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5th IEEE Conference on Energy Internet and Energy System Integration, EI2 2021

作者： Chen, Xuetong Huang, Jie Jin, Shuai Zhang, Yifei Ling, HengYu NARI Technology Co. Ltd. State Key Laboratory of Smart Grid Protection and Control Nanjing China

ISBN: (纸本)9781665434256

Mitigating climate change is a global consensus. C hina is aiming to have carbon emissions peak before 2030 and ac hieve carbon neutrality before 2060. The China national carbon market is one of the key measures to achieve this ambitious "30 •60" target. Compliance enterprises, financial institutions, and i ndividual investors are allowed to participate in the national car bon market and the complex trading interactions among these h eterogeneous participants will make the market dynamics diffic ult to predict and analyze, bringing challenges to market design and regulations. Guided by the framework of cyber-physical-soc ial system in energy (CPSSE), this paper constructs a hybrid si mulation environment based on the Dynamic Simulation platfor m for Macro-Energy Systems (DSMES), in order to study the he rding behavior effects on carbon market under different scenari o settings. The behavior models of different carbon traders such as compliance enterprises, offset developers and financial instit utions are analyzed and constructed. Then, the herding behavio reffects are studied under different market scenario settings sue has the supply of carbon emission allowance (CEA) and carbon offset credits (COC). Finally, key insights are discussed based o nmulti-scenario case studies, which provide decision support fo rmarket design and regulation. © 2021 IEEE

关键词： Climate change

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Design and Verification of a DC Direct-mounted Energy Storage Topology

Design and Verification of a DC Direct-mounted Energy Storag...

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IEEE Information Technology, Networking, Electronic and Automation control Conference

作者： Junwei Huang Wujie Chao Chaoping Deng Liyu Dai Jinke Wang Electric Power Research Institute of State Grid Fujian Electric Power Co. Ltd. Fuzhou China Fujian Key Laboratory of Smart Grid Protection and Operation Control Fuzhou China

ISBN: (数字)9798350370805

ISBN: (纸本)9798350370812

The modular multilevel converter based battery energy storage system (MMC-BESS) has the problem of pulsating current affecting battery life, and the high cost of retrofitting traditional modular multilevel converter (MMC) stations. The proposed DC direct-mounted energy storage topology in this paper is battery friendly and required number of battery cells is only 1/6 of MMC-BESS, greatly saving costs. This paper analyzes the topology structure and working principle of DC direct-mounted energy storage devices, and proposes a design method for the DC direct-mounted energy storage devices. The proposed design method is validated through simulation and prototype experiments. The simulation and construction of a DC 750V prototype have verified that the prototype has achieved good charging and discharging functions for DC energy storage, with small fluctuations in DC grid connected current and good power control effect. This study can provide reference and guidance for the design and application of high-voltage and high-capacity direct current energy storage devices that support offshore wind power to move towards the deep sea in the future.

关键词： Multilevel converters Fluctuations Costs Power control Prototypes High-voltage techniques Wind power generation Topology Batteries Energy storage

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An Feature Data Extraction Method Based on BPCA-SPCA

An Feature Data Extraction Method Based on BPCA-SPCA

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International Conference on Sensing, Diagnostics, Prognostics, and control (SDPC)

作者： Xiangyu Xing Bingrong Yan Yan Su Lingyun Tang College of Civil Aviation Nanjing University of Aeronautics and Astronautics Nanjing China Nari Group Corporation State Key Laboratory of Smart Grid Protection and Control Nanjing China

ISBN: (数字)9798350388855

ISBN: (纸本)9798350388862

With the increasing integration of systems and the rapid development of sensor monitoring technology, the types of monitoring data are more diverse and the number of samples are larger in flight test and operation than before. Due to the large volume and high complexity of monitoring data, the system fault diagnosis and prediction based on monitoring data is inefficient. In order to solve the problem of monitoring data redundancy, a feature extraction algorithm based on BPCA-SPCA is proposed. A system with high failure rate is selected as an example to extract the features of the system monitoring data and realize the verification of data sparseness. The experimental results show that based on BPCA-SPCA the principal components extracted monitoring data can effectively express the features of the original data, and the feature sparse vector can provide effective input information for subsequent fault diagnosis and indirectly improve the efficiency of fault diagnosis.

关键词： Fault diagnosis Redundancy Feature extraction Prediction algorithms Vectors Inference algorithms Sensors Complexity theory Data mining Monitoring

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Comparison of Adaptive Virtual Impedance Coefficient to Suppress Power Oscillation in Multi-VSG grids

Comparison of Adaptive Virtual Impedance Coefficient to Supp...

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IEEE PES Asia-Pacific Power and Energy Engineering Conference (APPEEC)

作者： Jie Ji Xingshuo Li Shuye Ding Yizhi Chen School of Electrical and Automation Engineering Nanjing Normal University Nanjing China State Key Laboratory of Smart Grid Protection and Control Nari Group Corporation Nanjing China

ISBN: (数字)9798350386127

ISBN: (纸本)9798350386134

The virtual synchronous generator(VSG) technology offers inertia support but also introduces active power oscillation, which are more serious when in multi-VSG. The previous studies proposed adaptive virtual impedance aimed at suppressing power oscillation in multi-VSG system. However, further research is still needed to thoroughly examine the adaptive virtual impedance coefficient. In this article, how the power oscillation of multi-VSG to be influenced by adaptive virtual impedance coefficient is investigated. Firstly, an analysis is conducted on the active power oscillation mechanism. Subsequently, the variation law of adaptive virtual impedance coefficient affecting active power oscillation is studied. Finally, The effects of different adaptive virtual impedance coefficient values is compared in simulations and experiment.

关键词： Adaptation models Adaptive systems Impedance Frequency synchronization Oscillators Frequency control

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Research on Construction of Dispatching Knowledge Model of Power grid 5

Research on Construction of Dispatching Knowledge Model of P...

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5th International Conference on Energy, Electrical and Power Engineering, CEEPE 2022

作者： Qing, Zheng Dai, Zemei Zhu, Nanyang Yang, Chunxiang Si, Xiaofeng Zhang, Kaifeng Southeast University School of Automation Nanjing China Nari CO.LTD & Nari Technology CO.LTD State Key Laboratory of Intelligent Power Grid Protection and Operation Control Nanjing China State Grid GanSu Electric Power Company Gansu China

ISBN: (纸本)9781665479059

With the construction of the new power market, the tasks of dispatching operation in the power grid become more frequent, and the scenes of dispatching operation are more complicated. The existing dispatching operation system and the technology of decision in power grid cannot meet the requirements. Therefore, this work establishes a knowledge model of power grid dispatching to provide an efficient decision-making tool. This work extracts the benefits of historical operation scenarios and the regulation of dispatching of power grid, and establishes a joint knowledge model of power grid dispatching based on mining and extracting the benefits of historical operation scenarios and the regulation of dispatching of power grid by big data analysis technology and natural language processing technology. The joint knowledge model is essential for dispatcher to formulate more reasonable dispatching operations, reduce the difficulty of decision-making and lower the requirements for dispatchers, which ensures the safe operation of the power grid. © 2022 IEEE.

关键词： Analytical models Decision making Dispatching Power grids Natural language processing Data models Regulation

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Digital Management and Application Platform for Security and Stability control Devices

Digital Management and Application Platform for Security and...

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Power and Energy (PandaFPE), Panda Forum on

作者： Fengjie Shen Jianbing Xu Yuqiang Hou Kang Zhao State Key Laboratory of Smart Grid Protection and Control NARI Group Corporation (State Grid Electric Power Research Institute) Nanjing China State Grid Shandong Electric Power Research Institute Jinan China

The management of massive security and stability control devices (SSCD) configured for power grids is relatively decentralized, and there is an urgent need for refinement and intensification. Focusing on the purpose of improving the reliability level of SSCD, and referring to the power grid digitization work plan, this paper constructs a digital management and application platform for SSCDs based on “running on the cloud platform+localization”. First, it introduces the platform positioning and overall framework, and then elaborates the business functions such as device management, version management, test management, evaluation and decision-making. This achieves digital management and reliability test evaluation of mass SSCDs, also improves the reliability level of SSCDs. Finally, illustrates the actual application effect of this platform in a laboratory.

关键词：

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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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2021 China Automation Congress, CAC 2021

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

ISBN: (纸本)9781665426473

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. © 2021 IEEE

关键词： Anomaly detection

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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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2021 China Automation Congress, CAC 2021

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

ISBN: (纸本)9781665426473

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. © 2021 IEEE

关键词： Optical flows

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Capacitance Current Compensation Method for Cable-Overhead Hybrid Transmission Lines 5th

Capacitance Current Compensation Method for Cable-Overhead H...

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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： Yao, Gang Wu, Tonghua Zheng, Yuping Teng, Xianliang Hong, Feng Chen, Guozhou NARI Group Corporation Nanjing211106 China State Key Laboratory of Smart Grid Protection and Control Nanjing211106 China

ISBN: (纸本)9789811597459

At present, the capacitance current compensation technology for transmission line differential protection is based on uniform parameters of entire lines, so it cannot be adapted to cable-overhead hybrid transmission lines. In this paper, a steady-state compensation method based on segment parameters, a time-domain compensation method based on whole line equivalent parameters and a time-domain compensation method based on segment parameters are proposed, which can adapt to different application scenarios, such as hybrid lines with shunt reactance at the ends and junctions. A PSCAD/EMTDC simulation shows that when a hybrid transmission line is short, the time-domain compensation method based on whole line equivalent parameters is simple to implement, and it can effectively compensate the capacitance current of hybrid transmission lines. The time-domain compensation method based on segment parameters can accurately compensate the capacitance current of hybrid transmission lines, taking into account the reliability and sensitivity of differential protection. © 2021, Springer Nature Singapore Pte Ltd.

关键词： Cables

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Evaluation of Wind Power Acceptance Capacity Based on N-1 Static Voltage Stability Region

SSRN

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SSRN 2024年

作者： Shu, Hongchun He, Yefu Wang, Guangxue Shi, Botao Zhang, Hanxin Zaho, Zhixin State Key Laboratory Collaborative Innovation Center for Smart Grid Fault Detection Protection and Control Jointly Kunming University of Science and Technology Kunming China Yunnan Key Laboratory of Green Energy and Digital Power Measurement Control and Protection Faculty of Land Resource Engineering Kunming University of Science and Technology China

Wind power generation is random and volatile with significant seasonal characteristics. Large-scale grid-connected wind power has an impact on the static safety of the system, especially under N-1 fault conditions. Therefore, this paper proposes an evaluation method of wind power acceptance capacity based on N-1 static voltage stability region to assess the maximum wind power acceptance capacity of the system. To accurately describe the dynamic correlation and seasonal characteristics of wind power generation in adjacent wind farms, a wind power output model is established based on k-medoids clustering and dynamic Copula function. Then, the seasonal generated scene data replaces the original wind power data for acceptance capacity assessment. The N-1 static voltage stability region model for wind power access is established, and the characterization method of wind power access to the N-1 static voltage stability region is determined by targeting search, searching, and selecting the most serious N-1 state. Monte Carlo is utilized to simulate the mathematical model of wind power acceptance capacity evaluation under different seasons, and combined with the N-1 static voltage stability domain, the maximum wind power acceptance capacity curve of the system is obtained. To verify the effectiveness of the proposed method, the IEEE-30 system connected to wind power is taken as an example for simulation analysis. The results show that the proposed method can quickly evaluate the maximum wind power acceptance capacity in the N-1 state, providing a basis for the planning and operation of a new energy power system with practical significance. © 2024, The Authors. All rights reserved.

关键词： Power generation

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