检索结果-内蒙古大学图书馆

SSRN 2022年

作者： Sun, Guanyue Zhao, Hongfeng Meng, Xiaoji Wang, Feng Dezhou University Shandong254300 China The Wind Solar Storage Division of State Key Laboratory of Control and Simulation of Power System and Generation Equipment School of Electrical Engineering Xinjiang University Urumqi830046 China Xidian Surge Arrester Co. Ltd. Shanxi Xi’an710200 China

This paper studies the aging characteristics of Ca-doped ZnO varistors when the accelerated AC aging chargeability is 0.9 (135°C/ 1000h). Ca-doped ZnO varistors not only there are good breakdown voltage and low leakage current, according to the current-voltage and capacitance-voltage characteristic curves of ZnO varistor before and after aging. After the aging, the breakdown voltage and leakage current change rate are small. The ZnO varistor doped with Ca can slow down the aging speed to a certain extent and has good stability under the AC electric field. © 2022, The Authors. All rights reserved.

关键词： Electric breakdown

来源：评论

学校读者我要写书评

暂无评论

Development scales of clean energy power in North Africa in the background of transnational interconnection

Development scales of clean energy power in North Africa in ...

引用

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

作者： Liang Zhao Ruoying Yu Zhe Wang Linan Qu Xiangyan Wang State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems China Electric Power Research Institute Beijing China Renewable Energy Research Centre China Electric Power Research Institute Beijing China Development Bureau Global Energy Interconnection Development and Cooperation Organization Beijing China

ISBN: (数字)9781728152813

ISBN: (纸本)9781728152820

Energy transformation and sustainable development is the strategy of global energy development. The clean energy development is an important way to achieve this goal, especially in North Africa, which is rich in wind and solar resources. In this paper, the distributed characteristic of clean energy resources and electric power industry in North Africa are analyzed. Under the background of transnational interconnection, the capacity scales optimization planning model of clean energy power generation development, including wind, photovoltaic (PV) and concentrating solar power (CSP) based on the objective of minimizing construction cost and electricity curtailment loss is established. Considering independent development of three countries, transnational interconnection within the region and transcontinental interconnection between North Africa and South Europe, optimal capacity scales of three types clean energy power are planned in Morocco, Egypt and Tunisia through time series production simulation method. Meanwhile, three scenarios of high, middle and low utilization hours of transmission channels are chosen to plan under transnational interconnection background. The results show that combined power generation of clean energy with CSP can replace a part of conventional power units to satisfy local load increase demand and transnational interconnection will promote the scale of clean energy development in all countries as well as realizing the complementary benefit of clean energy power in interconnected regions. It is an important way to implement the energy transformation strategy in North Africa in the future.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Wind power Forecasting Considering Data Privacy Protection: A Federated Deep Reinforcement Learning Approach

arXiv

引用

arXiv 2022年

作者： Li, Yang Wang, Ruinong Li, Yuanzheng Zhang, Meng Long, Chao The Key Laboratory of Modern Power System Simulation Control and Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China The State Grid Jilin Electric Power Co. Ltd Jilin Power Supply Company Chuanying District Jilin132001 China The School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China The School of National Key Laboratory of Science and Technology Vessel Integrated Power System Naval University of Engineering Wuhan430033 China The School of Water Energy and Environment Cranfield University United Kingdom

In a modern power system with an increasing proportion of renewable energy, wind power prediction is crucial to the arrangement of power grid dispatching plans due to the volatility of wind power. However, traditional centralized forecasting methods raise concerns regarding data privacy-preserving and data islands problem. To handle the data privacy and openness, we propose a forecasting scheme that combines federated learning and deep reinforcement learning (DRL) for ultra-short-term wind power forecasting, called federated deep reinforcement learning (FedDRL). Firstly, this paper uses the deep deterministic policy gradient (DDPG) algorithm as the basic forecasting model to improve prediction accuracy. Secondly, we integrate the DDPG forecasting model into the framework of federated learning. The designed FedDRL can obtain an accurate prediction model in a decentralized way by sharing model parameters instead of sharing private data which can avoid sensitive privacy issues. The simulation results show that the proposed FedDRL outperforms the traditional prediction methods in terms of forecasting accuracy. More importantly, while ensuring the forecasting performance, FedDRL can effectively protect the data privacy and relieve the communication pressure compared with the traditional centralized forecasting method. In addition, a simulation with different federated learning parameters is conducted to confirm the robustness of the proposed scheme. Copyright © 2022, The Authors. All rights reserved.

关键词： Electric load dispatching

来源：评论

学校读者我要写书评

暂无评论

Dynamic Identification for a Manipulator Model based on Stribeck Friction using the Quasi-Newton Iterative Method

Dynamic Identification for a Manipulator Model based on Stri...

引用

IEEE International Conference on Robotics and Biomimetics

作者： Feng Xiao Feilong Zhang Bing Han Hualiang Zhang School of Information Science and Engineering Shenyang University of Technology Shenyang China State Key Laboratory of Robotics Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China University of Chinese Academy of Sciences Beijing China Key Laboratory of Networked Control Systems Shenyang Institute of Automation Chinese Academy of Sciences Shenyang China Chinese Academy of Sciences Institutes for Robotics and Intelligent Manufacturing Shenyang China State Key Laboratory of Fluid Power and Mechatronic Systems School of Mechanical Engineering Zhejiang University Hangzhou China

The performance of dynamic control is intimately tied to modeling accuracy. However, traditional estimation methods and friction models, such as the least squares method and the Coulomb plus viscous model, fail to reflect the actual characteristics accurately. Particularly, the linear nature of the Coulomb plus viscous model overlooks the nonlinear static features of joint friction at slower velocities. To improve the rationality of the model structure, we integrate the Stribeck friction model into the Coulomb plus viscous model. However, introducing such nonlinearities compromises the applicability of the least squares method. As a countermeasure, we propose a new strategy that combines the least square method and the Quasi-Newton iterative method to identify the parameters of the modified nonlinear model. Additionally, the design of the excitation trajectory is critical to achieve high identification accuracy. We utilized the inverse of the smallest singular value of the observation matrix as the objective function. By minimizing it with the interior point method, we generate the excitation trajectory well-suited to stimulate dynamic characteristics. Then we leverage the discrepancies between the measured and estimated torques to assess the precision of the dynamic parameters of the manipulator. Remarkably, our proposed algorithm reduces the mean absolute error of the estimated torque by over 20.40%. Finally, an experiment of the industrial manipulator by hand guiding grab and drag is performed and shows that the proposed approach can provide the manipulator with comprehensive torque compensation.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Physical Passivation of Deep-Level Defect states in Polymer Dielectrics for Outstanding Dielectric Properties

SSRN

引用

SSRN 2023年

作者： Li, Xiao-Fen Wang, Tian-Yu Yin, Si-Jia Zhang, Gui-Xin Liu, Jian-Bo Liu, Bai-Xin School of Materials Science and Engineering Tsinghua University Beijing100084 China State Key Laboratory of Control and Simulation of Power System and Generation Equipment Department of Electrical Engineering Tsinghua University Beijing100084 China College of Art and Design Visual Communication Design SuZhou University Suzhou234111 China

The limited dielectric strength of polymer dielectrics hampers their reliable use in highly integrated electrical systems and high-energy storage film capacitors. This constraint is closely associated with the presence of deep-level defect states in polymer dielectrics. Here, we present an efficient and stable approach for the physical passivation of deep-level defect states aimed at enhancing the dielectric properties of polymer dielectrics. Employing inductively coupled plasma technology with argon as the carrier gas, the polymer undergoes substantial decreased deep-level defect states, as evidenced by nano-micro-region defect measurements. Consequently, the localized charge accumulation in the treated polymer dielectric is significantly reduced, resulting in a remarkable 62% increase in flashover voltage. The breakdown strength is also enhanced, and the treated material exhibits long-term stability. Moreover, materials featuring passivated deep-level defect states can boost discharge energy density without compromising efficiency. For instance, PTFE with passivated deep-level defect states maintains a discharge energy density of 1.18 J/cm3 and a charge-discharge efficiency of 95.06% at 200 °C and 300 MV/m. By focusing on deep-level defect states passivation, we introduce a strategy for receiving polymers with exceptional performance and stability. © 2023, The Authors. All rights reserved.

关键词： Passivation

来源：评论

学校读者我要写书评

暂无评论

72-Hour Real-Time Forecasting of Ambient Pm2.5 by Hybrid Graph Deep Neural Network with Aggregated Neighborhood Spatiotemporal Information

SSRN

引用

SSRN 2023年

作者： Teng, Mengfan Li, Siwei Xing, Jia Fan, Chunying Yang, Jie Wang, Shuo Song, Ge Ding, Yu Dong, Jiaxin Wang, Shansi Hubei Key Laboratory of Quantitative Remote Sensing of Land and Atmosphere School of Remote Sensing and Information Engineering Wuhan University Wuhan430079 China Hubei Luojia Laboratory Wuhan University Wuhan430079 China State Key Joint Laboratory of Environmental Simulation and Pollution Control School of Environment Tsinghua University Beijing100084 China School of Systems Science Beijing Normal University Beijing100875 China

The observation-based air pollution forecasting method has high computational efficiency over traditional numerical models, but a poor ability in long-term (after 6 hours) forecasting due to lack of detailed representation of atmospheric processes associated with the pollution transport. To address such limitation, here we propose a novel real-time air pollution forecasting model that applies a hybrid graph deep neural network (GNN_LSTM) to dynamically capture the spatiotemporal correlations among neighborhood monitoring sites to better represent the physical mechanism of pollutant transport across the space. Such design substantially improves the model performance in 72-hour PM2.5 forecasting over the whole Beijing-Tianjin-Hebei region (overall R2 increases from 0.6 to 0.79), particularly for polluted episodes (PM2.5 concentration >55 µg/m3) with pronounced regional transport to be captured by GNN_LSTM model. Inclusion of AOD feature further enhances the model performance in predicting PM2.5 over the sites where the AOD can inform additional aloft PM2.5 pollution feature related to the regional transport. The importance of neighborhood site (particularly for those in the upwind flow pathway of target area) features for long-term PM2.5 forecast is demonstrated by the increased performance in predicting PM2.5 in target city (Beijing) with the inclusion of additional 128 neighborhood sites. Moreover, the newly developed GNN_LSTM model also implies the "source"-receptor relationship, as impacts from distanced sites associated with regional transport grows along with the forecasting time (from 0% to 38% in 72 hours) following the wind flow. Such results suggest great potentials of GNN_LSTM in long-term air quality forecasting and air pollution prevention. © 2023, The Authors. All rights reserved.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

IEC61850-based information modeling of 126KV intelligent terminals

IEC61850-based information modeling of 126KV intelligent ter...

引用

International Conference on Advanced power System Automation and Protection (APAP)

作者： Shu-jian Zhang Bin Wang Ming Sun Xin-zhou Dong Tong Sun Run-bin Cao Electrical engineering and automation Hefei University of Technology Baohe District 230009 China State Key Lab of Control and Simulation of Power Systems and Generation Equipments Dept. of Electrical Engineering Tsinghua University Haidian District Beijing 100084 China School of Automation Nanjing University of Science and Technology Jiangsu 210094 China

The stability and reliability of the intelligent terminal's receiving information affects its control of intelligent switch in operation directly. To achieve reliable intelligent communications terminals, with techniques and methods of IEC61850 modeling, the paper completed the 126KVGIS intelligent terminal information model based on the analysis of its information characteristics, and established the hardware platform with data model and logical nodes provided by IEC61850. Thus it has a certain practical significance to promote the standard construction, operation and management of intelligent substation, and lead the digital process of process layer devices.

关键词： Object oriented modeling Switching circuits Circuit breakers Data models Unified modeling language Analytical models

来源：评论

学校读者我要写书评

暂无评论

Optimal operation of microgrids with risk-constrained state of charge

arXiv

引用

arXiv 2021年

作者： Lei, Jie Hans, Christian A. Sopasakis, Pantelis State Key Laboratory of Power Transmission Equipment & System Security and New Technology Chongqing University China Control Systems Group Technische Universität Berlin Germany School of EEECS and the i-AMS Centre Queen’s University Belfast United Kingdom

— In this paper we present a stochastic scenario-based model predictive control (MPC) approach for the operation of islanded microgrids with high share of renewable energy sources. We require that the stored energy remains within given bounds with a certain probability using risk-based constraints as convex approximations of chance constraints. We show that risk constraints can generally be cast as conic constraints and, unlike chance constraints, can control both the number and average magnitude of constraint violations. Lastly, we demonstrate the risk-constrained stochastic MPC in a numerical case study. Copyright © 2021, The Authors. All rights reserved.

关键词： Stochastic systems

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

Frequency-Domain Adaptive Parametric Model Order Reduction Method for Oscillatory Stability Analysis on Multi-Converter-Fed systems

引用

Journal of Modern power systems and Clean Energy 2024年第3期13卷 802-814页

作者： Xun Jiang Meiqin Mao Liuchen Chang Bao Xie Haijiao Wang Nikos D. Hatziargyriou Research Center for Photovoltaic System Engineering of Ministry of Education Hefei University of Technology Hefei China University of New Brunswick Fredericton New Brunswick Canada State Key Laboratory of Operation and Control of Renewable Energy & Storage Systems (China Electric Power Research Institute) Beijing China National Technical University of Athens Athens Greece

The oscillatory stability analysis of multi-converter-fed systems (MCFSs) with modest computational resources needs a precise parametric reduced-order impedance model (PROIM). However, the traditional Krylov subspace based parametric model order reduction (KS-PMOR) method has difficulty in building precise PROIM for MCFSs. This is because the factors related to the errors of PROIM are complicated and coupled. To fill this gap, the factors associated with the accuracy of the KS-PMOR method are estimated by defining three indicators: the convergence error, cumulative error, and rank of projection matrix. Using the three indicators, a frequency-domain adaptive parametric model order reduction (FDA-PMOR) method is developed to form the precise PROIM of MCFSs for the accurate and fast oscillatory stability analysis. The accuracy of the obtained PROIM using the proposed FDA-PMOR method and its efficiency in actual oscillatory stability analysis are validated by three MCFSs with different scales, i. e., a small-scale MCFS with four paralleled converter-based renewable energy generators (CREGs), a real-time simulation-based MCFS with eighteen paralleled CREGs, and a larger MCFS with ninety paralleled CREGs.

关键词： Impedance power system stability Interpolation Computational modeling Reduced order systems Parametric statistics Accuracy Frequency-domain analysis Adaptation models Vectors

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：