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检索条件"机构=Key Laboratore of Power System Intelligent Dispatch and Control"

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SCD File Management and Parsing Method Based on Graph Database: ∗Note: Sub-titles are not captured in Xplore and should not be used

SCD File Management and Parsing Method Based on Graph Databa...

引用

2023 International Conference on power system Technology, powerCon 2023

作者： Gu, Qianshuo Cong, Wei Chai, Qingfa Wang, Ruimei Wang, Feng Li, Yiquan Shangdong University Key Laboratory of Power System Intelligent Dispatch and Control Jinan China Guangdong Power Grid Co. Ltd. Power Dispatching and Control Center Guangzhou China

ISBN: (纸本)9798350300222

Aiming at the low level of SCD file management in smart substation, a method of SCD file management and analysis based on graph database is proposed. First, the file structure and function model of SCD under the SCL model are analyzed, and analyzed into DOM structure tree. Then, the SCD knowledge graph was constructed, and the Neo4j graph database was used for storage, management and parsing. Python was used to implement the method, and the visibility and query performance of the method were tested. The results show that this method is helpful to the management of SCD files and can improve the efficiency of operation and maintenance staff. © 2023 IEEE.

关键词： Graph Databases

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Fault Identification of Secondary Equipment in the intelligent Substation 2

Fault Identification of Secondary Equipment in the Intellige...

引用

2022 2nd International Conference on intelligent power and systems, ICIPS 2022

作者： Huang, Jiayin Zhang, Chi Ding, Xiaobing Peng, Ye Gao, Honghui Gao, Zhanjun Liu, Zhao CSG Power Dispatching and Control Center China Southern Power Grid Guangzhou China Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Shandong University Jinan China

With the continuous expansion of the scale of the power system and the increasingly complex structure, the intelligent construction of the power grid continues to deepen and the construction scale of smart substations as the core part of the smart grid is also expanding. At present, higher requirements are put forward for the operation and maintenance of the secondary system of the smart substation. Therefore, the fault diagnosis of the secondary system of smart substations has become an important research direction for smart grid construction. This paper proposes a secondary system fault location method for smart substations. The method uses a search algorithm based on an adjacency list and skyline query to determine the fault area. This scheme is applicable when the fault information is complete or not. Compared with the method of using the neural network to directly locate the fault of the whole network components, the training scale of the neural network is reduced and the "uncritical"feature quantity is reduced for the fault location. It highlights the value of "key"feature quantities and effectively improves the accuracy of the fault location. © Published under licence by IOP Publishing Ltd.

关键词： Location

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Current Transformer Polarity Judgment Based on Line Parameter Fitting with Closing Transient Current 17th

Current Transformer Polarity Judgment Based on Line Paramete...

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17th Annual Conference of China Electrotechnical Society, CES 2022

作者： Gu, Qianshuo Cong, Wei Wang, Feng Li, Yiquan Key Laboratory of Power System Intelligent Dispatch and Control Shandong University Jinan250000 China Power Dispatching Control Center of Guangdong Power Grid Co. Ltd. Guangzhou China

ISBN: (纸本)9789819903566

In order to solve the problem of current transformer (CT) reverse connection in power system, this paper proposes a method to judge CT polarity by fitting line parameters with closing transient current. Firstly, the relationship between line parameters and current is studied by deducing the mathematical form of closing current. By using the least square method to fit the sampling values of closing current, the line parameters are obtained. Compare the fitted line parameters with the actual line parameters. If the fitting result is consistent with the actual result, the CT polarity is correct;If the fitting result is contrary to the actual result, the CT polarity is reverse. In order to improve the accuracy of least square fitting, this paper uses matrix pencil algorithm to extract waveform features and realize decoupling among line parameters. Then, the differential equation of closing current is modified, and the remaining parameters are fitted and solved by the least square method. Finally, considering different operating environment and closing angle, the above algorithm is simulated by PSCAD and MATLAB. The simulation results show that when some sampling points are offset, the line parameters fitted by the matrix pencil algorithm are still consistent with the actual parameters. Therefore, the matrix pencil algorithm effectively improves the stability of the method and meets the needs of practical engineering. © 2023, Beijing Paike Culture Commu. Co., Ltd.

关键词： Differential equations

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Mid-Iong Term Photovoltaic power Forecasting Method Considering Periodicity Characterization

Mid-Iong Term Photovoltaic Power Forecasting Method Consider...

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2024 IEEE IAS Industrial and Commercial power system Asia, I and CPS Asia 2024

作者： Zhuo, Minyi Yang, Ming Li, Peng Sun, Yi Liu, Rui Zheng, Zhijie Shi, Bingke Shandong University Key Laboratory of Power System Intelligent Dispatch and Control Jinan China Economic & Technology Research Institute State Grid Shandong Electric Power Company Power Grid Planning Research Department Jinan China

ISBN: (纸本)9798350352290

Accurate forecasting of mid-long term photovoltaic power plays a key role in site planning, operation scheduling and mid-long term plan development for new power system. Meanwhile, the uncertainty in solar power generation is a key factor influencing the precision of its forecasting. This paper proposes a mid-long term PV power forecasting method considering periodic characterization, which first obtains the key meteorological factors through the maximal information coefficient, and extracts the timing features through ARIMA model for mid-long term PV power periodic component prediction. Then the results obtained from above are inputted to the LSTM model, which is trained using raw data to obtain the final PV power prediction results with high accuracy. Validation is carried out through the model's RMSE, MAE and MAPE metrics and the comparison of the model's forecasting results with traditional GRU model. © 2024 IEEE.

关键词： Solar power generation

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Synchronization Stability Analysis of Wind Farms Integrated MMC-HVDC system

Synchronization Stability Analysis of Wind Farms Integrated ...

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2023 International Conference on power system Technology, powerCon 2023

作者： Li, Li Qin, Changlong Kan, Changtao Yang, Jialun Li, Guanqun State Grid Jinan Power Supply Company Jinan China Shandong University Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Jinan China

ISBN: (纸本)9798350300222

High-voltage direct current (HVDC) based on modular multilevel converter (MMC) is an efficient way to integrate wind farms. However, following short-circuit fault on transmission line, wind turbines (WTs) may lose synchronization with sending-end MMC. As a result, delivery and consumption of wind power are under risk. This paper investigates the mechanism of synchronous instability of wind farm integrated MMC-HVDC system under the severe grid faults. First, a synchronization stability model of the whole is stablished, the existing of stable equilibrium points (SEPs) and the damping characteristic of the whole system are analyzed. Then, a synchronization stability enhancement strategy is proposed based on the coordination of WT and MMC. Last, the effectiveness of proposed strategy is verified by time-domain simulation. © 2023 IEEE.

关键词： Transient analysis

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A Missing Data Imputation Method for Electricity Consumption Data Based on TCN-Attention with Mask Tokens 4

A Missing Data Imputation Method for Electricity Consumption...

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4th International Conference on Consumer Electronics and Computer Engineering, ICCECE 2024

作者： Mao, Yifeng Yang, Ming Li, Peng Ou, Zhujian Shandong University Key Laboratory of Power System Intelligent Dispatch and Control Jinan China State Grid Nantong Power Supply Company State Grid Jiangsu Electric Power CO. LTD. Nantong China

ISBN: (纸本)9798350384062

With the popularization of smart meters, power companies can collect massive amounts of data from users for non-invasive load detection, electricity theft detection, etc. However, due to faults in smart meters and abnormal communication, the dataset often has missing values, making it difficult for data-driven methods to be widely applied. In this paper, we propose an unsupervised learning method based on TCN-Attention to fill in customers' electricity consumption data. Firstly, we extract electricity consumption features through TCN. In order to improve the feature extraction capability, we introduce a channel attention mechanism to TCN. The attention mechanism makes TCN focus on the effective features in the data by assigning weights. Meanwhile, we use mask tokens to cover a certain proportion of data, forcing the proposed model to learn potential feature representations of the data during the training process. Finally, the features are restored to data through feedforward neural networks. An example is given to verify the effectiveness of the proposed method. © 2024 IEEE.

关键词： Smart meters

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Impact assessment for large-scale off-grid of renewable energy on weakly interconnected systems 6

Impact assessment for large-scale off-grid of renewable ener...

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6th IEEE International Electrical and Energy Conference, CIEEC 2023

作者： Li, Li Qin, Changlong Dong, Xin Qiao, Rongfei Yang, Jialun State Grid Jinan Power Supply Company Jinan China Shandong University Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Jinan China

ISBN: (纸本)9798350346671

Under the background of increasingly serious off-grid problems of renewable energy, this paper analyzes the impact of large-scale off-grid of renewable energy and voltage stability in the weakly interconnected system. First, an improved index is proposed based on Simpson formula for assessing transient voltage stability and achieving early warning of instability risk. Then, based on the simulation of a real-life UHV (Ultra-high voltage) weakly interconnected system, two typical cascading failure scenarios are reasonably anticipated. These cascading failures contain a series of renewable energy off-grid and blocking of DC transmission caused by different initial failures, whose voltage stability is evaluated by the proposed index. Besides, the nature of cascading failure evolution is analyzed. Finally, accuracy and efficient of the proposed index are verified. © 2023 IEEE.

关键词： Transients

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Preventive control Method of Improving Transient Voltage Stability for power system Based on the Attention of CNN

Preventive Control Method of Improving Transient Voltage Sta...

引用

2023 IEEE Sustainable power and Energy Conference, iSPEC 2023

作者： Li, Zhendong Yan, Jiongcheng Liu, Yutian Li, Li Qu, Hanbing The Key Laboratory of Power System Intelligent Dispatch and Control of Ministry of Education Shandong University Jinan China State Grid Jinan Power Supply Company Jinan China

ISBN: (纸本)9798350322699

The widespread integration of renewable generation and the changes in load structure bring significant challenges to the transient voltage stability of large-scale power systems. In order to achieve fast decision of preventive control for improving transient voltage stability, this paper proposes a preventive control method based on the attention of Convolutional Neural Network (CNN). An optimization decision model is established, which not only considers multiple traditional constraints but also introduces the model attention indicator based on Gradient-weighted Class Activation Mapping (Grad-CAM), enabling a more targeted improvement of transient voltage stability. The proposed indicator is capable of extracting the knowledge learned by CNN-based transient voltage assessment model, and utilizing it to guide the optimization decision-making of preventive control. Simulation results of provincial grid of eastern China demonstrate that the optimized control scheme can effectively enhance the transient voltage stability of power systems. © 2023 IEEE.

关键词： model attention indicator power system preventive control transient voltage stability

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Wind and PV power Ramp Events Prediction Based on Long Short-Term Memory Network

Wind and PV Power Ramp Events Prediction Based on Long Short...

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2023 IEEE Sustainable power and Energy Conference, iSPEC 2023

作者： Wang, Zengwei Li, Zhendong Liu, Yutian Ma, Huan The Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Shandong University Jinan China The State Grid Shandong Electric Power Research Institute Jinan China

ISBN: (纸本)9798350322699

With the increasing penetration rate of renewable generation, the challenges arising from its randomness and intermittent nature are becoming more pronounced. In particular, wind and photovoltaic power ramp events pose a serious threat to the secure and stable operation of power systems, and even lead to frequency instability and load shedding. Based on the long short-term memory neural networks (LSTM), this paper proposes a novel renewable power ramp events (RPREs) forecasting approach. First, filter the key tie-lines. Second, the LSTM network was driven by the known time series of wind, PV, load, and tie-line power to forecast the tie-line power for the next hour, thereby determining the adjustable capacity of the tie-line. Finally, the regulatory capability of the grid is considered to judge the occurrence of a power ramping event. Case study demonstrates that the proposed method can effectively predict power ramping events and meets the requirements of online assessment. © 2023 IEEE.

关键词： LSTM photovoltaic power ramping events forecasting wind power

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Ill-conditioned Problem of Fault Location Equations for Three-Terminal Lines in Distribution Network by μMPMU

Ill-conditioned Problem of Fault Location Equations for Thre...

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2022 power system and Green Energy Conference, PSGEC 2022

作者： Zhang, Junpeng Meng, Xinyuan Wang, Rundong Shandong University Key Laboratory of Power System Intelligent Dispatch and Control Ministry of Education Jinan China

ISBN: (数字)9781665499934

ISBN: (纸本)9781665499934

Three terminal line is a typical structure in distribution network, and its fault location has been the focus because of the large scale distributed generation integration. Recently, a parameter-free fault location method based on line voltage was proposed, which overcomes the problem that line parameters are unknown and only two line voltages can be measured in distribution network of China. Although it is more practical than previous methods, the RTDS test shows that the location equations of this method have ill-conditioned problems, that is, tiny measurement error causes too large deviation in the result. To study this problem, the ill-conditioned problem of the location equations is analyzed by condition number at first. Then the condition number of the location equations is calculated by simulation, and it is verified that the location results will produce a large error in the condition of small error of PSCAD simulation data and μMPMU measurement data from RTDS device. © 2022 IEEE.

关键词： Errors

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