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4th International Conference on Machine Learning and intelligent Communications, MLICOM 2019

作者： Shao, Baozhu Song, Chunhe Wang, Zhongfeng Li, Zhexi Yu, Shimao Zeng, Peng Liaoning Electric Power Research Institute State Grid Liaoning Electric Power Co. Ltd. 110000 Shenyang China Key Laboratory of Networked Control Systems Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110016 China Shenyang Power Supply Company State Grid Liaoning Electric Power Co. Ltd. 110000 Shenyang China

ISBN: (纸本)9783030323875

Sensor-based condition monitoring systems are becoming an important part of modern industry. However, the data collected from sensor nodes are usually unreliable and inaccurate. It is very critical to clean the sensor data before using them to detect actual events occurred in the physical world. Popular data cleaning methods, such as moving average and stacked denoise autoencoder, cannot meet the requirements of accuracy, energy efficiency or computation limitation in many sensor related applications. In this paper, we propose a data cleaning method based on multi-sensor spatiotemporal correlation. Specifically, we find out and repair the abnormal data according to the correlation of sensor data in adjacent time and adjacent space. Real data based simulation shows the effectiveness of our proposed method. © 2019, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Sensor nodes

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Chinese Named Entity Recognition in power Domain Based on Bi-LSTM-CRF

Chinese Named Entity Recognition in Power Domain Based on Bi...

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作者： Zhenqiang Zhao Zhenyu Chen Jinbo Liu Yunhao Huang Xingyu Gao Fangchun Di Lixin Li Xiaohui Ji School of Information Engineering China University of Geosciences Beijing Key Laboratory of Research and System Evaluation of Power Dispatching Automation Technology(China Electric Power Research Institute) Big Data Center State Grid Corporation of China Power Dispatching and Control Center State Grid Corporation of China Institute of Microelectronics Chinese Academy of Sciences

Efficient recognition of proprietary entities is an important basic work for text data mining and intelligent application in power *** power domain Named Entity Recognition(NER) methods rely on feature engineering seriously,which unable to learn power entity features *** order to learn entity features automatically and extract power domain named entities efficiently,a model based on Bidirectional Long Short-Term Memory Neural Networks(Bi-LSTM) and Conditional Random Field(CRF) was proposed in this *** representations were fed into the neural networks as an additional feature and Skip-gram embeddings were trained on power domain *** results showed the precision rate reaches higher than 88.25% and the recalling rate reaches higher than 88.04%,which confirm the method based on BiLSTM and CRF is effective for named entity recognition in the power domain.

关键词： Named Entity Recognition power Domain Bi-LSTM CRF

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power System Small-signal Stability Assessment Model Based on Residual Graph Convolutional Networks

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Journal of Physics: Conference Series 2021年第1期2095卷

作者： Yinsheng Su Mengxuan Guo Haicheng Yao Lin Guan Jiyu Huang Siting Zhu Zhi Zhong Department of Power System Operation China Southern Power Grid Guangzhou China School of Electric Power South China University of Technology Guangzhou China Guangdong Provincial Key Laboratory of Intelligent Operation and Control for New Energy Power System Guangzhou China

Small-signal stability (SSA) is important to power system security. A data-driven approach is established for rapid prediction of the power system oscillation characteristics. The key of the approach is the Graph Convolution Networks (GCN) with residual mechanism, which works to aggregate features from high-dimension steady-state operation information and is denoted as ResGCN (RESidual GCN) in the paper. The residual mechanism helps to overcome the network degradation phenomenon. Both the oscillation frequency and damping ratio of multiple modes can be predicted by the proposed model. The performance of the proposed scheme as well as its adaptability to the power system topological changes is verified on the IEEE 39 Bus system.

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Day-Ahead Scheduling of Distribution Level Integrated Electricity and Natural Gas System Based on Fast-ADMM With Restart Algorithm

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IEEE ACCESS 2018年 6卷 17557-17569页

作者： Chen, Jian Zhang, Weitong Zhang, Yicheng Bao, Guannan Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Minist Educ Jinan 250061 Shandong Peoples R China Nanyang Technol Univ Sch Elect & Elect Engn Singapore 639798 Singapore State Grid Shandong Elect Power Dispatching & Con Jinan 250001 Shandong Peoples R China

power generated by the natural gas (NG) is a promising option for solving the restrictions on the development of the power industry. Consequently, the high interdependence between NG network and electricity network should be considered in this integration. In this paper, a day-ahead scheduling framework of integrated electricity and NG system (IENG) is proposed at a distribution level based on the fast alternating direction multiplier method with restart algorithm considering demand side response and uncertainties. Within the proposed framework, the detailed model of the IENG system at a distribution level is established, where the NG flow equation is processed by incremental linearization method to improve the computational efficiency. The objective is to minimize the operation costs of the entire system. With consideration of the uncertainties of distributed generation and electricity load as well as the uncertainties from the NG load, a two-stage robust optimization model is introduced to obtain the worst case within the uncertainty set, which is solved by column and constraints generation algorithm. In addition, the demand-side response (DSR) model including the decentralized air conditioning (AC) load model and the centralized ice-storage AC load model is integrated into the scheduling framework. Finally, the proposed day-ahead scheduling framework is verified by numerical studies where the optimal scheduling schemes are obtained in different cases, both the effects of the uncertainties and the performance with introducing DSR to the system operation are analyzed.

关键词： Day-ahead scheduling demand-side response (DSR) integrated electricity and natural gas system (IENG) natural gas (NG) uncertainty

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Design of Overall Framework of Self-Service Big Data Governance for power grid 4th

Design of Overall Framework of Self-Service Big Data Governa...

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4th International Conference on Machine Learning and intelligent Communications, MLICOM 2019

作者： Qiao, Lin Zhou, Qiaoni Song, Chunhe Wu, Hao Liu, Biqi Yu, Shimao State Grid Liaoning Electric Power Co. Ltd. Shenyang110000 China Key Laboratory of Networked Control Systems Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110016 China

ISBN: (纸本)9783030323875

At present, power grid companies have not formed a complete data quality control system and a comprehensive and effective data quality assurance mechanism, which restricts the deep mining of data value. In this paper, based on the full-service unified data center of power grid Company, a general framework of self-service power grid big data governance is presented. Firstly, the related work of big data governance is reviewed;secondly, the architecture and characteristics of the grid company’s full-service unified data center are analyzed;thirdly, the related requirements of self-service grid big data governance are analyzed;fourthly, the overall framework of self-service grid big data governance is proposed. Compared with other general big data governance framework, the proposed framework considers the specification of power grid as well as the features of self-service, making the framework more feasible. © 2019, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Big data

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A Data Quality Improvement Method Based on the Greedy Algorithm 4th

A Data Quality Improvement Method Based on the Greedy Algori...

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4th International Conference on Machine Learning and intelligent Communications, MLICOM 2019

作者： Wang, Zhongfeng Fu, Yatong Song, Chunhe Ge, Weichun Qiao, Lin Zhang, Hongyu Key Laboratory of Networked Control Systems Shenyang Institute of Automation Chinese Academy of Sciences Shenyang110016 China Institutes for Robotics and Intelligent Manufacturing Chinese Academy of Sciences Shenyang110016 China State Grid Liaoning Electric Power Co. Ltd. 110000 Shenyang China

ISBN: (纸本)9783030323875

High-quality data is very important for data analysis and mining. Data quality can be indicated by many indicators, and some methods have been proposed for data quality improvement by improving one or more data quality indicators. However, there is few work to discuss the impact of the processing order of data quality indicators on the overall data quality. In this paper, first, some data quality indicators and their improvement methods are given;second, the impact of the processing order of data quality indicators on the overall data quality is discussed, and then a novel data quality improvement method based on the greedy algorithm is proposed. Experiments have been shown that the proposed method can improves the data quality while reducing the time and computational costs. © 2019, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering.

关键词： Data reduction

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Method for Single-phase Electric Meter Phase Discrimination Based on Multiple Linear Regression

Method for Single-phase Electric Meter Phase Discrimination ...

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

作者： Liqiang Zhang Wei Cong Gang Dong Yun Sun Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan China State Grid Shandong Electric Power Company Jinan China

ISBN: (数字)9781728117225

ISBN: (纸本)9781728117232

The phase information of single-phase electric meter is crucial to improve the level of load management and the quality of modeling. A method for single-phase electric meter phase discrimination based on multiple linear regression (MLR) is proposed. The MLR equation takes the single-phase electric meter voltage as the dependent variable. Meanwhile, it takes the gateway meter voltage, the gateway meter current and the single-phase electric meter current as the independent variables. Each single-phase meter forms a regression equation with the gateway meter A, B and C respectively. The determination coefficients of the three regression equations are calculated. According to the value of the coefficients, the phase of single-phase electric meter is discriminated. An example is given to analyze the proposed method with actual energy meter reading data. The analysis results show that the proposed method has higher accuracy and reliability.

关键词： Meters Mathematical model Logic gates Voltage measurement power supplies Correlation power measurement

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An improved fault recovery strategy for active distribution network considering LVRT capability of DG

An improved fault recovery strategy for active distribution ...

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8th Renewable power Generation Conference (RPG 2019)

作者： Yongji Cao Weisheng Liu Yi Zhang Hengxu Zhang Key Laboratory of Power System Intelligent Dispatch and Control of the Ministry of Education (Shandong University) Jinan China State Grid Shandong Electric Power Company Jinan China

ISBN: (数字)9781839531248

ISBN: (纸本)9781839531255

The growing integration of distributed generation (DG) has changed the operation characteristics of traditional distribution network, and so the active distribution network (ADN) has emerged. Fault recovery is significant to reduce the loss of power failure, but the traditional control strategy without consideration of DG is no longer suitable for ADN. An improved fault recovery strategy is proposed to coordinate the fault reclosing and the low voltage ride through (LVRT) capability of DG. The influence of fault reclosing on the voltage variation of the point of common coupling (PCC) of DG is analyzed, with different relative locations of fault and PCC, and a critical LVRT voltage is extracted from the scenario where fault reclosing fails. In order to avoid DG outage, a blocking criterion of fault reclosing is presented according to the fault location and the first voltage dip of PCC. Then, the ADN can be split into planned islands considering the balance of DG power and loads and the load priorities, once the fault reclosing is blocked. Moreover, the WAMS Light is implemented for high-speed synchronous data collection and online central control. A case study is conducted to verify the effectiveness of proposed approach.

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A Distribution System State Estimation Analysis Considering the Dynamic Load Effect

A Distribution System State Estimation Analysis Considering ...

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IEEE-Region-10 Conference (IEEE TENCON)

作者： Zhang, Bing Ma, Linlin Liu, Xiaoliang Liu, Guanhong Yang, Wenjia Ma, Xianli Yang, Kun Liu, Qian Wang, Chen Wang, Xiaohui State Grid Shandong Elect Power Co Power Dispatching Control Ctr Shandong Elect Power Co Jinan Shandong Peoples R China State Grid Shandong Elect Power Co Weifang Power Supply Co Weifang Peoples R China Shandong Univ Key Lab Power Syst Intelligent Dispatch & Control Jinan Shandong Peoples R China

ISBN: (纸本)9781538654576

the reliable state awareness of modern distribution system relies on advanced measurement system, well-adapted calculation method as well as a better understanding of load and embedded power source. State estimator, as the most important tool to achieve real-time state awareness must take load model into consideration. In this paper, the ERL (Exponential Recovery Load) model is utilized to grasp the dynamic property during the disturbance periods. The proposed SE procedure is detailed in this paper and a simulation case with IEEE-33-bus system is conducted to verify the effectiveness.

关键词： State Estimation distribution system WLS dynamic load model ERL

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Fault location determination method for relay protection communication system based on power grid operation and maintenance multi-source data

Fault location determination method for relay protection com...

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Sustainable power and Energy Conference (iSPEC)

作者： Bozhong Pan Wei Cong Mengchen Sun Jiang Yu Maoran Zheng Key Laboratory of Power Grid Intelligent Dispatch and Control Ministry of Education(Shandong University) Jinan China State Grid Tianjin Electric Power Company Tianjin China China Southern Power Grid Co. Ltd. Guangzhou China

Multi-channel simultaneous warning events of the fiber-optic communication system which supporting the relay protection service are frequently transmitted. Due to the large number of warning information, it is difficult to determine the fault location of protection channel accurately. Based on the multi-source data of power grid operation and maintenance, a Bayesian network model is adopted to propose a fault location determination method for relay protection communication system. Based on the warning information of the RPMS (Relay Protection Management System) and the communication network management system, combined with the OMS (Operation Management System) information, the fault area is first identified to narrow the fault location judging range, and then the historical operation and maintenance data are used in the fault area. Obtained prior probability, the fault probability calculation is carried out by the improved Bayesian algorithm, inferred the cause of fault, and the fault location is judged by the communication resource management system information. The results of the example analysis prove the validity and accuracy of the proposed method. The method is also applicable to multi-region concurrency fault location determination.

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