检索结果-内蒙古大学图书馆

International Conference on power system technology (powerCON)

作者： Xia Yuanyang Li Xiaocong Liu Yuan Guangxi Key Laboratory of Power System Optimization and Energy Technology Guangxi University Nanning China Intelligent Manufacturing College Nanning University Nanning China Marketing Department Yalong River Hydropower Development Co. Ltd. Chengdu China

The signal components of single-phase grounding current in resonant grounding system contain rich fault characteristic information and are difficult to be fully utilized. A method for line selection using transient fault feature information is proposed. This method achieves information mining through spatiotemporal transformation, expands observation channels, and provides sufficient fault feature information. Adopting blind source separation algorithm to obtain and amplify fault signal features, eliminating compensation effects caused by component reversal. In addition, the concept of generalized correlation coefficient was proposed, and a line selection method based on line energy factor was first proposed. Both simulation calculation and field data-based experiments verify that the method can be applied to fault line selection of grounding system under complex fault conditions of multi type feeders, and accurate and reliable line selection results can be obtained.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Gas Sensitivity Study of Early Diagnostic Markers for Lung Cancer Using Mote2 Single Molecular Membranes Doped with Different Tm Atoms:Based on Density Functional Theory

SSRN

引用

SSRN 2025年

作者： Chen, Yujie Jiang, Wenhao Zhang, Yiyi Chen, Dachang Xu, Min Liu, Jiefeng Jia, Pengfei School of Electrical Engineering Guangxi University Nanning China School of Electrical and Electronic Engineering Wuhan Polytechnic University Wuhan China College of Food Science and Bioengineering Xihua University Chengdu China Guangxi Engineering Technology Innovation Center of Electric Power Transmission and Distribution Network Lightning Protection Guangxi University Nanning China Guangxi Key Laboratory of Power System Optimization and Energy Technology China

Lung cancer has become one of the deadliest and most prevalent cancers worldwide, and the use of gas sensors to detect volatile organic compounds (VOCs) in the exhaled breath of lung cancer patients is gaining increasing popularity. Compared with traditional medical diagnostic methods, this method is cost-effective and less invasive. During our experiments, we employ density functional theory to explore how transition metal (Cu, Pd, Pt)-doped MoTe2 single-molecule membranes respond to VOCs commonly found in the exhalation gas of patients with lung cancer in the early stages of the disease. All three modified systems exhibited excellent thermal stability, and the sorption of VOCs is significantly enhanced compared to the pristine MoTe2, ensuring effective desorption and sensing performance at elevated temperatures. Moreover, the changes in the band gap before and after adsorption are notably distinct, indicating strong gas sensitivity. Among the doped structures, MoTe2-Cu shows the highest adsorption capacity for C5H8, C3H6O, and C3H8O, accompanied by the largest change in the band gap. Due to the varying sensitivities of the three lung cancer biomarker sensors to different gases, cross-sensitivity can be minimised, highlighting the potential for qualitative analysis of VOC gas *** offers new insights and methods for the early detection and prevention of lung cancer. © 2025, The Authors. All rights reserved.

关键词： Lung cancer

来源：评论

学校读者我要写书评

暂无评论

Normalized deep neural network with self-attention mechanism accelerated ADMM for distributed energy management of regional integrated energy systems considering renewable energy uncertainty

引用

energy 2025年 330卷

作者： Linfei Yin Rongkun Liu Wei Ge Guangxi Key Laboratory of Power System Optimization and Energy Technology Guangxi University Guangxi Nanning 530004 China

Wind power and photovoltaic have strong volatility and strong uncertainty, and the energy management (EM) problems of the power system become increasingly complex. Traditional scheduling methods have a slow solution speed, which may be difficult to satisfy the real-time demands of EM. To address this problem, this study presents an alternating direction multiplier method (ADMM) for normalized deep neural networks based on self-attention mechanism (ADMM-NDNN-SAM). The proposed ADMM-NDNN-SAM is a mathematical-model dual-driven framework, where ADMM is a mathematical model and self-attention mechanism is a data-driven method. ADMM-NDNN-SAM organically combines the theoretical reliability of analytical methods with the flexibility and predictive capability of data-driven methods, and can perform intelligently and efficiently in dealing with large-scale and multi-constraint complex integrated energy system optimization problems. Experimental findings on IEEE 39- and 118-bus systems verify that:(1) computational speed is significantly improved. ADMM-NDNN-SAM accelerates the computation speed by 55.12 % and 52.90 % compared with ADMM; (2) compared to seven best-of-breed approaches, ADMM-NDNN-SAM reduces at least 7.11 % of the cost and 8.64 of the CO2 emissions on IEEE 39-bus system, and at least 0.03 % of the cost and 37.65 % of the CO2 emissions on IEEE 118-bus system; (3) scheduling scheme derived from the ADMM-NDNN-SAM method is robust.

关键词： Distributed Wind

来源：评论

学校读者我要写书评

暂无评论

Attention-embedded lightweight convolutional neural network for real-time diagnosis of abnormal electricity consumption behaviors

引用

Expert systems with Applications 2025年 288卷

作者： Linfei Yin Xiaoyu He Guangxi Key Laboratory of Power System Optimization and Energy Technology Guangxi University Nanning Guangxi 530004 China

With the popularization and incorporation of massive renewable energy sources, the electricity consumption behavior of users is gradually diversified and intellectualized. In addition, the switching of large-capacity loads and flexible loads has brought difficulties in monitoring and analyzing user electricity consumption behaviors. To efficiently diagnose abnormal electricity consumption behavior, the traditional load dataset is preprocessed by the proposed multi-directional movement and fast cropping method. The proposed multi-directional movement enhances the accuracy of Google’s inception network from 50% to 98.81%. Furthermore, this study proposes an attention-embedded lightweight convolutional neural network-11 (ALCNN11) network consisting of convolutional layers, pooling layers, batch normalization layers, and residual-like attention blocks. The proposed ALCNN11 can accurately and quickly recognize whether the electricity consumption of users is abnormal or normal. The proposed ALCNN11 network is compared with six unified time scale networks such as “Google’s inception Net”, “a convolutional neural network for image classification”, and “learning transferable architectures for scalable image recognition-mobile” models. The proposed ALCNN11 has the highest accuracy of 99.81% and takes 42.25% less time than visual geometry group 16.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Deep convolutional generative adversarial network accelerated optimization algorithm for parameter optimization of permanent magnet synchronous generator controllers

引用

Applied Soft Computing 2025年 180卷

作者： Linfei Yin Haomiao Li Yongzi Ye Fang Gao Guangxi Key Laboratory of Power System Optimization and Energy Technology Guangxi University Nanning Guangxi 530004 China

In permanent magnet synchronous generators (PMSG), optimized rotor-side controller (RSC) parameters improve the power coefficient. Aiming at the traditional intelligent optimization algorithms since the long optimization time and insufficient global search capability, this work proposes adaptive differential evolution variants with linear population size reduction (L-SHADE) for constrained optimization with Levy flights (COLSHADE) accelerated by using deep convolutional generative adversarial network (DCGAN). The DCGAN-COLSHADE converts the parameters of the PMSG controllers into pictures and utilizes the DCGAN alternative algorithmic iterative process to speed up the COLSHADE iterative process and accomplish a broader and deeper global optimization problem. The PMSG simulation results utilizing the maximum power point tracking strategy verify the DCGAN-COLSHADE can obtain globally optimal solutions and higher system stability. The fitness function value of DCGAN-COLSHADE is 3.96 % smaller than the comparison algorithm; the average computation time is 79.28 % less than the particle swarm optimization (PSO), 80.35 % less than the moth flame optimization (MFO), 80.75 % less than the whale optimization algorithm (WOA), 80.52 % less than gray wolf optimization (GWO) and 77.96 % less than COLSHADE. In addition, the results of rapid control prototype (RCP) hardware experiments validate the feasibility and effectiveness of the algorithm.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Cr2-Modified G-Cn Interface: A Novel Gas Sensitive Material for Decomposition Products of Green Insulating Gas CF3SO2F

SSRN

引用

SSRN 2024年

作者： Xu, Yang Wang, Mingxiang Zhang, Yiyi Chen, Dachang Xu, Min Ma, Changyou Jia, Pengfei School of Electrical Engineering Guangxi University Nanning530004 China School of Electrical and Electronic Engineering Wuhan Polytechnic University Wuhan530004 China College of Food Science and Bioengineering Xihua University Chengdu610039 China Data Recovery Key Laboratory of Sichuan Province Neijiang Normal University Neijiang641100 China Guangxi Key Laboratory of Power System Optimization and Energy Technology China

Currently, CF3SO2F shows great potential as a green insulating gas to replace SF6 in the electrical industry to support the dual-carbon program. However, it has the potential to undergo partial discharges and thus decomposition under the operating voltage of the power grid, and the gas-sensitive detection technique is an effective method to diagnose this problem. In this work, the gas-sensitive properties of the Cr2@g-CN interface for each harmful gas molecule were investigated from a microscopic point of view, using the harmful gases (SO2, HF, SO2F2, CF4) that may be produced by CF3SO2F as the detection targets. Then, the performance of Cr2@g-CN interface as a gas sensor material in practical applications was predicted. The final results revealed that the Cr2@g-CN interface is most suitable as a potential gas-sensitive material for SO2 gas sensors. The exploration of humidity effects suggests that Cr2@g-CN remains a promising SO2 gas sensing material for practical applications in specific humidity environments. This work reveals the origin of the excellent properties of Cr2@g-CN as a gas sensor material and provides new ideas for the detection of CF3SO2F decomposition products. © 2024, The Authors. All rights reserved.

关键词： Gases

来源：评论

学校读者我要写书评

暂无评论

Control of Doubly Fed Induction Generator-Based Wind Turbine for the Supplementary Frequency Regulation 20

Control of Doubly Fed Induction Generator-Based Wind Turbine...

引用

20th IEEE International Conference on Communication technology, ICCT 2020

作者： Chen, Xiaobin Liu, Hui Xie, Haimin Qin, Risheng Guangxi University Guangxi Key Laboratory of Power System Optimization and Energy Technology Nanning China Yunnan Power Grid Corporation Ltd Electric Power Research Institute Kunming China

ISBN: (纸本)9781728181417

To enhance the frequency stability and reduce the reserve of active power, a control strategy is proposed for doubly fed induction generator-based wind turbine (DFIG-WT) to participate in supplementary frequency regulation (SFR) in this paper. A control framework is developed for wind farm to implement the regulation in real time. While the operating conditions of wind turbines are uploaded to the control center, the capacity for regulation of wind farm is calculated in the control center. At the same time, the task for regulation is assigned from the control center to wind turbines, and the power distribution method is proposed for DFIG-WT to participate in SFR within their capacity. Simulations on an interconnected two-area power system show that the proposed strategy can effectively enhance the frequency stability of the system and simultaneously improve the capacity of the power grid for wind power absorption. © 2020 IEEE.

关键词： Wind turbines

来源：评论

学校读者我要写书评

暂无评论

Subsynchronous Oscillation Detection Using Synchrosqueezing Wavelet Transforms and K-means Clustering

Subsynchronous Oscillation Detection Using Synchrosqueezing ...

引用

power and Electrical Engineering (ACPEE), 5th Asia Conference on

作者： Jianluo Lu Yude Yang Guangxi Key Laboratory of Power System Optimization and Energy-Saving Technology Guangxi University Nanning China

ISBN: (数字)9781728152813

ISBN: (纸本)9781728152820

For the non-stationary and nonlinear characteristics of the Subsynchronous Oscillation (SSO) of the power system, the existing detection methods are sensitive to noise, and it is difficult to obtain the characteristic and development trend of oscillation. In this paper, Synchrosqueezing Wavelet Transforms (SWT) combined with K-means Clustering is introduced into subsynchronous oscillation harmonic detection and analysis. The strong anti-mode aliasing ability and anti-noise ability of SWT are utilized to clearly and intuitively represent the oscillation modes contained in the signal under the background of noise. Frequency domain slicing is used to extract and reconstruct the modes that need attention from the power signals containing multiple oscillation modes for parameter identification. Combined with the feature of SWT that squeezes the wavelet coefficients to the center frequency, the K-means clustering method is used to accurately locate the center frequency of the oscillating mode contained in the signal before reconstruction, and the frequency slice interval of the signal reconstruction can be automatically selected. Finally, the simulation results verify the validity and accuracy of the proposed method.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Docker-Based energy Management system Development and Deployment Methods

Docker-Based Energy Management System Development and Deploy...

引用

power and energy Engineering (ICPEE), International Conference on

作者： Zongsheng Li Hua Wei Chunjie Lian Shengchao Qin Guangxi Key Laboratory of Power System Optimization and Energy Saving Technology (Guangxi University) Nanning China

ISBN: (数字)9781728191256

ISBN: (纸本)9781728191263

This paper proposes a Docker-based energy management system (DEMS) architecture to solve the problems of slow deployment and low flexibility of traditional energy management system (TEMS). Compared with TEMS, DEMS uses containerized packaging, the deployment environment and the number of Web Service releases are reduced from at least three times to one, and the workload is reduced by about two times. When the system has high concurrency, the application can be elastically expanded by adding or subtracting instances to calmly cope with peak traffic. DEMS applications use a mirrored development method. During the update process, only the Dockerfile needs to be modified first, and then the container instance is regenerated according to the new Dockerfile, which speeds up and simplifies the application update process. On the other hand, Docker virtualization is more lightweight and convenient than VMs, effectively reducing virtualization costs. This architecture has been applied to the upgrade and transformation of an actual power system EMS in China, which has good actual operating results.

关键词： Containers Virtualization Computer architecture Cloud computing power systems Reliability Virtual machining

来源：评论

学校读者我要写书评

暂无评论

$\mathrm{L}_p$ Quasi Norm State Estimator for power systems

引用

Journal of Modern power systems and Clean energy 2021年第4期10卷 871-882页

作者： Zhongliang Lyu Xiaoqing Bai Hua Wei Daiyu Xie Le Zhang Peijie Li School of Electrical Engineering Guangxi University Nanning China Guangxi Key Laboratory of Power System Optimization and Energy Technology Guangxi University Nanning China Power Dispatching Control Center of Guangxi Power Grid Nanning China

This paper proposes an L p (0 2 norm estimators, the proposed estimator can suppress the bad data more effectively. The robustness of the proposed estimator is discussed, and an analysis shows that its ability to suppress bad data increases as $p$ decreases. Moreover, an algorithm is suggested to solve the non-convex state estimation problem. By introducing a relaxation factor in the mathematical model of the proposed estimator, the algorithm can prevent the solution from converging to a local optimum as much as possible. Finally, simulations on a 3-bus DC system, the IEEE 14-bus and IEEE 300-bus systems as well as a 1204-bus provincial system verify the high computation efficiency and robustness of the proposed estimator.

关键词： power systems Mathematical model Robustness Weight measurement State estimation Noise measurement Simulation

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：