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A disturbance localization method for power system based on group sparse representation of compressed sensing 2

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A disturbance localization method for power system based on ...

2nd IEEE International Conference on Electrical Engineering, Big Data and Algorithms, EEBDA 2023

作者： Wang, Zeyi Jiao, Mingxi Wang, Daliang Liu, Minxu Jiang, Minglei Wang, He Li, Shiqiang State Grid Jilin Electric Power Co. Ltd. Changchun Power Supply Company Changchun China Institute of State Grid Jilin Electric Power Co. Ltd. Economic and Technical Research Changchun China Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Jilin China

ISBN: (纸本)9781665462532

This paper proposes a new disturbance localization method for power system based on group sparse representation of compressed sensing. Based on the analysis of disturbance characteristics of power system, the sparse dictionary of compressed sensing group is constructed by the admittance matrix, impedance matrix, and power variation matrix. In addition, the traditional generalized orthogonal matching pursuit reconstruction algorithm is improved to obtain the group sparse coefficients corresponding to the above dictionaries for compressive sensing sparse reconstruction, and the corresponding weights of each class in the group sparse dictionary are determined based on the entropy weight method to realize the accurate location of power system disturbances. In this paper, the IEEE 39 node power systems are built on the PSCAD/EMTDC simulation platform for experimental verification, and three common disturbances of cutting generator capacity, cutting load capacity and single-phase grounding short circuit are analyzed respectively. The simulation results show that the proposed method can achieve the accurate location of common disturbances in power systems with limited measurement device configurations, and has the advantages of less computation and strong robustness to noise. © 2023 IEEE.

关键词： Entropy

A Short-Term power Prediction Method for Wind Farm Cluster Based on Time Dynamic Graph Network and Improved Transformer Model

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A Short-Term Power Prediction Method for Wind Farm Cluster B...

2025 International Russian Smart Industry Conference, SmartIndustryCon 2025

作者： Han, Chao Chen, Zihang Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Jilin132012 China Jiangmen Power Supply Bureau Guangdong Power Grid Co. Ltd Jiangmen529020 China

ISBN: (纸本)9798331511241

In recent years, wind power has gradually replaced thermal power as the main source of new energy generation. Wind power prediction in advance can help formulate scheduling strategies and improve the stability of the power system. With the advent of the Industry 4.0 and the widespread application of artificial intelligence technology, artificial algorithms have been extensively used in the field of wind power prediction. To further explore the spatiotemporal correlation of every wind farm in the wind farm cluster, a temporal dynamic graph network is used to divide the wind farm farm into several sub-clusters. Then, the KAN-BiLSTM-Transformer algorithm is used to predict wind power of each wind sub-cluster. Finally, the wind power of each sub-cluster is added to attain the final predicted power of the wind farm cluster. After verification, the RMSE and MAE of the proposed method is 0.06849 and 0.05805 respectively, with an accuracy of 93.15%, which is superior to the compared algorithms. Proposed method can provide more accurate prediction results. © 2025 IEEE.

关键词： Farms

Optimization control Strategy of Pumped Storage power Station Considering Cost Allocation

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Optimization Control Strategy of Pumped Storage Power Statio...

2023 International Conference on power system technology, powerCon 2023

作者： Yan, Jun Song, Qinglong Guo, Qi Xin, Lijian Meng, Fancheng Yu, Shuo Zhou, Jiaxu Li, Cuiping Li, Junhui Co. Ltd. Hohhot China Northeast Electric Power University Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Jilin China Co. Ltd. Power Dispatching and Control Branch Hohhot China Co. Ltd. Inner Mongolia Electric Power Research Institute Branch Hohhot China

ISBN: (纸本)9798350300222

Against the backdrop of the increasing proportion of new energy generation, pumped storage, as the main energy storage method, face problems of low utilization and poor economic benefits. To improve the enthusiasm and overall efficiency of pumped storage power stations, this article proposes an optimized control strategy for pumped storage power stations that takes into account cost sharing. This strategy combines the PSS allocation system operation rules and control strategies to improve the utilization of PSS capacity by expanding its application scenario range, and to increase its enthusiasm for extraction by increasing rental income;This article takes a regional power grid in northwest China as an example for analysis, and the results show that the proposed strategy can effectively improve the utilization level and economic benefits of PSS. © 2023 IEEE.

关键词： Cost effectiveness

Multi-Timescale Risk Scheduling for Transmission and Distribution Networks for Highly Proportional Distributed energy Access

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SSRN 2023年

作者： Wang, He Liu, Ziyue Bian, Jing Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China

With the incorporation of more renewable energy sources, distribution networks are shifting from passive to active. The enhanced coupling of transmission and distribution networks is enhanced and bidirectional tides affect the reliable and secure operation of such networks. This paper proposes a multi-timescale risk dispatch study for transmission and distribution networks that have a high proportion of distributed energy access to meet the rising demand for coupling between the two types of networks. First, a day-ahead scheduling model that takes into account various operational risks is developed with the goal of minimizing total operating costs, and it optimizes the source network load and storage of multiple adjustable resources of the transmission network and distribution network jointly under the risk limit constraint. Second, an intraday scheduling model is built with the goal of minimizing the overall risk value of the transmission network and distribution network, and the day-ahead scheduling plan is modified to realize this, considering the magnitude of different operational risk values of the transmission network and distribution network. Finally, the effectiveness of the proposed multi-time-scale risk dispatch model is verified through the analysis of arithmetic cases, and it is proved that the model can enable the interaction and coordination between transmission and distribution networks as well as the synergistic optimization of operating costs and operating risks. © 2023, The Authors. All rights reserved.

关键词： Electric power transmission networks

Wind-storage-hydrogen-gas Turbine Coordinated Operation Strategy for power Fluctuation Mitigation

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Gaodianya Jishu/High Voltage Engineering 2025年第5期51卷 2125-2136页

作者： Kong, Lingguo Fan, Naiwen Shi, Zhenyu Kang, Jiandong Han, Zijiao Liu, Chuang Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Northeast Electric Power University Jilin132012 China China Electric Power Research Institute Beijing100192 China State Grid Liaoning Electric Power Company Shenyang110006 China

To address the challenges posed by the volatility, absorption rate, and economic efficiency of large-scale wind power integration, this paper proposes a coordinated operation strategy for power fluctuation mitigation, in which hydrogen storage and gas turbines are predominantly used,with battery storage as a supplement. Firstly, a capacity optimization model for a highly dynamic hydrogen production system with adaptable SC-ALK electrolyzer is established. Secondly, a levelized cost of electricity (LCOE) objective function is constructed in which the coupling characteristics of wind-storage-hydrogen-gas turbine systems are taken into account, and an operational control strategy for 18 different conditions is proposed. Then, the proposed operational control strategy and objective function are combined to build an economic capacity allocation model, which is solved using an improved particle swarm optimization algorithm. Finally, typical wind power data from seven major regions in China are used for case analysis to verify the effectiveness of the proposed method and to determine the economic capacity allocation schemes for wind farms in each region. © 2025 Science Press. All rights reserved.

关键词： Particle swarm optimization (PSO)

Fault Location Method of Dc Distribution Network Based on Multivariate Information Fusion

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SSRN 2023年

作者： Wang, He Zhang, Zekun Yu, Huanan Li, Shiqiang Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China

The accuracy of Direct Current (DC) distribution network fault location for a single electrical or switching quantity fault information is difficult to meet the requirements. This paper proposes a fault location method of DC distribution network based on multivariate information fusion. Firstly, the compressed sensing algorithm is used to reconstruct the fault transient electrical data to obtain the sparse characteristics of the high-frequency fault current. Secondly, the Bayesian network is established to obtain the fault probability of the faulty component based on the protection action inf0ormation generated by the faulty component, and then the sparse fault characteristics and fault probability of the fault current are normalized to obtain the fault degree of the electrical quantity and switching quantity. Finally, the traditional Dempster Shafer (DS) evidence theory fusion algorithm is improved to solve the problem of conflict of uncertain subsets by weight allocation method, and then the fault degree of electrical quantity and switching quantity is fused by combining Bayesian estimation method and weighting method, so as to achieve accurate fault location. simulation experiments conducted using MATLAB software demonstrate that the proposed method can effectively reduce the evidence conflict at the fault point, and the fault location accuracy is improved by 2% to 4% compared with the traditional DS evidence theory, which has a good engineering application prospect for the fault location of DC distribution network. © 2023, The Authors. All rights reserved.

关键词： Bayesian networks

Short-Term Interval Prediction of Photovoltaic power Considering Correlation Information Matching of Meteorological Resources and Trend Mutation Perception

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SSRN 2023年

作者： Yang, Mao Li, Yi Zhang, Wei Su, Xin Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin 132012 China

Since errors in deterministic forecasting of photovoltaic power cannot be avoided, interval prediction can adequately characterize the uncertainty in photovoltaic power, which in turn provides further guidance for decision making in the dispatch department. The current interval prediction method is still incomplete in mining the physical change process of photovoltaic power, and there is a problem of low matching degree of gridded meteorological forecast data in the provincial area. Aiming at the above problems, a short-term interval prediction framework of photovoltaic power considering meteorological correlation information matching and trend mutation perception is proposed in this paper. Firstly, the NWP information is reconstructed for low matching degree power stations, and the weather type is predicted by photovoltaic output level. Next, the prediction interval is calculated based on the state transition probability matrices for trend-change factor, time-correlation factor, and numerical-mutation factor. Finally, the framework of this paper is applied to a photovoltaic power plant in Jilin Province, China, and the results of the arithmetic example show that, compared with other methods, the average RMSE of this paper's method is reduced by 5.3%, and the CWC is improved by at least 2.1%, which verifies the effectiveness of this paper's method. © 2023, The Authors. All rights reserved.

关键词： Decision making

Wind power Ultra-Short-Term Prediction Method Based on Nwp Wind Speed Correction and Double Clustering Division of Transitional Weather Process

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SSRN 2023年

作者： Yang, Mao Guo, Yunfeng Huang, Yutong Key Laboratory of Modern Power System Simulation and Control & Renewable Energy Technology Ministry of Education [Northeast Electric Power University Jilin132012 China

Wind power prediction technology is important for building novel power systems with a high proportion of renewable energy. Numerical weather prediction (NWP) data quality has a significant impact on the accuracy of ultra-short-term wind power prediction (USTWPP). However, existing NWP do not reflect the adaptability of different weather processes, because of it’ s forecasting errors. In view of this, this paper proposes an USTWPP method based on NWP wind speed correction and transitional weather process division. The BILSTM-INFO-HKELM was first used to correct the NWP wind speed, and then the multiple clustering method was used to divide the transitional weather processes to establish a model for USTWPP based on different scenarios, the overall method was finally applied to a wind farm in west inner Mongolia, China. Compared to the pre-correction, the wind speed forecasted RMSE was reduced by 1.702 and the MAE by 1.366. Based on the wind power ultra-short-term prediction method proposed in this paper, the average reduction in RMSR is 4.96% and in MAE is 4.36% compared to the various comparison methods in this paper. The wind power ultra-short-term prediction method combining wind speed correction and double clustering division of weather scenarios can significantly improve prediction accuracy. © 2023, The Authors. All rights reserved.

关键词： Wind power

A Review of Coupling and Interaction Studies of Grid-Forming Converters Based on Transient Stability

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A Review of Coupling and Interaction Studies of Grid-Forming...

energy, Electrical and power Engineering (CEEPE), International Conference on

作者： Zhen Tang Shuo Wang Yang Cui Xueting Cheng Yuting Zhao State Grid Shanxi Electric Power Research Institute Taiyuan China Key Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology Northeast Electric Power University Jilin China

ISBN: (数字)9798350375794

ISBN: (纸本)9798350375800

Grid-forming (GFM) inverters, with their synchronous voltage source characteristics, have attracted widespread attention in recent years due to their ability to effectively enhance the stability of power-electronic-based new power systems. The document starts by examining the mechanism of system stability established by GFM and analyzes the issues that need to be addressed urgently after GFM is integrated into the system. Grid-forming control establishes multiple coupling channels with the grid connection point to provide voltage and frequency support. However, the frequency coupling also brings about many interaction issues. The document divides the coupling interaction issues into "internal coupling" and "external interaction" issues based on whether the control structure modification is considered, and evaluates the research path for them.

关键词： Couplings Reviews Resonant frequency power system stability Stability analysis Resonance Transient analysis