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检索条件"机构=tate Key Laboratory of Smart Grid Protection and Control"

共 369 条记录，以下是231-240 订阅

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Impact of Generation Companies' Heterogeneous Investment Behaviors on the Effects of Non-fossil Energy Incentive Policies

Impact of Generation Companies' Heterogeneous Investment Beh...

引用

2021 IEEE Sustainable Power and Energy Conference, iSPEC 2021

作者： Cai, Bin Li, Tianran Wang, Kui Li, Zhiyuan Zhu, Lei Wen, Jun Xue, Yusheng Nari Group Corporation State Grid Electric Power Research Institute State Key Laboratory of Smart Grid Protection and Control Nanjing China Integrated Energy of Jiangsu Province Nanjing Normal University Nari School of Electrical and Automation Engineering Engineering Laboratory of Gas-Electricity Nanjing China China Huaneng Group Co. Ltd Beijing China

ISBN: (纸本)9781665414395

The incentive policies for non-fossil energy are important factors affecting the investment behavior of generation companies (GENCOs). However, the investment behavior of different types of GENCOs in the system could be quite different, so the implementation of the policy must consider how to achieve incentive compatibility with the investment behavior of GENCOs. This article constructs a power transition simulation model that considers the investment behavior of GENCOs. Taking the wind power feed-in tariff policy as an example, it analyzes the impact of policy on the whole system's low carbon transition pathway of the power structure and the evolution trajectory of system carbon emissions under different behavior scenarios. © 2021 IEEE.

关键词： Investments

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Research on External Characteristics for PMSG Wind Turbine Systems under Symmetrical Fault

Research on External Characteristics for PMSG Wind Turbine S...

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2020 IEEE Sustainable Power and Energy Conference, iSPEC 2020

作者： Xie, Hua Zhao, Qingchun Liu, Peilin Gao, Xuesong NARI Group Corporation State Key Laboratory of Smart Grid Protection and Control Nanjing China School of Electrical Engineering Shandong University Jinan China

ISBN: (纸本)9781728191645

Wind turbines (WTs) are based on power electronic converters. Due to different control schemes of converters, WTs exhibit diverse external characteristics when grid symmetrical fault occurs. Thus, the output current and output power of WTs cannot be forecasted, which is a challenge for the power system stability. In this regard, this paper proposes a novel strategy for Permanent Magnetic Synchronous Generator (PMSG) wind turbine systems. The strategy aims to force the PMSG exhibit a stable EFC during grid fault and provide an output current reference to the power system. Besides, the proposed strategy aims at enhancing the low-voltage ride-through capability of the PMSG. The effectiveness and robustness of the proposed strategy is verified in DIgSILENT PowerFactory. © 2020 IEEE.

关键词： Synchronous generators

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A Flow-Appearance Fusion Defect Detection Method for Substation Equipment in Multi-Scene

A Flow-Appearance Fusion Defect Detection Method for Substat...

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Chinese Automation Congress (CAC)

作者： Qingwei Zhang Jing Wang Peng Wang Wenhao Zhou Chunhui Zhao State Key Laboratory of Smart Grid Protection and Control NARI Technology Development Company Limited Nanjing China Stale Key Laboratory of Industrial Control Technology Zhejiang University Hangzhou China

ISBN: (纸本)9781665426480

In the daily maintenance process of substation, the defect detection of substation equipment is a critical problem. This task is challenging considering of the variety of defects, the rarely sample of various defects and the complex environment. This paper presents a flow-appearance fusion defect detection method for substation equipment in multiple scenes, which contains a Siamese optical flow module and a defect location module. The Siamese optical flow module is a pretrained optical flow network, which is utilized to obtain forward and backward optical flow between the normal image and the detect image. The optical flow represents the common changing features of different types of defects in multiple scenes. The defect location module utilizes MI-darknet53 to realize the extraction and fusion of appearance and flow features. Then the extracted multiscale features are used to build the feature pyramid network (FPN), which combines semantic defect information in high level and geometric defect information in low level. Finally, FPN is utilized to predict object-level defect areas in three different scales. Experiments show that our proposed method has good reliability and superior performance in the defect detection for the dataset of multi-scene substation equipment.

关键词： Substations Automation Semantics Maintenance engineering Feature extraction Reliability Data mining

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Small-Signal Modeling of Modular Multilevel DC Transformer 5th

Small-Signal Modeling of Modular Multilevel DC Transformer

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International Top-Level Forum on Engineering Science and Technology Development Strategy and 5th PURPLE MOUNTAIN FORUM on smart grid protection and control, PMF2020

作者： Hou, Kai Wu, Xingyu Min, Fuhong Wang, Zhigang Wang, Guoning State Key Laboratory of Smart Grid Protection and Control Nanjing Jiangsu211106 China Nanjing Jiangsu211106 China NARI Technology Co. Ltd. Nanjing Jiangsu211106 China School of Electrical and Automation Engineering Nanjing Normal University Nanjing210023 China

ISBN: (纸本)9789811597459

The dc transformer is considered to be one of the most promising components in future energy systems. The modular multilevel dc transformer inherits many of the characteristics of modular multilevel converter and dual active bridge, which brings many advantages and leads to different working principles from traditional dc transformers. In this paper, the mathematical model is obtained by harmonic decomposition and the small-signal model is obtained by linearization. The parameters of the PI controller are designed according to the small-signal model. The open-loop time-domain simulation verifies the accuracy of the mathematical model. The closed-loop simulation model verifies the reliability of the PI controller. After adding the PI controller, the results of the output voltage show that the model has fast dynamic response with no static errors, which proves that the model obtained by the harmonic decomposition is reliable. © 2021, Springer Nature Singapore Pte Ltd.

关键词： DC transformers

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The operation analysis of the CCHP driven by Gas-steam combined cycle 2

The operation analysis of the CCHP driven by Gas-steam combi...

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2nd International Conference on Oil and Gas Engineering and Geological Sciences, OGEGS 2020

作者： Liang, Junyu Yuan, Xingyu Gu, Jiangqi Yunnan Electric Power Research Institute Csg China Nari Group Co. Ltd State Key Laboratory of Smart Grid Protection and Operation Control

In combined cooling heating and power system, the gas-steam combined cycle is gradually used more and more. The common operation mode in CCHP is mainly to determine heat by electricity and heat by electricity. This paper defines an index indicator and analyzes the difference between the two operating modes in different intervals through the system energy supply interval chart, finally analyzes the difference in the indicators between the two operating modes through the actual load method. It is concluded that in winter operating conditions, the following the thermal load (FTL) operation mode is better;in summer operating conditions, the indicator of following the electric load (FEL) is better;during the transition season, the value of PEC is better in the case of following the thermal load. © Published under licence by IOP Publishing Ltd.

关键词： Thermal load

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Automatic Generation Method of Multi-Bays Graph In Power System based on Real-time Topological Model

Automatic Generation Method of Multi-Bays Graph In Power Sys...

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作者： Yuan Gao LianJie Chen Peng Si YunGuang Su CaiShen Fang Hua Xu Kun Huang NARI Group Corporation(State Grid Electric Power Research Institute) NARI Technology Co. Ltd. NARI Group Corporation(State Grid Electric Power Research Institute) NARI Technology Co. Ltd.State Key Laboratory of Smart Grid Protection and Control

Substation supervisory control is an essential part of power grid monitoring system. Besides the power flow between substations, the running states of the devices in substations are important to the staff in power grid. At present, the substation devices with their running states are drawn in electrical bay graphs, which are widely used in the power grid dispatching department. Traditional electrical bay graphs contain devices in only one substation and the drawing process of the graph relies on manual work. In this paper, an automatic generation method of multi-bay graph in power system based on real-time topological model is proposed. There are two stages in the method. In the first stage, necessary model information is obtained according to topology in real-time database. In the second stage, the bay features are firstly built in the method and the classification of the bays is achieved by these ***, a data structure of device tree is proposed and the automatic layout of devices is realized based on the data structure. Finally, automatic wiring of the devices is achieved from the perspective of aesthetic and objectivity. Experimental results show that the graph drawn by the proposed method could not only reflect the actual connection mode and running states of the substation devices but also show the power flow between these substations. The proposed drawing method could reduce manual operations and improve the work efficiency of the power grid staff.

关键词： Multi-Bays Graph Device Tree Automatic Layout Automatic Wiring

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Waveform Design for MIMO-OFDM Based Dual-functional Radar and Communication Systems

Waveform Design for MIMO-OFDM Based Dual-functional Radar an...

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International Conference on Wireless Communications and Signal Processing (WCSP)

作者： Tianchen Liu Liang Wu Zaichen Zhang Jian Dang Bingcheng Zhu Yin Yao Liu Dongsheng National Mobile Communications Research Laboratory Southeast University Nanjing P.R.China Purple Mountain Laboratory Nanjing P.R.China State Key Laboratory of Smart Grid Protection and Control NARI Group Co. Ltd Nanjing China

ISBN: (纸本)9781665450867

Dual-functional radar-communications (DFRC) technique has attracted substantial attention. The radiation power of radar system is usually very high, and it is usually not afforded by the communication receiver. To solve this problem, this paper proposes a waveform design scheme for the DFRC system based on multiple-input and multiple-output (MIMO) and orthogonal frequency division multiplexing (OFDM) techniques. In the proposed scheme, a convex optimization problem is firstly formulated to derive the optimal covariance matrix of the transmit signals. Based on the optimal covariance matrix, a subcarrier and power allocation scheme is proposed to meet the power requirement of the DFRC system. Simulation results show that compared with the traditional OFDM based DFRC scheme, the proposed scheme can achieve almost the same target detection performance, and a much higher achievable data rate. Meanwhile, the proposed scheme can guarantee that the power radiated in the communication direction satisfies the communication power requirement.

关键词： Wireless communication OFDM Simulation Radar Receivers Object detection Convex functions

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An Intelligent Indoor Localization System in the NLOS Environment Based on Deep Learning and CSI Images

An Intelligent Indoor Localization System in the NLOS Enviro...

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International Conference on Wireless Communications and Signal Processing (WCSP)

作者： Lu Sun Liang Wu Zaichen Zhang Jian Dang Yulong Shen Gefeng Huang Liliang Ding National Mobile Communications Research Laboratory Southeast University Nanjing P.R.China Purple Mountain Laboratory Nanjing P.R.China State Key Laboratory of Smart Grid Protection and Control NARI Group Co. Ltd Nanjing China

ISBN: (纸本)9781665450867

With the rapid development of the smart service industry, indoor high-precision localization technology in the non-line-of-sight (NLOS) environment has attracted great interest. Fingerprint-based indoor localization has been widely employed due to its low hardware cost and high localization accuracy. In this paper, we propose an indoor intelligent localization system based on a 2-dimensional deep convolutional neural network (2D DCNN) and image fingerprints extracted from the channel state information (CSI). Simulation results show that the proposed localization system can achieve a high localization accuracy in the NLOS environment.

关键词： Location awareness Deep learning Wireless communication Simulation Signal processing algorithms Fingerprint recognition Signal processing

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Developing Characteristics of Oil-immersed Transformer Internal Fault with Dignostic Method Using Convergence Patterns of Free Gas

Developing Characteristics of Oil-immersed Transformer Inter...

引用

Electrical Engineering (CIYCEE), IEEE China International Youth Conference on

作者： Yucheng Zhang Zhiguo Hao Yuping Zheng Shuyan Pan Boyu Li Zhongxin Xue Jinzhao Deng School of Electrical Engineering Xi’an Jiaotong University Xi’an China State Key Laboratory of Smart Grid Protection and Operation Control Nanjing China

ISBN: (纸本)9781665400657

Light gas protection only operates when gas within the transformer collection chamber reaches threshold volume. Such criterion failed to reflect transformer conditions accurately due to the lack of understanding for defect developing process and corresponding gas generation- convergence pattern, which has led to lower protection reliability and has caused several transformer explosions. To address current problem, an experimental tank with structure resembling that of a power transformer is set up, inside which the needle-plate oil-pressboard breakdown model is planted. Experimental results indicate that throughout fault development, voltage drops became more frequent until arcing occurs, so is HFCT signal; meanwhile gas generation rate increases through slight partial discharge, spark discharge and arcing stage, the collected gas volume corresponds with patterns above. The purpose of this study is to clarify the defect developing process and the gas generation-convergence pattern for oil-immersed transformer internal fault in guidance for a more reliable protection method.

关键词： Surface discharges Windings Oil insulation Discharges (electric) Reliability Sparks Plastics

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A Flow-Guided Anomaly Detection Method For Substation Equipment in Changing Scenarios

A Flow-Guided Anomaly Detection Method For Substation Equipm...

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Chinese Automation Congress (CAC)

作者： Qingwei Zhang Jing Wang Peng Wang Wenhao Zhou Yingxuan Li Chunhui Zhao State Key Laboratory of Smart Grid Protection and Control NARI Technology Development Company Limited Nanjing China Stale Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University Hangzhou China

ISBN: (纸本)9781665426480

The anomaly detection for substation equipment is of great significance to maintain the safe operation of substations. With the development of deep learning, many anomaly detection methods based on deep convolutional neural networks (CNN) have been proposed. However, the challenge lies in the diversity of the environment and the variety of anomaly types in the substation. This paper proposes a Flow- Guided Anomaly Detection Method, which contains a data augmentation module and a flow-guided feature fusion module. The data augmentation module utilizes CycleGAN to transfer the style of the images to adapt to changing scenarios, such as different illumination and season conditions. The flow-guided feature fusion module extracts the optical flow between the test image and the template image by a pre-trained FlowNet, which represents the change information between the image pair and is universal for different anomaly types. Then the appearance information and change information of the image are aggregated to obtain the fused feature, which contains more semantic information. Finally, the fused feature is utilized to accurately detect a wider range of abnormal types. Experiments show that our proposed method has superior performance in anomaly detection for substation equipment and is more robust to changing scenarios.

关键词： Deep learning Adaptation models Substations Fuses Semantics Lighting Feature extraction

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