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A Frequency control Model for Cyber Physical Power System Considering Demand Response Strategy

Energy Procedia 2018年 145卷 38-43页

作者： Ni Ming Chen Qian Li Manli Wang Qi Tang Yi NARI Group Corporation(State Grid Electric Power Research Institute) Nanjing 211106 China NARI Technology Co. Ltd. Nanjing 211106 China State Key Laboratory of Smart Grid Protection and Control Nanjing 211106 School of Electrical Engineering Southeast University Nanjing 210096 China

Due to the increase of power transmission capacity, once an active power vacancy happens, power systems will face a serious frequency instability problem. With the development of communication technology in cyber physical power system (CPPS), demand response (DR) resources can take the initiative to reduce electricity utilization in order to tackle the system under-frequency challenge. This paper presented a frequency control model for CPPS considering DR strategy to rapidly forecast the effects of DR sources participating in frequency control. The model was verified through a case study as well.

关键词： load frequency control(LFC) cyber physical power system demand response

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Status evaluation of smart substation measurement and control device

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IOP Conference Series: Materials Science and Engineering 2019年第4期563卷

作者： Zhang Min Shen Jian Chen Li Zhou Bin Zhou Shao Liang Hou Zhe NARI Group Corporation (State Grid Electric Power Research Institute) Nanjing China State Key Laboratory of Smart Grid Protection and Control Nanjing China NARI Technology Corporation Co. Ltd Nanjing China

In power system, measurement and control device plays an important role in maintaining an ideal level of reliability. Therefore, the reliability of the measurement and control device should be evaluated to fully understand the cause of its failure. A new evaluation model is proposed, which relates the fault of measurement and control system with the four main reasons of device hardware fault, software fault, auxiliary equipment fault and human fault. In addition, the model can also comprehensively consider other aspects of the measurement and control system, such as human error in testing and software upgrade, effectiveness of daily operation monitoring, degree of dependence on self-inspection, local backup and misoperation. These studies have a lot of significance to the reliability of the control system, and also can effectively improve the stability of the system.

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Design and Implementation of Integrated Service Penetration Technology Cross Security Region

Design and Implementation of Integrated Service Penetration ...

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IEEE Conference on Energy Internet and Energy System Integration (EI2)

作者： Qiang Yi Shupeng Wan Kai Zhang Peng Chen Hailong Guo Baoshan Gao System R&D Center NARI Group Corporation NARI Technology Co. Ltd Nanjing China System R&D Center State Key Laboratory of Smart Grid Protection and Control Nanjing China

In the power dispatching automation system, production control security region and management information security region adopt forward and backward isolation devices for physical isolation, with the enhancement of the functional relevance between the security regions and the expansion of the system functions, one-way synchronization of production control security region to management information security region has been unable to meet the requirements of application expansion of supervisory control. In accordance with the principles of safety protection standards, it is urgent to establish a data transmission mechanism that can cross the forward and backward isolation, realize service penetration cross the security region. In this paper, a scheme of integrated service invocation across the security region is proposed, which can be invoked by the service bus that can be transparent and unaware service bus, encapsulate cross domain service protocol, establish virtual access, and complete service invocation. Through the signature verification technology, the service message is tampered in the communication, the communication security of the service invocation is guaranteed, the rights of the service are obtained through the authorization and the security of the service invocation cross the security region. The integrated service invocation technology cross the security region has been applied in Jiangsu Province, Beijing and Hangzhou. It provides a safe and stable support for the construction of the grand operation system, and provides a powerful guarantee for the efficient operation of the power grid.

关键词： Security Production control Power systems Safety Servers Synchronization Dispatching

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A Deep Learning Based Real-time Load Forecasting Method in Electricity Spot Market

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Journal of Physics: Conference Series 2019年第6期1176卷

作者： Qipei Zhang Jixiang Lu Zhihong Yang Mengfu Tu Nari technology co ltd. Nanjing 211106 China State Key Laboratory of Intelligent power grid protection and operation control Nanjing 211106 China

This paper analyzes the potential influence in Chinese electricity market due to the reform and access of the electricity spot market. On this occasion, a deep learning based model for load forecasting is proposed to improve the market operator's precise scheduling level and assist power retailers in managing bid strategies. Long-Short Term Memory (LSTM) unit is used to modeling, which is one of the most popular techniques of deep learning. In addition, historical power load data and meteorological data of Suzhou and Lianyungang in China from January 2015 to December 2017 are used for the study to training and evaluate forecasting model. As a result, this paper shows the compare results with exiting machine algorithm for load forecasting.

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Reliability analysis of security and stability control systems with remote redundancy in power systems

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IOP Conference Series: Earth and Environmental Science 2019年第3期227卷

作者： Xijian Dong Heping Jia Bijun Li Chao Huo Feng Xue Jianbo Luo Xianbo Ke NARI Group Corporation (State Grid Electric Power Research Institute) Nanjing 211106 China State Key Laboratory of Smart Grid Protection and Control Nanjing 211106 China College of Electrical Engineering Zhejiang University Hangzhou 310027 China Northwest Division of State Grid Corporation of China Xi'an 710048 China.

During the transition period of UHV AC/DC power grid construction in China, the dependence of the secure and reliable operation of power grids on the security and stability control system (SSCS) has been greatly enhanced. SSCS has shown a trend of large-scale, wide-area and complex in recent years. Considering the high reliability requirements of large-scale SSCS, the necessity of redundant configuration of important sites is first outlined in this paper. Moreover, the reliability indices including mis-operation rate and rejection rate of SSCS with and without remote redundancy are analyzed as well as the relationship between reliability indices and failure rate of single device. The key research directions of the reliability research of the SSCS under the new situation are further pointed out.

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Research and Application of Trans-Regional Cooperative Disposal of UHV Interconnected Power grid 3

Research and Application of Trans-Regional Cooperative Dispo...

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2017 3rd IEEE International Conference on control Science and Systems Engineering (ICCSSE)

作者： Shan Xin Jiang Yefeng Wu Li Jin Yiding Wang Yiyu Lu Jinjun NARI Group Corporation NARI Technology Co.Ltd State Key Laboratory of Smart Gird Protection and Control Jiangsu Electric Power Company of State Grid of China National Electric Power Dispatching and Control Center State Grid Corporation of China

ISBN: (纸本)9781538604854

With the rapid construction of UHV AC/DC power grid, the integration characteristics of power grid are becoming more and more prominent, and real-time operation control of dispatching is significantly becoming more and more difficult. The existing monitoring and control model based on the system model data cannot meet the requirements for the development of UHV power grid. Based on the existing achievements of dispatching automation system, the general goal and framework of the trans-regional cooperative disposal of UHV interconnected power grid are put forward, and the key technologies are analyzed in four aspects: situation awareness, fault location, joint disposal and cooperative control to provide reference and example for follow-up construction for real-time control and support system for the dispatching of UHV power grid.

关键词： UHV situation awareness cooperative disposal source grid load wide area graphic browsing DC fault diagnosis

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Research on Identification Method of Transformer Based on Improved Hu Invariant Moments

Research on Identification Method of Transformer Based on Im...

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International Conference on Mechatronics and Intelligent Robotics, ICMIR 2017

作者： Yu, Hua-dong Ou, Qing-hai Wu, Qing Zhang, Zhe Li, Wen-jing Wang, Yubo Liu, Guohua Lu, Yongling Hu, Chengbo Liu, Na Wang, Rong State Grid Information and Telecommunication Group Co. Ltd. Beijing China State Grid Key Laboratory of Power Industrial Chip Design and Analysis Technology Beijing Smart-Chip Microelectronics Technology Co. Ltd. Beijing100192 China Beijing Engineering Research Center of High-Reliability IC with Power Industrial Grade Beijing Smart-Chip Microelectronics Technology Co. Ltd. Beijing100192 China State Grid Jiangsu Electric Power Company Research Institute Nanjing21110 China Control and Computer Engineering College North China Electric Power University NCEPU Beijing China

ISBN: (纸本)9783319709895

With the rapid development of electric power industry and the expansion of power grid scale, more and more attentions have been paid to the safe operation of electrical equipment. The target recognition method we used now couldn’t recognize power transformer well, which is based on gray information. In this paper, a transformer identification algorithm based on improved Hu moment invariants is proposed. The transformer identification algorithm proposed in this paper has the advantages of good recognition effect and high recognition accuracy. The correctness and feasibility of the proposed algorithm have been verified by experiments. © 2018, Springer International Publishing AG.

关键词： Template matching

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Self-Healing smart grid system based on artificial neural network

Self-Healing smart grid system based on artificial neural ne...

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2017 IASTED International Conference on Modelling, Identification and control, MIC 2017

作者： Li, Chen Wei, Qi Jian, Shen Zhe, Hou NARI Group Corporation State Grid Electric Power Research Institute Nanjing211106 China NARI Technology Co Ltd Nanjing211106 China State Key Laboratory of Smart Grid Protection and Control Nanjing211106 China Hangzhou Xiao Shan China Power Supply Company China

ISBN: (纸本)9780889869882

In this paper, a novel logic decomposing method in self-healing smart grid system based on neural networks is presented and the theoretical fundamentals of the design are expounded. The proposed automatic smart grid topology search algorithm, which is based on artificial neural network (ANN), realizes the adaptive function of analyzing and updating the self-healing system logic in the grid automatically. Furthermore, the configuration design in a neural network mode makes the system have the parallel processing mechanism and the ability of learning and fault decision-making. The outlet of protection is transferred from the neural networks by adjusting the connecting weights. Therefore, the system can classify and recognize arbitrarily complex connecting mode and acting logic.

关键词： Neural networks

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Online Identification of Transient Stability and Unstable Generators Based on Deep Learning

Online Identification of Transient Stability and Unstable Ge...

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IEEE Conference on Energy Internet and Energy System Integration (EI2)

作者： Yanzhen Zhou Qiang Liu Qinglai Guo Hongbin Sun Xianyu Zha Feng Xue Wenlu Zhao Chen Li Zhijian Zhang Liangliang Hao Department of Electrical Engineering Tsinghua University Beijing China State Key Laboratory of Smart Grid Protection and Control State Grid Electric Power Research Institute Jiangsu China State Grid Xinyuan Maintenance Branch State Grid Xinyuan Company Ltd. Beijing China State Grid Beijing Electric Power Dispatching and Control Center Beijing China School of Electrical Engineering Beijing Jiaotong University Beijing China

Machine learning methods have been considered as a promising method for online transient stability analysis. This paper presents a deep learning approach for transient stability prediction and unstable generator identification based on convolutional neural networks (CNNs). The post-disturbance dynamic responses of all the generators are utilized as the input features. A binary classification CNN model is generated for transient stability prediction. And a multi-class classification CNN model is built for unstable generator identification. Moreover, the multi-class CNN model can provide the unstable probability of each generator using the probability outputs and the label information. Comprehensive studies are conducted on the New England 10-machine 39-bus system to verify the effectiveness of the proposed approach.

关键词： Generators Power system stability Stability analysis Transient analysis Predictive models Thermal stability

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Ultra-short-term wind speed forecasting method based on spatial and temporal correlation models

Ultra-short-term wind speed forecasting method based on spat...

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6th International Conference on Renewable Power Generation

作者： Zhou, Haiqiang Xue, Yusheng Guo, Jizhu Chen, Jiehui Energy and Electrical Engineering School Hohai University Nanjing Jiangsu Province211100 China NARI Group Corporation State Grid Electric Power Research Institute Nanjing211106 China State Key Laboratory of Smart Grid Protection and Control Nanjing211106 China

An ultra-short-term wind speed forecasting method based on spatial and temporal correlation models is proposed. Firstly, the temporal correlation model was studied. The generalised distance of wind speed time series is defined based on the dynamic time warping distance and correlation coefficient. Samples with similar wind dynamic patterns are classed into the same group. Time series in one group are depicted with a representative time series which is modelled by an autoregressive moving average (ARMA) model. For time series which cannot be classed to any of these groups, a special group was defined. It was modelled by artificial neural network (ANN). Secondly, the spatial correlation between the target wind farm and the reference wind farm was investigated with the meteorological data taking into consideration. The grey prediction method is utilised to predict the wind speed. Finally, the combined ultra-short-term wind speed forecasting method is proposed. It takes into account the inherent time correlation of the target wind speed and its spatial correlation with reference wind farm. The wind speed prediction of wind farms in northwest USA verifies the effectiveness and feasibility of the proposed method. © 2017 Institution of Engineering and Technology. All rights reserved.

关键词： Time series

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