检索结果-内蒙古大学图书馆

International Conference on power System Technology (powerCON)

作者： Liangyuan Chen Ke Zhou Dajian Li Jian Zhao Xunbo Gao Ruize Tong Houxian Du Guangxi Key Laboratory of Intelligent Control and Maintenance of Power Equipment Electric Power Research Institute of Guangxi Power Grid Corporation Co. Ltd. Nanning Guangxi Zhuang Autonomous Region China Electric Power Research Institute of Guangxi Power Grid Corporation Co. Ltd. Nanning Guangxi Zhuang Autonomous Region China Guangxi Power Grid Corporation Co. Ltd. Nanning Guangxi Zhuang Autonomous Region China Digital Grid Research Institute of China Southern Power Grid Guangzhou China

power transformers are essential components of the power system, and their safe and stable operation is of paramount importance. Temperature monitoring plays a vital role in transformer condition assessment, as it is crucial for preventing defects such as insulation aging caused by overheating. The cooling system, a critical part of transformer heat dissipation, indirectly reflects the internal temperature distribution of the transformer. In this paper, by analyzing the cooling system's heat dissipation methods, we establish simplified models for both the transformer body and the cooling system. We simulate the temperature distribution of the cooling system under different loads and various inter-turn short-circuit faults, summarizing their corresponding relationships with the load multiples. The results indicate that the cooling system's temperature distribution exhibits a “higher on top, lower at bottom” pattern, showing a linear correlation with both the load multiples and the severity of inter-turn short-circuit faults.

关键词：

来源：评论

学校读者我要写书评

暂无评论

A Novel YJQR-LSTM Model for Nonparametric Probabilistic Sustainable Agriculture Wind power Forecasting Based on intelligent IoT

引用

IEEE Internet of Things Journal 2024年

作者： Wang, Jie Jiang, Junhui Chen, Xinlong Cai, Defu Wu, Yue Lu, Renzhi School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Harbin Engineering University College of Computer Science and Technology Harbin150001 China State Grid Hubei Electric Power Research Institute Hubei Wuhan430079 China School of Technology State Key Laboratory of Efficient Production of Forest Resources Key Laboratory of National Forestry and Grassland Administration on Forestry Equipment and Automation Beijing Forestry University Beijing100083 China Key Laboratory of Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Key Laboratory of Industrial Internet of Things and Networked Control Ministry of Education Chongqing400065 China State Key Laboratory of Mechanical Transmission for Advanced Equipment Chongqing University Chongqing400044 China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China

Energy costs associated with the consumption of non-renewable energy sources have become an important issue in improving the international competitiveness of agriculture. Wind power, as a renewable energy source, can replace non-renewable energy sources to reduce energy costs and improve the sustainability of agricultural. However, the inherent intermittency, randomness, and volatility within weather conditions and wind speed presents a substantial challenge in accurately predicting wind power generation. This work proposes a novel YJQR-LSTM algorithm that leverages Yeo-Johnson quantile regression (YJQR) with a long short-term memory (LSTM) network for nonparametric probabilistic forecasting of wind power generation via the intelligent Internet of Things. First, an improved YJQR model based on the YJ transformation is designed to obtain a more precise characterization of wind uncertainty, providing a more flexible probability density function for wind power generation. Then, utilizing the unique structure of the LSTM network to learn the parameters of the YJQR model, temporal features can be extracted from time series data. To mitigate the impact of outliers in the raw data on accuracy and improve computational efficiency, a novel logarithmic likelihood function is developed as the loss function utilized in the training phase. The effectiveness of the proposed algorithm is validated using a real-world dataset from five wind farms from the Global Energy Forecasting Competition. Numerical results demonstrate that the algorithm provides more accurate wind power prediction results in complex wind power data environments, which is important for making full use of wind energy and thus reducing the consumption of non-renewable energy in agriculture. © 2024 IEEE.

关键词： Wind forecasting

来源：评论

学校读者我要写书评

暂无评论

Research on cloud-side collaborative task migration strategy based on simulated annealing-Bee Colony Algorithm in power IoT 2

Research on cloud-side collaborative task migration strategy...

引用

2nd International Conference on Consumer Electronics and Computer Engineering, ICCECE 2022

作者： Zhang, Bowen Zeng, Zeng Miao, Weiwei Chinese Academy of Sciences Key Laboratory of Networked Control Systems Shenyang China Chinese Academy of Sciences Shenyang Institute of Automation Shenyang China Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang China State Grid Jiangsu Electric Power Co. Ltd. Information Telecommunication Branch Nanjing China

ISBN: (纸本)9781665408868

In the power IoT, in order to make up for the shortcomings of insufficient computing capabilities of edge-side devices, cloud-side collaboration technology has attracted more and more attention. The cloud-side collaboration technology relies on the selection of task migration strategies. However, when the existing migration strategies face the complex edge-side terminal devices in the power IoT, the energy consumption and delay performance are not good enough, which greatly affects the user's power experience. Therefore, it is very valuable to study a cloud-side collaborative task migration strategy under the power IoT environment. This paper proposes a task migration strategy based on simulated annealing-Bee Colony Algorithm in the environment of power IoT, which can solve the problem of task migration. Experimental results show that compared with the existing popular methods, this method has advantages in terms of energy consumption and time delay. This research can meet the real-time requirements of the power IoT, while reducing energy consumption and improving the user's power experience, thereby promoting the further development of the power IoT. © 2022 IEEE.

关键词： Simulated annealing

来源：评论

学校读者我要写书评

暂无评论

Optimizing Binary Sequence Excitation Signals for Rapid Impedance Spectrum Measurement in Proton Exchange Membrane Fuel Cells

Optimizing Binary Sequence Excitation Signals for Rapid Impe...

引用

第43届中国控制会议

作者： Jingzhi Lei Chuang Sheng Jingjing Wang Liansong Yu Xi Li School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control of Education MinistryHuazhong University of Science and Technology State Grid Electric Power Research Institute Wuhan Nanrui Limited Liability Company Shenzhen Huazhong University of Science and Technology Research Institute

ISBN: (数字)9789887581581

ISBN: (纸本)9798350366907

With the increasing demand for efficient and reliable renewable energy sources,Proton Exchange Membrane Fuel Cells(PEMFCs) have emerged as a promising *** experiments demonstrate that Electrochemical Impedance Spectroscopy(EIS) effectively differentiates various states of *** broadband signals as testing excitations significantly reduces EIS measurement time,facilitating real-time monitoring of PEMFCs' health under dynamic *** signal design requires maintaining adequate amplitude across frequency components for noise resistance while minimizing signal peak value to reduce operational *** paper introduces an EIS simulation environment,leveraging PEMFCs' impedance and electrochemical noise *** focuses on optimizing the excitation signal's amplitude-frequency distribution using discrete interval binary *** results indicate that our method achieves minimal perturbation amplitude while preserving measurement accuracy in amplitude-frequency signal design.

关键词： Proton exchange membrane fuel cell Electrochemical impedance spectroscopy Electrochemical noise Excitation signal optimization

来源：评论

学校读者我要写书评

暂无评论

Short Circuit Ratio Index Considering HVDC Transient Characteristics

Short Circuit Ratio Index Considering HVDC Transient Charact...

引用

Asia Conference on Energy and Environment Engineering (ACEEE)

作者： Fan Li Haoyang Yu Zhongjian Liu Dong Liu Kexin Zhang Cheng Zhang Mingjie Wang Yixing Zhang De Zhang Xiaofan Su State Grid Economic and Technological Research Institute Co. Ltd. Beijing China Power Dispatching Control Center of Guizhou Power Grid Co. Ltd. Guiyang China The School of Electrical Engineering Xi’an Jiaotong University Xi’an China Hunan Key Laboratory of Energy Internet Supply-Demand and Operation State Grid Hunan Electric Power Company Limited Economic & Technical Research Institute Changsha China

HVDC systems are extensively utilized due to their numerous advantages. However, these systems encounter significant challenges in terms of transient voltage stability during fault occurrences. Therefore, there is a pressing need for an improved evaluation method to assess the transient voltage level in multi-infeed systems. To address this issue, this paper proposes a novel index, namely the transient multi-infeed short circuit ratio (TMSCR), based on the short circuit ratio (SCR) index, which takes into account the transient voltage characteristics of the system. The paper proceeds as follows: Firstly, it introduces the definition of existing indicators. Secondly, it incorporates transient active or reactive power to derive an index that considers the transient characteristics. Finally, it compares the characteristics of the two short-circuit ratio indexes, and the simulation results validate the accuracy of the proposed indicators.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Development and Application of State-Sensing Technology for power Equipment 2020

Development and Application of State-Sensing Technology for ...

引用

Proceedings of the 3rd International Conference on Information Technologies and Electrical Engineering

作者： Wenjun Liu Yuanfu Xu Qiang Han Yao Wang Lei Xu State Key Laboratory of Electrical Insulation of Power Equipment Xi'an Jiaotong University Xi'an China Power Dispatching and Control Center State Grid State Grid Tianjin Electric Power Company Tianjin China Power Dispatching and Control Center State Grid Tianjin Electric Power Company Tianjin China

ISBN: (纸本)9781450388665

With the increasing expansion of power grid scale, the research and application of artificial intelligence technology in the electrical field will further promote the profound transformation of power grid structure. power equipment, as core elements of power grid, monitoring information has been quantification and discretization caused by the grid intelligent transformation. Therefore, it is urgent to deeply integrate artificial intelligence technology and take advantage of data driven to improve the perception ability of equipment running status, thereby promoting the utilization ratio of power equipment assets and ensuring safety and reliability of power grid. At present, the traditional equipment status evaluation cannot realize the efficient utilization of massive power data. In addition, the power data obtained by the current sensing technology still has problems such as errors and instability, which leads to the fact that the state perception effect of the power equipment cannot satisfy the development demand of the power grid. However, as a new solution, the introduction of the Internet of Things and big data analysis technology provide new technical support for the power equipment perception *** this paper, the mature state perception technology and its application has been summarized. Furthermore, the corresponding parameter performance, advantages and disadvantages has been analyzed. Finally, the future development of state perception technology of power equipment is prospected according to the current situation of power grid.

关键词： Artificial Intelligence (AI) the Internet of Things State Perception Electrical Equipment

来源：评论

学校读者我要写书评

暂无评论

Simulation research on primary frequency regulation coordination control strategy of hybrid wind-PV-ES power station based on AGC

Simulation research on primary frequency regulation coordina...

引用

Annual Meeting of CSEE Study Committee of HVDC and power Electronics (HVDC 2023)

作者： S. Li Y. Hu X. He Y. Zhu T. He C. Luo C. Deng G. Zeng M. Su Yunnan Electric Power Research Institute Kunming People's Republic of China National Energy Power Grid Technology R&D Centre Guangzhou People's Republic of China State Key Laboratory of HVDC Electric Power Research Institute CSG Guangzhou People's Republic of China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou People's Republic of China CSG Key Laboratory for Power System Simulation Electric Power Research Institute China Southern Power Grid Guangzhou People's Republic of China

With the increase of wind and solar renewable energy penetration in power system, the frequency control ability of power system completely depending on traditional power supply has weakened. This actuality requires that renewable energy stations should be equipped with a certain amount of energy storage to improve the primary frequency control ability. This paper considers the fast response ability and flexible control of energy storage for both charging and discharging, as well as its unique frequency response characteristics. Firstly, the control characteristics of the primary frequency regulation of the hybrid wind-solar-storage power station(Wind-PV-ES) are analyzed. By improving the automatic generation control(AGC) strategy of the hybrid Wind-PV-ES power station, a coordinated control strategy for the primary frequency regulation of the hybrid Wind-PV-ES power station is proposed for different frequency ranges based on the improved AGC control. After the primary frequency regulation action, the energy storage output is given priority control before wind and solar. When the energy storage active margin is insufficient, use the frequency regulation capacity of wind and photovoltaic power system to improve the primary frequency regulation capacity of the hybrid Wind-PV-ES power station. The control strategy proposed in this paper can improve the primary frequency regulation capability of renewable energy station. Finally, the paper verifies the effectiveness of the proposed control strategy through simulation.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Development and application of state-sensing technology for power equipment 3

Development and application of state-sensing technology for ...

引用

3rd International Conference on Information Technologies and Electrical Engineering, ICITEE 2020

作者： Liu, Wenjun Xu, Yuanfu Han, Qiang Wang, Yao Xu, Lei State Key Laboratory of Electrical Insulation of Power Equipment Xi'An Jiaotong University Xi'an China Power Dispatching and Control Center State Grid State Grid Tianjin Electric Power Company Tianjin China

ISBN: (纸本)9781450388665

With the increasing expansion of power grid scale, the research and application of artificial intelligence technology in the electrical field will further promote the profound transformation of power grid structure. power equipment, as core elements of power grid, monitoring information has been quantification and discretization caused by the grid intelligent transformation. Therefore, it is urgent to deeply integrate artificial intelligence technology and take advantage of data driven to improve the perception ability of equipment running status, thereby promoting the utilization ratio of power equipment assets and ensuring safety and reliability of power grid. At present, the traditional equipment status evaluation cannot realize the efficient utilization of massive power data. In addition, the power data obtained by the current sensing technology still has problems such as errors and instability, which leads to the fact that the state perception effect of the power equipment cannot satisfy the development demand of the power grid. However, as a new solution, the introduction of the Internet of Things and big data analysis technology provide new technical support for the power equipment perception technology. In this paper, the mature state perception technology and its application has been summarized. Furthermore, the corresponding parameter performance, advantages and disadvantages has been analyzed. Finally, the future development of state perception technology of power equipment is prospected according to the current situation of power grid. © 2020 ACM.

关键词： Internet of things

来源：评论

学校读者我要写书评

暂无评论

Accurate Identification and Localization of Transmission Lines Under Complex Lighting for Distribution Network power Supply Operation Robots

Accurate Identification and Localization of Transmission Lin...

引用

Chinese Automation Congress (CAC)

作者： Tianhe Liu Xin Chen Chenyu Hu Xu Jian Shengzu Li Gang Wang School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Equipment Technology Center State Grid Hubei Electric Power Co. Ltd. Electric Power Science Research Institute Wuhan China Distribution Department State Grid Hubei Electric Power Co. Ltd. Wuhan Power Supply Company China

ISBN: (数字)9798350368604

ISBN: (纸本)9798350368611

Accurate identification and position of transmission lines is critical for robots to safely and effectively perform distribution network operations. However, such tasks are often challenged by complex lighting conditions, where depth information can be easily lost. Transmission lines have limited texture features and reflective surfaces, making it difficult to match image feature points. To address these challenges, this paper proposes a visual perception system for weak texture targets under complex lighting, based on an “eye-on-hand” configuration and a depth complementation algorithm. Furthermore, a high-precision identification and localization method for transmission line grasping points is developed, utilizing the fusion of binocular visual color maps and depth maps. The proposed method has been shown to effectively solve the problem of identifying and localizing the grasping points of transmission lines under complex lighting conditions. Experiments demonstrated that the method can improve the localization accuracy to within $\pm 4\text{mm}$ , outperforming other algorithms. The method is characterized as simple and efficient, and it enhances the environmental adaptability of distribution network robots.

关键词： Location awareness Visualization power transmission lines Accuracy Image color analysis Lighting Distribution networks Grasping Wire Robots

来源：评论

学校读者我要写书评

暂无评论

Capacity Model and Optimal Scheduling Strategy of Multi-Microgrid Based on Shared Energy Storage

SSRN

引用

SSRN 2024年

作者： Dai, Bin Wang, Honglei Li, Bin Li, Chengjiang Tan, Zhukui Electrical Engineering College Guizhou University Guiyang550025 China Key Laboratory of "Internet+" Collaborative Intelligent Manufacturing in Guizhou Provence Guizhou Guiyang550025 China State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou310027 China School of Engineering University of Tasmania HobartTAS7005 Australia Electric Power Research Institute Guizhou Power Grid Co. Ltd. Guiyang550002 China

The large-scale use of renewable energy (RE) requires proportional investment in energy storage to solve the uncertainty of both the supply and demand sides of the power grid, which brings about the problems of high investment costs and long payback periods. This paper proposes a multi-microgrid energy storage sharing (SES) model. The SES model shapes the virtual energy storage capacity during power system operation, and the demand for energy storage capacity is reduced. A benefit distribution mechanism is developed to ensure fair income distribution among participants based on their investment proportion, promoting direct benefit interaction. A bi-level optimization method is designed to optimize the energy storage capacity and scheduling strategy simultaneously to ensure that they match each other. A non-dominated sorting equilibrium optimizer algorithm is proposed to avoid the Pareto solution set falling into local optimal and ensure the reasonable realization of the proposed benefit distribution mechanism. The results show that compared with distributed energy storage, the SES model reduces the required storage capacity of the system by 43.27% and reduces the daily investment and operation and maintenance cost by 25.98%. With the same operational performance, the SES model requires less storage capacity and 97.30% self-consumption of RE. © 2024, The Authors. All rights reserved.

关键词： Investments

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：