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Sampled Value Attack Detection for Busbar Differential Protection Based on a Negative Selection Immune system

Journal of Modern power systems and Clean energy 2023年第2期11卷 421-433页

作者： Jun Mo Hui Yang Guangxi Key Laboratory of Power System Optimization and Energy Technology Guangxi UniversityNanning 530004China

Considering a variety of sampled value(SV)attacks on busbar differential protection(BDP)which poses challenges to conventional learning algorithms,an algorithm to detect SV attacks based on the immune system of negative selection is developed in this *** healthy SV data of BDP are defined as self-data composed of spheres of the same size,whereas the SV attack data,i.e.,the nonself data,are preserved in the nonself space covered by spherical detectors of different *** avoid the confusion between busbar faults and SV attacks,a self-shape optimization algorithm is introduced,and the improved self-data are verified through a power-frequency fault-component-based differential protection criterion to avoid false *** on the difficulty of boundary coverage in traditional negative selection algorithms,a self-data-driven detector generation algorithm is proposed to enhance the detector coverage.A testbed of differential protection for a 110 kV double busbar system is then *** SV attacks of BDP such as amplitude and current phase tampering,fault replays,and the disconnection of the secondary circuits of current transformers are considered,and the delays of differential relay operation caused by detection algorithms are investigated.

关键词： Cyberattack busbar differential protection(BDP) negative selection self-data-driven detector sampled value attacks internal faults

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Improved Multi-Grained Cascade Forest Model for Transformer Fault Diagnosis

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CSEE Journal of power and energy systems 2025年第1期11卷 468-476页

作者： Yiyi Zhang Yuxuan Wang Jiefeng Liu Heng Zhang Xianhao Fan Dongdong Zhang Guangxi Key Laboratory of Power System Optimization and Energy Technology Guangxi UniversityNanningGuangxi530004China

Dissolved gas analysis(DGA)is an effective online fault diagnosis technique for large oil-immersed ***,due to the limited number of DGA data,most deep learning models will be overfitted and the classification accuracy cannot be ***,this paper has introduced the idea of deep neural networks into the multi-grained cascade forest(gcForest),which is a tree-based deep learning model,and proposed an improved gcForest that can be accelerated by ***,in order to extract features more effectively and reduce memory consumption,the multi-grained scanning of gcForest is replaced by convolutional neural ***,the cascade forest(CasForest)is replaced by cascade eXtreme gradient boosting(CasXGBoost)to improve the classification ***,235 DGA samples are used to train and evaluate the proposed *** average fault diagnosis accuracy of the improved gcForest is 88.08%,while the average recall,precision,and Fl-score are 0.89,0.90,0.89,***,the proposed method still has high fault diagnosis accuracy for datasets of different sizes.

关键词： Convolutional neural networks dissolved gas analysis fault diagnosis multi-grained cascade forest(gcForest) power transformer

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TOPSIS Scoring Method for Industrial Users Based on DEMATEL-EWM Weighting Method 1

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37th Annual Conference on power system and Automation in Chinese Universities, CUS-EPSA 2022

作者： Zhu, Songyang Bai, Xiaoqing Key Laboratory of Power System Optimization and Energy Saving Technology Guangxi University Nanning530004 China

ISBN: (数字)9789819914395

ISBN: (纸本)9789819914388

The evaluation and analysis of the power consumption behavior of industrial users can help the power marketing department provide a theoretical basis for assessing industrial users. Firstly, this paper constructs a user behavior evaluation system to evaluate users through positive and negative characteristics. Then, this paper establishes an evaluation model based on the technique for order preference by similarity to the ideal solution (TOPSIS). For the index weight of the user’s power consumption behavior, this paper uses the comprehensive weight method combining the decision-making trial and Evaluation laboratory (DEMATEL) and entropy weight method (EWM). Based on this, the TOPSIS model is established based on an improved weight method. The load stability of a laser enterprise in China is analyzed using the evaluation model, combined with two weighting methods and positive and negative characteristics. © 2023, State Grid Electric power.

关键词： Electric power utilization

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Data-Driven RNN Method for Distribution Network Optimal power Flow Problems 3

Data-Driven RNN Method for Distribution Network Optimal Powe...

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3rd power system and Green energy Conference, PSGEC 2023

作者： Zhang, Zixuan Yang, Shiao Jia, Yujing Xiao, Jiawen Bai, Xiaoqing Guangxi University Key Laboratory of Guangxi Electric Power System Optimization and Energy-Saving Technology Guangxi Nanning China

ISBN: (纸本)9798350340099

The optimal power flow (OPF) problem has long been a central focus for researchers in the field of power systems. With the widespread adoption of data-driven approaches, this paper introduces a novel solution to the distribution network OPF problem using a recurrent neural network (RNN) method. By leveraging the power of RNNs, this method offers a promising approach to address the challenges associated with optimizing power flow in distribution networks. To evaluate the effectiveness of the proposed method, a simulation experiment was conducted on a 12-bus distribution network system. The results of the experiment not only confirmed the method's efficacy but also showcased its superior performance compared to existing approaches. This success paves the way for the future application of the RNN method in larger-scale power systems. Overall, this research highlights the significance of data-driven methods in addressing the challenges of power system optimization. The successful application of the RNN method in solving the distribution network OPF problem underscores its potential to revolutionize the field and improve the efficiency and reliability of power systems in the future. © 2023 IEEE.

关键词： Recurrent neural networks

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A Low-Rank Algorithm Based on Riemannian optimization for Optimal power Flow Problem 3

A Low-Rank Algorithm Based on Riemannian Optimization for Op...

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3rd power system and Green energy Conference, PSGEC 2023

作者： Huang, Shengquan Bai, Xiaoqing Shang, Qinghua Wang, Rui Guangxi University Key Laboratory of Guangxi Electric Power System Optimization and Energy-Saving Technology Guangxi Nanning China

ISBN: (纸本)9798350340099

The optimal power flow (OPF) problem is essentially a mathematical programming that aims to seek an optimal operation condition subject to network and physical constraints. The semidefinite programming (SDP) relaxation has emerged as a popular technique to solve the OPF problem, but it often finds a high-rank solution and encounters difficulties in obtaining an exact solution for mesh network. Therefore, this paper utilizes a Riemannian optimization method to solve the low-rank optimal solution for OPF problem via SDP. Firstly, a Burer-Monteiro factorization-based augmented Lagrangian method is applied to the standard SDP of OPF. Then, the Riemannian gradient and Hessian are derived to solve the subproblem with the Riemannian trust-region method. Finally, the strategy for escaping from saddle points and the technique that adjusts the parameters for solving a low-rank solution are given. The simulation results verify the accuracy of the proposed algorithm can obtain a lower-rank solution compared to other advanced SDP solvers. © 2023 IEEE.

关键词： Mathematical programming

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Safety monitoring method for powerline corridors based on single‐stage detector and visual matching

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High Voltage 2024年第4期9卷 805-815页

作者： Jinheng Li Hanbo Zheng Peng Liu Yanshen Liang Feng Shuang Junjie Huang Guangxi Key Laboratory of Power System Optimization and Energy Technology Guangxi UniversityNanningChina China Southern Power Grid Guangxi Power Grid Company Ltd. NanningChina State Grid Hubei Electric Power Research Institute WuhanChina

Effective monitoring and early warning of overhead power lines are critical for ensuring power supply stability and personnel ***,existing methods that rely solely on single vision or light detection and ranging(LiDAR)have limitations such as numerous invalid alarms,hardware equipment constraints,and lack of real-time monitoring *** article proposes an intelligent monitoring method for safety distance of the powerline corridor based on heterogeneous sensor ***,an optimised single-stage detector is designed to detect safety hazard *** the detector,the backbone network and the sample matching strategy are improved;in addition,the learning strategy is ***,the pose transformation relationship is obtained through the visual matching of prior LiDAR information and *** back projection transformation of 2D–3D is achieved according to the ***,a monocular camera-based end-to-end distance measurement scheme is proposed by combining 2D object information with coordinate transformation *** scheme is applied to the distance measurements from hazard objects to *** experimental results show that the optimisation method improves the detection accuracy and reduces the computational complexity of the ***,case experiments with continuous frame data verify the effectiveness of the safety distance monitoring scheme.

关键词： visual hardware matching

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Aging Estimation of Transformer Insulating Paper in Hotspot Region Under Non-Uniform Thermal Field Based on Furfural Markers

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IEEE Transactions on Dielectrics and Electrical Insulation 2024年第3期32卷 1660-1667页

作者： Zhang, Heng Li, Wen Rao, Ruidong Liu, Chuying Zhang, Enze Jiang, Zaijun Fan, Xianhao Liu, Jiefeng Wu, Thomas Guangxi University Guangxi Key Laboratory of Power System Optimization and Energy Technology Guangxi Nanning530004 China Tsinghua University Department of Electrical Engineering Beijing100084 China

The insulating paper at the hotspot region of the transformer winding is the weakest part, thus it is essential to grasp its aging condition. Furfural is employed as a chemical marker to characterize the aging condition of insulating paper. However, existing studies focused on the aging assessment of insulating paper at uniform aging conditions based on furfural, and there is a lack of reports on the insulating paper aging estimation in the hotspot region. Given this, an improved beluga whale optimization algorithm optimized multilayer perceptron model (IBWO-MLP) is proposed to predict the DP (degree of polymerization) value in the hotspot region. Firstly, non-uniform aging experiments are conducted on oil-paper insulations. Furthermore, DP values of insulating paper in the hotspot region were predicted by the IBWO-MLP model, and the accuracy of the prediction models was compared. Moreover, based on the enhanced data after the prediction of the IBWO-MLP model, a DP estimate model for insulating paper in hotspot region applicable to field conditions was established. Eventually, the reliability of the constructed model was verified by data from the field transformer. In this regard, this study aims to contribute a novel approach to the aging estimation of the insulating paper in the hotspot region, which is supportive of the diagnosis of insulation failures. © 1994-2012 IEEE.

关键词： Furfural

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Multistep Prediction of Multiple Small Hydropower Stations' Total power in a Watershed within a Day Considering the Distributed Discharge TCN-LSTM Model 4

Multistep Prediction of Multiple Small Hydropower Stations' ...

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2023 4th International Conference on Electrical, Electronic Information and Communication Engineering, EEICE 2023

作者： Xu, Hongyi Guangxi Key Laboratory of Power System Optimization and Energy Technology Guangxi University Nanning530004 China

First, this paper proposes that although the small hydropower group in the basin terrace as a whole uses the hydrological natural flow to generate electricity, the small hydropower except the first stage will also reuse a certain proportion of the small hydropower outflow and immediately upper stage, solving the problem of the relationship between the total power prediction of the small hydropower group and the hydrological natural flow prediction at all levels. Second, this paper proposes a satellite remote sensing monitoring point selection method based on topographic elevation to determine the increment of rainfall collection area above each small hydropower dam site, solving the correspondence between the source of the incoming flow of each small hydropower and the rainfall collection area above the dam site nested step by step, and the problem that each small hydropower is dividing the hydrological and natural flow of the whole basin according to the increment of rainfall collection area above the dam site. Third, this paper proposes a method that combines computational yield flow, deep learning simulation of sink flow, and fitting small hydropower generation equations, i.e., considering the distributed yield flow TCN-LSTM model (DR-TCN-LSTM), which solves the problem that the major part of the incoming flow except for the first level small hydropower is the reuse of the outgoing flow and the immediate upper-level small hydropower, which is treated by the immediate upper-level small hydropower, rather than the purely natural state product of the problem. In an example of an 8-step prediction of multiple small hydropower stations' total power in a certain basin in Guangxi, China within a day, this paper proposes a Distributed Runoff TCN-LSTM Model (DR-BP-LSTM), and the Nash coefficient of the total power is 0.919. The Nash coefficient is increased by 0.02 due to the calculated discharge. In the selection of deep learning models, the Nash coefficient of the predi

关键词： Rain

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Optimal Topology Design of Remote Low Voltage AC Distribution systems

Optimal Topology Design of Remote Low Voltage AC Distributio...

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2023 IEEE Green energy and Smart systems Conference, IGESSC 2023

作者： Taing, Ratha Li, Xiaocong Guangxi University Guangxi Key Laboratory of Power System Optimization and Energy Technology Nanning Guangxi530000 China

ISBN: (纸本)9798350313536

This paper addresses the AC low voltage distribution system by proposing the optimal topology in a remote village for 25 years of planning. The minimum distance algorithm is employed to find the nearest loads to electric poles with the given coordinates. Then, those loads and the closest electric pole are assigned as a cluster. Next, the minimum-spanning-tree (MST) is used to define the shortest connection of clusters. After that, phase ABC repeated is used to balance the three phases system. Thereafter, the load flow is performed with respect to the constraint. Thus, the conductor size is defined. Finally, the cost of the distribution system (CAPEX, OPEX, and TOTEX) is calculated. The result shows that the proposed algorithm has energy losses that are lower than the overall energy losses of the system. © 2023 IEEE.

关键词： energy dissipation

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Simulation and test on lightning protection of large photovoltaic power station by gas arc-extinguishing device 20

Simulation and test on lightning protection of large photovo...

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20th International Conference on AC and DC power Transmission 2024, ACDC 2024

作者： Qin, Honglin Huang, Ping Xu, Shijie Guangxi University Nanning530004 China Guangxi Key Laboratory of Power System Optimization and Energy Technology Guangxi University Nanning530004 China

ISBN: (纸本)9781837242672

Large photovoltaic power station are built in wide deserts, mountains and fields, and lighting accidents occur frequently. This paper proposes a gas arc-extinguishing device to lightning protection and ensure that photovoltaic power stations can continue to generate electricity safely. The gas arc-extinguishing device principle is analyzed, and then the arc extinguishing process is simulated by COMSOL Multiphysics simulation software. Finally, the power-frequency continuous current interruption test is performed. The simulation and test results show that the device can effectively arc extinguishing on the insulator of the transmission line of large photovoltaic power station. © The Institution of Engineering & technology 2024.

关键词： Lightning protection

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