechanical Engineering Tianjin University of Technology Tianjin300384 China School of Computer Science Tianjin University of Technology Tianjin300384 China School of Automation Shenyang Institute of Engineering Shenyang110136 China Baoding Power Supply Company Hebei Electric Power Company State Grid Corporation of China Baoding071000 China

As an important component of all-electric aircraft, the main propulsion machine is developing towards high energy density, high efficiency and high fault tolerance. In order to improve the energy density of main propulsion machine for all-electric aircraft, a novel approach, which can be used for excellent performance improvement of electric machine of all-electric aircraft, is reported in this paper. The analytical formula of energy density is put forward and the design method of high energy density permanent magnet machine is presented. A high energy density machine with rated power of 30kW is designed, and the electromagnetic field simulation analysis, strength and stress structure verification, temperature field simulation analysis and multi-physical field coupling analysis are obtained. A prototype is developed, the experiment platform is established, and experiments are performed. The energy density of main propulsion machine designed is up to 21kW·N·m/kg2, and the index is increased by 3.2 times. The optimal method based on the multi-physical field analysis can be also applied to other high energy density machines. © 2020, Politechnica University of Bucharest. All rights reserved.

关键词： Electromagnetic fields

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Maintenance Optimization for Combined Heat and power Unit Based on Opportunistic Maintenance Strategy

Maintenance Optimization for Combined Heat and Power Unit Ba...

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IEEE/IAS Industrial and Commercial power system Asia (I&CPS Asia)

作者： Yumin Zhang Xingquan Ji Yixiao Yu Bo Xu Xueshan Han Lin Zhang College of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao China Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan China State Grid Energy Research Institute Co. Beijing China

ISBN: (数字)9781728143033

ISBN: (纸本)9781728143040

Integrated energy system is composed of different multiple energy systems. When the combined heat and power (CHP) unit fails, more than one energy systems can be influenced. Therefore, it is very important to improve the reliability of CHP unit. In this paper, we propose a maintenance decision making model for CHP unit based on opportunistic maintenance strategy. Firstly, the expression of the availability of CHP unit considering opportunistic maintenance is derived. And then, in order to quantify the impact of different maintenance strategies on system operation, system operation risk is given taking electrical load loss and thermal load loss into account. Finally, maintenance decision making model of the CHP unit is established with maintenance constraints. Case studies show that the model can optimize maintenance strategies and improve the reliability of CHP unit and the overall system efficiency.

关键词： Maintenance engineering Cogeneration Reliability power system reliability Resistance heating Couplings

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A TextCNN Based Approach for Multi-label Text Classification of power Fault Data

A TextCNN Based Approach for Multi-label Text Classification...

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IEEE International Conference on Cloud Computing and Big Data Analysis (ICCCBDA)

作者： Qiang Zhang Rongrong Zheng Ziyan Zhao Bo Chai Jiangui Li Artificial Intelligence on Electric Power System State Grid Corporation Joint Laboratory (GEIRI) Global Energy Interconnection Research Institute Co. Ltd Beijing China State Grid Information & Telecommunication Co. Ltd School of Control and Computer Engineering North China Electric Power University Beijing China

ISBN: (数字)9781728160245

ISBN: (纸本)9781728160252

With the increasing number of power terminal devices in power systems, fault diagnosis based on textual fault data has become a challenging task. Classification technology plays an important role in power system fault diagnosis. In this paper, we propose a TextCNN based approach to multi-label text classification for analyzing fault text data of power terminal devices. First, the main category labels of faults and failure were constructed. The dataset was preprocessed for feature representation. Next, we adopted the TextCNN based model for multi-label classification of power fault texts. The experimental results show that the proposed method is better than the typical multi-label classification models for power fault text multi-label classification. The constructed label categories were also experimentally evaluated, and these labels reflect the main types of power faults and failure.

关键词： Text categorization Internet of Things power system faults Feature extraction Fault diagnosis

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Distributionally Multi-level Co-optimization Dispatch Considering Primary and Secondary Frequency Regulation

Distributionally Multi-level Co-optimization Dispatch Consid...

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IEEE/IAS Industrial and Commercial power system Asia (I&CPS Asia)

作者： Xingquan Ji Yumin Zhang Pingfeng Ye Xueshan Han Bo Xu Ziyang Yin College of Electrical Engineering and Automation Shandong University of Science and Technology Qingdao China Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan China State Grid Energy Research Institute Co. Beijing China

ISBN: (数字)9781728143033

ISBN: (纸本)9781728143040

Distributed energy resource (DER) including wind power, solar energy and energy storage system (ESS) are connected to the active distribution network (ADN) in various combination ways, which makes the distribution network have interaction. As a bridge connecting the transmission grid (TG) and micro grid (MG), ADN breaks the traditional operation pattern of TG+ADN+MG. Considering the physical connections and shared information among TG, ADN and MG, this paper proposes a decentralized and parallel analytical target cascading (ATC) algorithm for TG+ADN+MG multi-level co-optimization dispatch considering primary and secondary frequency regulation. To explore the synergistic ability of the TG+ADN+MG coping with uncertainties of DER, i.e., wind power, the primary and secondary frequency regulation of TG are implemented to cope with uncertainties. Furthermore, the distributional uncertainties of wind power and load are well modeled by data driven, which is proposed in our previous work [1]. An improved 6-bus system is used to test the proposed model, the numerical results illustrate the effectiveness and efficiency of the proposed method.

关键词： Couplings Uncertainty power systems Optimization Load modeling Generators Frequency control

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