Статті в журналах: "Line Outage Identification"

1

Chen, Yu Christine, Taposh Banerjee, Alejandro D. Dominguez-Garcia, and Venugopal V. Veeravalli. "Quickest Line Outage Detection and Identification." IEEE Transactions on Power Systems 31, no. 1 (January 2016): 749–58. http://dx.doi.org/10.1109/tpwrs.2015.2394246.

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Arabali, A., M. Majidi, M. S. Fadali, and M. Etezadi-Amoli. "Line outage identification-based state estimation in a power system with multiple line outages." Electric Power Systems Research 133 (April 2016): 79–86. http://dx.doi.org/10.1016/j.epsr.2015.12.013.

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3

Kundu, Shubhrajyoti, Sumit Banerjee, Siddhartha Sankar Thakur, and Mehebub Alam. "Line outage identification using comparison of bus power mismatch considering PMU outage." International Journal of Nanoparticles 12, no. 3 (2020): 238. http://dx.doi.org/10.1504/ijnp.2020.10031799.

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4

Alam, Mehebub, Shubhrajyoti Kundu, Siddhartha Sankar Thakur, and Sumit Banerjee. "Line outage identification using comparison of bus power mismatch considering PMU outage." International Journal of Nanoparticles 12, no. 3 (2020): 238. http://dx.doi.org/10.1504/ijnp.2020.109547.

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5

Ding, Xue Yang, and Xin Dong Liu. "A Blackout Model Based on Optimal Risk Index and High-Risk Line Identification." Advanced Materials Research 383-390 (November 2011): 2390–97. http://dx.doi.org/10.4028/www.scientific.net/amr.383-390.2390.

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This paper summarizes the defects of both OPA model and its improved models and then proposes a new model in order to simulate real power system roundly. There is an inner loop based on DC power flow optimization to minimize the change in generation or load shed and an outer loop based on the risk theory. In the outer loop, whether to improve the line capacity and how to improve are determined by risk index of line improvement (RILI) and line improvement degree function, respectively. A new prevention strategy against cascading failure is proposed by identifying the high-risk lines and determining optimal RILI which minimize line improvement cost and load loss. In the end, simulation based on 39-bus New England System reveals that new model is closer to real power system than the original one by comparing outage probability and load loss between the two models, and risk-based assessment interval and line improvement delay play important roles in prevention against power system outages, and improvement based on risk assessment can reduce outage probability to varying degrees, which illustrates the practical significance of optimal RILI.

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6

Amin Mohammed, Dara H. "Voltage Stability Analysis for Kurdistan Region Power System Using Fast Voltage Stability Index." Tikrit Journal of Engineering Sciences 21, no. 2 (September 18, 2013): 75–79. http://dx.doi.org/10.25130/tjes.21.2.10.

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In any stressed power system, Identification of the weakest bus and transmission lines is veryimportant for planning and operation to prevent voltage collapse which leads to total blackout ofthe whole system. The aim of the paper is to use a technique to determine the weakest buses ofthe power system. Increasing load in power system could lead to the event of voltage collapsewhich implies the contingency in the system. Increasing load and line outage contingencies areranked so that the line which highly affects the system could be identified. This paper proposesto utilize an established index called FVSI (Fast Voltage Stability Index) to identify the sensitivelines and critical line outages in the system. Test system of this paper is the KRPS-30-Bus-132kV. The contingency ranking process can be conducted by computing the line stability indexof each line for a particular Increasing load and for line outage contingency. The contingencywhich is ranked the highest implies that it contributed to the system instability.

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7

He, Jia, and Maggie X. Cheng. "Machine learning methods for power line outage identification." Electricity Journal 34, no. 1 (January 2021): 106885. http://dx.doi.org/10.1016/j.tej.2020.106885.

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8

Emami, Roozbeh, and Ali Abur. "External system line outage identification using phasor measurement units." IEEE Transactions on Power Systems 28, no. 2 (May 2013): 1035–40. http://dx.doi.org/10.1109/tpwrs.2012.2220865.

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9

Kim, Taedong, and Stephen J. Wright. "PMU Placement for Line Outage Identification via Multinomial Logistic Regression." IEEE Transactions on Smart Grid 9, no. 1 (January 2018): 122–31. http://dx.doi.org/10.1109/tsg.2016.2546339.

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10

Vijay, R. "Transmission Line Outage Detection and Identification by Communal Spider Optimization Algorithm." CVR Journal of Science & Technology 14, no. 01 (June 1, 2018): 38–42. http://dx.doi.org/10.32377/cvrjst1408.

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11

Lotfifard, Saeed. "Sparse Sensing Platform for Line-Outage Identification in Multiarea Power Systems." IEEE Transactions on Industrial Informatics 13, no. 3 (June 2017): 947–55. http://dx.doi.org/10.1109/tii.2017.2679022.

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12

Babakmehr, Mohammad, Farnaz Harirchi, Ahmed Al-Durra, S. M. Muyeen, and Marcelo Godoy Simoes. "Compressive System Identification for Multiple Line Outage Detection in Smart Grids." IEEE Transactions on Industry Applications 55, no. 5 (September 2019): 4462–73. http://dx.doi.org/10.1109/tia.2019.2921260.

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13

Daram, Suresh Babu, Mulpuri Kiran, P. S. Venkataramu, and M. S. Nagaraj. "Identification of DG Location through Sensitivity Factors under Line Outage Condition." International Journal of Grid and Distributed Computing 10, no. 11 (November 30, 2017): 23–32. http://dx.doi.org/10.14257/ijgdc.2017.10.11.03.

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14

Hosseini, Zohreh S., Mohsen Mahoor, and Amin Khodaei. "AMI-Enabled Distribution Network Line Outage Identification via Multi-Label SVM." IEEE Transactions on Smart Grid 9, no. 5 (September 2018): 5470–72. http://dx.doi.org/10.1109/tsg.2018.2849845.

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15

Alam, Mehebub, Shubhrajyoti Kundu, Siddhartha Sankar Thakur, and Sumit Banerjee. "PMU based line outage identification using comparison of current phasor measurement technique." International Journal of Electrical Power & Energy Systems 115 (February 2020): 105501. http://dx.doi.org/10.1016/j.ijepes.2019.105501.

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16

Arabali, Amirsaman, Mahmoud Ghofrani, and Mehdi Farasat. "A new multiple line outage identification formulation using a sparse vector recovery technique." Electric Power Systems Research 142 (January 2017): 237–48. http://dx.doi.org/10.1016/j.epsr.2016.10.006.

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17

Zhao, Yue, Jianshu Chen, and H. Vincent Poor. "A Learning-to-Infer Method for Real-Time Power Grid Multi-Line Outage Identification." IEEE Transactions on Smart Grid 11, no. 1 (January 2020): 555–64. http://dx.doi.org/10.1109/tsg.2019.2925405.

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18

Li, Xiongli, Fei Xiao, Youlin Hu, and Huikai Peng. "Research on Recognition of Topological Relations Between Residential Lines in Low Voltage Station Area Based on Correlation Analysis Algorithm and Probabilistic Decision Method." Journal of Nanoelectronics and Optoelectronics 16, no. 7 (July 1, 2021): 1107–14. http://dx.doi.org/10.1166/jno.2021.3053.

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In order to solve the problems of low accuracy and incomprehensive recognition of the topological relationship between households in the station area and the incomplete recognition results in traditional methods, a method for identifying topological relationships between household changes in low-voltage stations based on correlation analysis algorithm and probabilistic decision method is proposed. The BIRCH method is used to cluster the topological relationship characteristics of the household line changes in the low-voltage station area, and the topological relationship characteristics are obtained through clustering parameter initialization, clustering implementation and clustering evaluation, and the user phases in the topological relationship are identified according to the feature clustering results. The correlation analysis method is used to analyze the similarity of the voltage sequence of the points to be identified and the comprehensive similarity of all the faults of the target distribution transformer and the auxiliary distribution transformer, and set a similarity threshold to determine whether the points to be identified belong to the same station area. Finally, based on the probabilistic decision-making method, the identification of the topological relationship of the low-voltage station area household line change is completed. The experimental results show that this method can not only identify the topological relationship of single distribution transformer outage, but also identify the topological relationship of multiple distribution transformer outage. The accuracy of the identification result is high, and the identification loss function is low, which indicates that the identification result of this method is reliable and comprehensive.

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19

Li, Xiongli, Fei Xiao, Youlin Hu, and Huikai Peng. "Research on Recognition of Topological Relations Between Residential Lines in Low Voltage Station Area Based on Correlation Analysis Algorithm and Probabilistic Decision Method." Journal of Nanoelectronics and Optoelectronics 16, no. 7 (July 1, 2021): 1107–14. http://dx.doi.org/10.1166/jno.2021.3053.

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In order to solve the problems of low accuracy and incomprehensive recognition of the topological relationship between households in the station area and the incomplete recognition results in traditional methods, a method for identifying topological relationships between household changes in low-voltage stations based on correlation analysis algorithm and probabilistic decision method is proposed. The BIRCH method is used to cluster the topological relationship characteristics of the household line changes in the low-voltage station area, and the topological relationship characteristics are obtained through clustering parameter initialization, clustering implementation and clustering evaluation, and the user phases in the topological relationship are identified according to the feature clustering results. The correlation analysis method is used to analyze the similarity of the voltage sequence of the points to be identified and the comprehensive similarity of all the faults of the target distribution transformer and the auxiliary distribution transformer, and set a similarity threshold to determine whether the points to be identified belong to the same station area. Finally, based on the probabilistic decision-making method, the identification of the topological relationship of the low-voltage station area household line change is completed. The experimental results show that this method can not only identify the topological relationship of single distribution transformer outage, but also identify the topological relationship of multiple distribution transformer outage. The accuracy of the identification result is high, and the identification loss function is low, which indicates that the identification result of this method is reliable and comprehensive.

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20

Ahmed, A., Q. Khan, M. Naeem, M. Iqbal, A. Anpalagan, and M. Awais. "An insight to the performance of estimation of distribution algorithm for multiple line outage identification." Swarm and Evolutionary Computation 39 (April 2018): 114–22. http://dx.doi.org/10.1016/j.swevo.2017.09.006.

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21

Huang, Keke, Zili Xiang, Wenfeng Deng, Xiaoqi Tan, and Chunhua Yang. "Reweighted Compressed Sensing-Based Smart Grids Topology Reconstruction With Application to Identification of Power Line Outage." IEEE Systems Journal 14, no. 3 (September 2020): 4329–39. http://dx.doi.org/10.1109/jsyst.2019.2958869.

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22

Ogujor, E. A., E. U. Ubeku, and P. T. Aikhoje. "Application of Pareto Analysis to Faults Identification in Electrical Distribution Network: A Case Study of Ugbowo 11kV Feeder, Benin City, Nigeria." Advanced Materials Research 62-64 (February 2009): 75–81. http://dx.doi.org/10.4028/www.scientific.net/amr.62-64.75.

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Application of Pareto Analysis technique in major feeder pillar faults identification is presented in this paper. Power outage data due to feeder pillar faults were collected between January, 2005 and September, 2007 from Power Holding Company of Nigeria (PHCN), Ugbowo district office, Edo State, Nigeria for four feeder pillars. The data were processed and Pareto Analysis technique was applied to the field data. The results obtained shows that eliminating wrong fusing and overloading in Edaiken 2 and Holex feeder pillars will reduce faults by 77.42 and 79.53% respectively while eliminating wrong fusing, overloading and line-to-line faults in Uwasota 2 and Holy Rosary feeder pillars will reduce faults by 87.9 and 88.35% respectively.

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23

Alam, Mehebub, Shubhrajyoti Kundu, Siddhartha Sankar Thakur, and Sumit Banerjee. "A new cost effective algorithm for online identification of line outage contingency using current phasor of PMU." Sustainable Energy, Grids and Networks 23 (September 2020): 100373. http://dx.doi.org/10.1016/j.segan.2020.100373.

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24

Gotman, N. E., and G. P. Shumilova. "Identification of line status changes using phasor measurements through deep learning networks." Power engineering: research, equipment, technology 22, no. 6 (March 26, 2021): 55–67. http://dx.doi.org/10.30724/1998-9903-2020-22-6-55-67.

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THE PURPOSE. To consider the problem of detecting changes in a power grid topology that occurs as a result of the power line outage / turning on. Develop the algorithm for detecting changes in the status of transmission lines in real time by using voltage and current phasors captured by phasor measurement units (PMUs) are placed on buses. Carry out experimental research on IEEE 14-bus test system. METHODS. This paper proposes a method from the field of artificial intelligence such as machine learning in particular "Deep Learning" to solve the problem. Deep Learning arises as a computational learning technique in which high level abstractions are hierarchically modelled from raw data. One of the means to effectively extract the inherent hidden features in data are Convolutional Neural Networks (CNNs). RESULTS. The article describes the topic relevance, offers to apply the method for detecting status of lines using a CNN classifier. The combination of different CNN architectures and the number of time slices from the moment of line status change are used to detect the power grid topology. The effectiveness of the joint use of PMUs and CNN in solving this problem has been proven. CONCLUSION. A solution for the line status change detection in the transient states using a CNN classifier is proposed. A high accuracy of the line status detection was obtained despite the influence of noise on measurement data. A change in the network topology is detected at the very beginning of the transient state almost instantly. It will allow the operator several times during the first seconds to identify the line state in order to make sure that the decisions made are correct.

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25

Mawle, Prashant P., Gunwant A. Dhomane, and Prakash G. Burade. "Application of artificial intelligence in early fault detection of transmission line-a case study in India." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 6 (December 1, 2022): 5707. http://dx.doi.org/10.11591/ijece.v12i6.pp5707-5716.

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<span lang="EN-US">Reliable energy is ensured by the power quality, safety and security. For reliability and economic growth of transmission utilities, it is necessary to maintain continuity of supply, which is challenging under deregulated system. It is essential for utilities to conduct regular maintenance of transmission lines before supply interrupts. To protect line from fault, it is necessary to detect fault on line, its classification and location at the earliest. Various smart techniques along with application of artificial intelligence (AI) in power system are under investigation. This paper tries to find solution by identifying practical common faults occurred on transmission lines, and also suggests the suitable maintenance methodology. It uses the artificial neural network (ANN) method and live line maintenance technique (LLMT) for pre identification of a fault and subsequent predictive maintenance. Paper compares results of combination of ANN with LLMT and cold line maintenance technique (CLMT). Comparison of statistical analysis shows combine model of ANN and LLMT results in minimize outage time, failure rate which can improve system availability and increases revenue.</span>

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26

Marín-Cano, Cristian Camilo, Juan Esteban Sierra-Aguilar, Jesús M. López-Lezama, Álvaro Jaramillo-Duque, and Walter M. Villa-Acevedo. "Implementation of User Cuts and Linear Sensitivity Factors to Improve the Computational Performance of the Security-Constrained Unit Commitment Problem." Energies 12, no. 7 (April 11, 2019): 1399. http://dx.doi.org/10.3390/en12071399.

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Power system operators must schedule the available generation resources required to achieve an economical, reliable, and secure energy production in power systems. This is usually achieved by solving a security-constrained unit commitment (SCUC) problem. Through a SCUC the System Operator determines which generation units must be on and off-line over a time horizon of typically 24 h. The SCUC is a challenging problem that features high computational cost due to the amount and nature of the variables involved. This paper presents an alternative formulation to the SCUC problem aimed at reducing its computational cost using sensitivity factors and user cuts. Power Transfer Distribution Factors (PTDF) and Line Outage Distribution Factors (LODF) sensitivity factors allow a fast computation of power flows (in normal operative conditions and under contingencies), while the implementation of user cuts reduces computational burden by considering only biding N-1 security constraints. Several tests were performed with the IEEE RTS-96 power system showing the applicability and effectiveness of the proposed modelling approach. It was found that the use of Linear Sensitivity Factors (LSF) together with user cuts as proposed in this paper, reduces the computation time of the SCUC problem up to 97% when compared with its classical formulation. Furthermore, the proposed modelling allows a straightforward identification of the most critical lines in terms of the overloads they produce in other elements after an outage, and the number of times they are overloaded by a fault. Such information is valuable to system planners when deciding future network expansion projects.

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27

Zhuang, Guanqun, Weichen Wang, Dexin Li, Song Gao, and Changjiang Wang. "Research on identification method of weak links in transmission network considering strong wind in severe cold weather." Journal of Physics: Conference Series 2450, no. 1 (March 1, 2023): 012042. http://dx.doi.org/10.1088/1742-6596/2450/1/012042.

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Abstract The ice disaster has brought many adverse effects on the power transmission system, which is mainly studied from the transmission line failure rate perspective. Strong winds often accompany the ice disaster weather, the motion path of wind is considered when identifying the weak location of transmission network system. According to the theory of meteorological simulation, and the mathematical relationship between the effective wind speed and the forced outage rates is obtained. A transient stability risks assessment method is proposed considering the ice disaster in the case of a strong wind moving path. According to the fault probability of transmission lines, a predictive fault set for power grid risk assessment is established. The IEEE-39 bus system is used as an example to analyze the effectiveness of the proposed method. The simulation results show that meteorological parameters, geographical environment, and other factors, especially the meteorological advance speed and the direction of transmission lines, will cause greater damage to the stability of the transmission system.

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28

Kawal, Kevin, Steven Blair, Qiteng Hong, and Panagiotis N. Papadopoulos. "Selective Auto-Reclosing of Mixed Circuits Based on Multi-Zone Differential Protection Principle and Distributed Sensing." Energies 16, no. 6 (March 8, 2023): 2558. http://dx.doi.org/10.3390/en16062558.

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Environmental concerns and economic constraints have led to increasing installations of mixed conductor circuits comprising underground cables (UGCs) and overhead transmission lines (OHLs). Faults on the OHL sections of such circuits are usually temporary, while there is a higher probability that faults on UGC sections are permanent. To maintain power system reliability and security, auto-reclose (AR) schemes are typically implemented to minimize outage duration after temporary OHL faults while blocking AR for UGC faults to prevent equipment damage. AR of a hybrid UCG–OHL transmission line, therefore, requires effective identification of the faulty section. However, the different electrical characteristics of UGC and OHL sections present significant challenges to existing protection and fault location methods. This paper presents a selective AR scheme for mixed conductor circuits based on the evaluation of differential currents in multiple defined protection zones, using distributed current transformer (CT) measurements provided by passive optical sensing. Case studies are conducted with a number of different UGC–OHL configurations, and the results demonstrate that the proposed scheme can accurately identify the faulty section, enabling effective selective AR of a comprehensive range of mixed conductor circuit topologies. The proposed scheme is also more cost effective, with reduced hardware requirements compared to conventional solutions. This paper thereby validates the optimal solution for mixed circuit protection as described in CIGRE Working Group B5.23 report 587.

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29

Azhar, Izzuddin Fathin, Lesnanto Multa Putranto, and Roni Irnawan. "Development of PMU-Based Transient Stability Detection Methods Using CNN-LSTM Considering Time Series Data Measurement." Energies 15, no. 21 (November 4, 2022): 8241. http://dx.doi.org/10.3390/en15218241.

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The development of electric power systems has become more complex. Consequently, electric power systems are operating closer to their limits and are more susceptible to instability when a disturbance occurs. Transient stability problems are especially prevalent. In addition, the identification of transient stability is difficult to achieve in real time using the current measurement data. This research focuses on developing a convolutional neural network—long short-term memory (CNN-LSTM) model using historical data events to detect transient stability considering time-series measurement data. The model was developed by considering noise, delay, and loss in measurement data, line outage and variable renewable energy (VRE) integration scenarios. The model requires PMU measurements to provide high sampling rate time-series information. In addition, the effects of different numbers of PMUs were also simulated. The CNN-LSTM method was trained using a synthetic dataset produced using the DigSILENT PowerFactory simulation to represent the PMU measurement data. The IEEE 39 bus test system was used to simulate the model under different loading conditions. On the basis of the research results, the proposed CNN-LSTM model is able to detect stable and unstable conditions of transient stability only from the magnitude and angle of the bus voltage, without considering system parameter information on the network. The accuracy of transient stability detection reached above 99% in all scenarios. The CNN-LSTM method also required less computation time compared to CNN and conventional LSTM with the average computation times of 190.4, 4001.8 and 229.8 s, respectively.

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30

Maraaba, Luqman, Khaled Al-Soufi, Twaha Ssennoga, Azhar M. Memon, Muhammed Y. Worku, and Luai M. Alhems. "Contamination Level Monitoring Techniques for High-Voltage Insulators: A Review." Energies 15, no. 20 (October 17, 2022): 7656. http://dx.doi.org/10.3390/en15207656.

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Insulators are considered one of the most significant parts of power systems which can affect the overall performance of high-voltage (HV) transmission lines and substations. High-voltage (HV) insulators are critical for the successful operation of HV overhead transmission lines, and a failure in any insulator due to contamination can lead to flashover voltage, which will cause a power outage. However, the electrical performance of HV insulators is highly environment sensitive. The main cause of these flashovers in the industrial, agricultural, desert, and coastal areas, is the insulator contamination caused by unfavorable climatic conditions such as dew, fog, or rain. Therefore, the purpose of this work is to review the different methods adopted to identify the contamination level on high-voltage insulators. Several methods have been developed to observe and measure the contamination level on HV insulators, such as leakage current, partial disgorgement, and images with the help of different techniques. Various techniques have been discussed alongside their advantages and disadvantages on the basis of the published research work in the last decade. The major high-voltage insulator contamination level classification techniques discussed include machine learning, fuzzy logic, neuro–fuzzy interface, detrended fluctuation analysis (DFA), and other methods. The contamination level data will aid the scheduling of the extensive and costly substation insulator, and live line washing performed using high-pressured water. As a result, considerable benefits in terms of improved power system reliability and maintenance cost savings will be realized. This paper provides an overview of the different signal processing and machine-learning methods adopted to identify the contamination level on high-voltage insulators. Various methods are studied, and the advantages and disadvantages of each method are discussed. The comprehensive review of the islanding methods will provide power utilities and researchers with a reference and guideline to select the best method to be used for contamination level identification based on their effectiveness and economic feasibility.

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31

Awais, M., A. Ahmed, M. Naeem, M. Iqbal, N. Qadri, and A. Anpalagan. "Multiple line outages identification: A customized quantum inspired approach." Electric Power Systems Research 134 (May 2016): 47–55. http://dx.doi.org/10.1016/j.epsr.2015.12.001.

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32

Zhu, Hao, and Georgios B. Giannakis. "Sparse Overcomplete Representations for Efficient Identification of Power Line Outages." IEEE Transactions on Power Systems 27, no. 4 (November 2012): 2215–24. http://dx.doi.org/10.1109/tpwrs.2012.2192142.

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33

Chen, Jung-Chieh, Wen-Tai Li, Chao-Kai Wen, Jen-Hao Teng, and Pangan Ting. "Efficient Identification Method for Power Line Outages in the Smart Power Grid." IEEE Transactions on Power Systems 29, no. 4 (July 2014): 1788–800. http://dx.doi.org/10.1109/tpwrs.2013.2296897.

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34

Li, Wen-Tai, Chao-Kai Wen, Jung-Chieh Chen, Kai-Kit Wong, Jen-Hao Teng, and Chau Yuen. "Location Identification of Power Line Outages Using PMU Measurements With Bad Data." IEEE Transactions on Power Systems 31, no. 5 (September 2016): 3624–35. http://dx.doi.org/10.1109/tpwrs.2015.2495214.

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35

Guler, T., and G. Gross. "Detection of Island Formation and Identification of Causal Factors Under Multiple Line Outages." IEEE Transactions on Power Systems 22, no. 2 (May 2007): 505–13. http://dx.doi.org/10.1109/tpwrs.2006.888985.

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36

Wu, Jie, Jinjun Xiong, and Yiyu Shi. "Efficient Location Identification of Multiple Line Outages With Limited PMUs in Smart Grids." IEEE Transactions on Power Systems 30, no. 4 (July 2015): 1659–68. http://dx.doi.org/10.1109/tpwrs.2014.2357751.

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37

Morales, John, and Marco Carpio. "Induced Lightning Stroke Identification on Protection Relays." Applied Mechanics and Materials 775 (July 2015): 368–72. http://dx.doi.org/10.4028/www.scientific.net/amm.775.368.

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It is well known that lightning strokes produce mal-operation of transmission line protection relays. Where, protection devices cannot identify correctly between lightning stroke that generates or not permanent faults. Thus, when a flash produces a permanent fault, the protection relay sends a trip order, and the Transmission Line (TL) is disconnected correctly. However, when a lightning stroke does not produce a permanent fault, the protection devices also send the trip order, and the TL is disconnected unnecessary. In this context, these phenomena can produce unnecessary electric power outages, producing damage for the society and economic. Therefore, it is necessary to correctly identify between these lightning stroke signals. Besides that, direct lightning strokes, which hit directly on TLs or transmission towers, have usually been analyzed. However, induced lightning strokes, which hit on ground, have not been considered in previous analyzed. In this paper, in order to identify these induced lightning strokes, an algorithm based on a deterministic focus is proposed.

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38

Xie, Dan, Qing Chen, Ye Sun, Ning Shao, Yuzhan Dong, and Wei Ding. "A Wide-Area Measurement System-Based Load Encroachment Identification Method Applicable to Power Systems with High Wind Power Penetration." Applied Sciences 13, no. 16 (August 15, 2023): 9279. http://dx.doi.org/10.3390/app13169279.

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One of the main factors in triggering cascading outages is the unexpected tripping of backup protection caused by load encroachment (LE). Hence, LE should be identified quickly to avoid unexpected tripping. This paper proposes a fast LE identification method based on the wide-area measurement system (WAMS), applicable to transmission grids with high wind power penetration. Firstly, based on the improved shortest path algorithm, the method searches for critical lines greatly affected by the LE to determine the collected range of wide-area information. Then, by analyzing the hidden dangers of the existing calculation method for the active power estimation value (APEV) in the power system with wind farms, a fast calculation method of the APEV based on the WAMS is proposed to ensure that the existing LE identification criterion is still applicable in the high-penetration system of wind power. Finally, based on the PSASP platform, the wind farm model is integrated into the IEEE 39-bus New England system for simulation. The simulation results show that the method proposed in this paper can quickly search for the critical line set (CLS) and accurately identify the LE under high wind power penetration, effectively avoiding the unexpected tripping of backup protection and preventing cascading outages.

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Hemalatha, S., and P. Valsalal. "Identification of Optimal Path in Power System Network Using Bellman Ford Algorithm." Modelling and Simulation in Engineering 2012 (2012): 1–6. http://dx.doi.org/10.1155/2012/913485.

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Power system network can undergo outages during which there may be a partial or total blackout in the system. In that condition, transmission of power through the optimal path is an important problem in the process of reconfiguration of power system components. For a given set of generation, load pair, there could be many possible paths to transmit the power. The optimal path needs to consider the shortest path (minimum losses), capacity of the transmission line, voltage stability, priority of loads, and power balance between the generation and demand. In this paper, the Bellman Ford Algorithm (BFA) is applied to find out the optimal path and also the several alternative paths by considering all the constraints. In order to demonstrate the capability of BFA, it has been applied to a practical 230 kV network. This restorative path search guidance tool is quite efficient in finding the optimal and also the alternate paths for transmitting the power from a generating station to demand.

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Joshua, Nalima, Abubakar Abdulkarim, S. Palanikumar, Mohammed Dahiru Buhari, and G. V. Ramana. "Reliability Study of Electrical Distribution Network in Kampala East." KIU Journal of Science, Engineering and Technology 2, no. 1 (April 4, 2023): 53–60. http://dx.doi.org/10.59568/kjset-2023-2-1-08.

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This research focuses on the reliability study of the electrical distribution network in Kampala East, which is connected to Lugogo, Nakawa, Kireka and Ntinda substations. The network is unable to supply its customers with reliable power at all times. Methods used in this research involve data identification, collection, cleaning, analyzing and interpretation. Also conducted are determination of reliability indices, identification of causes of supply interruptions and improvement of reliability. Depending on the reliability study outcome, the electrical distribution network in Kampala East has customer hours lost (System Average Interruption Duration Index) of 8.34 per month per customer, number of outages per month per customer (System Average Interruption Frequency Index) is 5.65 hours, Energy not served to customers of 2.14 GWh per month and Faults resolution time (Customer Average Interruption Duration Index) of 1.58 hours. The major cause of interruptions are system faults and emergency shutdowns. In this study, Reconfiguring network through use of appropriate combinations of opening of sectionalizing (normally Closed) switches and closing of tie-line (normally- Open) switches on feeders, the reliability is improved to 4.18 customers hours lost per month per customer and the number of outages per month per customer is 5.35, the energy not served of 0.18 GWh and faults resolution time of 0.84 Hours. This gives percentage improvements of 49.88%, 5.31%, 54.2%, and 88.61% in SAIDI, SAIFI, ENS and CAIDI respectively. The current level of reliability of electrical distribution network in Kampala East exceeds the target set by the regulator for 2022.

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Mustafa, Ahmed A., and Ahmed AK Tahir. "Improving the Performance of Finger-Vein Recognition System Using A New Scheme of Modified Preprocessing Methods." Academic Journal of Nawroz University 9, no. 3 (August 30, 2020): 397. http://dx.doi.org/10.25007/ajnu.v9n3a855.

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This paper aims at improving the performance of finger-vein recognition system using a new scheme of image preprocessing. The new scheme includes three major steps, RGB to Gray conversion, ROI extraction and alignment and ROI enhancement. ROI extraction and alignment includes four major steps. First, finger-vein boundaries are detected using two edge detection masks each of size (4 x 6). Second, the correction for finger rotation is done by calculating the finger base line from the midpoints between the upper and lower boundaries using least square method. Third, ROI is extracted by cropping a rectangle around the center of the finger-vein which is determined using the first and second invariant moments. Forth, the extracted ROI is normalized to a unified size of 192 x 64 in order to compensate for scale changes. ROI enhancement is done by applying the technique of Contrast-Limited Adaptive Histogram Equalization (CLAHE), followed by median and modified Gaussian high pass filters. The application of the given preprocessing scheme to a finger-vein recognition system revealed its efficiency when used with different methods of feature extractors and with different types of finger-vein database. For the University of Twente Finger Vascular Pattern (UTFVP) database, the achieved Identification Recognition Rates (IRR) for identification mode using three feature extraction methods Local Binary Pattern (LBP), Local Directional Pattern (LDP) and Local Line Binary Pattern (LLBP) are (99.79, 99.86 and 99.86) respectively, while the achieved Equal Error Rates (EER) for verification mode for the same feature extraction methods are (0.139, 0.069 and 0.035). For the Shandong University Machine Learning and Applications - Homologous Multi-modal Traits (SDUMLA-HMT) database, the achieved Identification Recognition Rates (IRR) for identification mode using three feature extraction methods LBP, LDP and LLBP are (99.57, 99.73 and 99.65) respectively, while the achieved Equal Error Rates (EER) for verification mode for the same feature extraction methods are (0.419, 0.262 and 0.341). These results outrage those of the previous state-of-art methods.

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Mohamad, Hasmaini, Wan Iqmal Faezy Wan Zalnidzham, Nur Ashida Salim, Shahrani Shahbudin, and Zuhaila Mat Yasin. "Power system restoration in distribution network using minimum spanning tree - Kruskal’s algorithm." Indonesian Journal of Electrical Engineering and Computer Science 16, no. 1 (October 1, 2019): 1. http://dx.doi.org/10.11591/ijeecs.v16.i1.pp1-8.

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<span>Events such as natural and manmade interference, line, transformer and feeder outages that occur in electric power distribution system negatively impact the continuity of power supply, thus affecting the power demand supply as well as customer’s satisfaction. In that cases, the restoration of power needs to be carried out immediately in order to guarantee the system’s reliability. The power flow path identification is considered as a difficult task especially in a huge system due to large number of switches. Kruskal’s algorithm is presented in this paper to find the minimum power flow path in a power distribution network. The comparison of performance between presented Kruskal’s algorithm and Binary Particle Swarm Optimization (BPSO) was made in solving a problem regarding network reconfiguration. The proposed load restoration approach is tested on IEEE 33-bus single feeder radial distribution system using MATLAB software. From the results, it is found that the presented Kruskal’s algorithm was able to search for the minimal power flow path that contribute to loss reduction for power restoration after the occurrence of fault.</span>

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Nopendri, Nopendri, and Dewi Nasien. "Troubleshooting Generator Sets using Expert System." Journal of Applied Business and Technology 1, no. 2 (May 31, 2020): 112–26. http://dx.doi.org/10.35145/jabt.v1i2.36.

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PT. Zaman Teknindo (PT. ZT) is a company engaged in Mechanical and Engineering field which is registered as one PT. Telkomsel vendors. The problems that occur at PT. ZT, if the power outage and generator set (generator) does not start automatically. The corrective team on duty at that time will go to the field and find a solution to the problem. With a lack of knowledge from the corrective team, they need help from the mechanical team. The mechanical team is an external team of PT. ZT. To bring a mechanical team requires an enormous cost and a relatively long time needed to get to the location. Based on the problem above, this study proposes a forward chaining expert system that is by depth-first search using the certainty factor method. To prove whether a fact is certain or not, it must be in the metric form in generator troubleshooting. The research methodology used the Software Development Life Cycle (SDLC) starting from problem identification, analysis, design, coding, testing and maintenance. This system is web-based, so users can easily access and choose symptoms of the damage. With this system makes it easy for PT. ZT especially the corrective team in the field can easily find out the damage symptoms without having to meet with experts directly.

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Glotov, Oleg S., Alexander N. Chernov, and Andrey S. Glotov. "Human Exome Sequencing and Prospects for Predictive Medicine: Analysis of International Data and Own Experience." Journal of Personalized Medicine 13, no. 8 (August 8, 2023): 1236. http://dx.doi.org/10.3390/jpm13081236.

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Today, whole-exome sequencing (WES) is used to conduct the massive screening of structural and regulatory genes in order to identify the allele frequencies of disease-associated polymorphisms in various populations and thus detect pathogenic genetic changes (mutations or polymorphisms) conducive to malfunctional protein sequences. With its extensive capabilities, exome sequencing today allows both the diagnosis of monogenic diseases (MDs) and the examination of seemingly healthy populations to reveal a wide range of potential risks prior to disease manifestation (in the future, exome sequencing may outpace costly and less informative genome sequencing to become the first-line examination technique). This review establishes the human genetic passport as a new WES-based clinical concept for the identification of new candidate genes, gene variants, and molecular mechanisms in the diagnosis, prediction, and treatment of monogenic, oligogenic, and multifactorial diseases. Various diseases are addressed to demonstrate the extensive potential of WES and consider its advantages as well as disadvantages. Thus, WES can become a general test with a broad spectrum pf applications, including opportunistic screening.

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Buchmann, Claudia. "Gender Inequalities in the Transition to College." Teachers College Record: The Voice of Scholarship in Education 111, no. 10 (October 2009): 2320–46. http://dx.doi.org/10.1177/016146810911101002.

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Background In terms of high school graduation, college entry, and persistence to earning a college degree, young women now consistently outperform their male peers. Yet most research on gender inequalities in education continues to focus on aspects of education where women trail men, such as women's underrepresentation at top-tier institutions and in science and engineering programs. The paucity of research on the realms where women outpace men, namely college enrollment and completion, constitutes a major gap in the literature. Purpose This article provides an overview of gender inequality in the transition to college and in college experiences by examining the ways that women are advantaged in higher education and the arenas where they still trail men. It also discusses theoretical perspectives useful in assessing the causes of gender inequality and then suggests how future research could advance our understanding of the complex nature of gender inequality in higher education. Research Design The identification and critical review of research and theories that have been used or that could prove useful in assessing and explaining the complex patterns of gender inequalities in the transition to college and in higher education more generally. Conclusions/Recommendations Fruitful pathways for future research to advance understanding of the complex nature of gender inequalities in higher education include examining gender inequalities early in the educational life course, attending to gender differences within vulnerable segments of the population who may be particularly at risk for not attending higher education, and investigating how the structure and practices of schooling relate to gender differences in educational outcomes.

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Wolf, Aaron T., Shira B. Yoffe, and Mark Giordano. "International waters: identifying basins at risk." Water Policy 5, no. 1 (February 1, 2003): 29–60. http://dx.doi.org/10.2166/wp.2003.0002.

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Despite the growing literature on water and conflict in international river basins, little empirical work has been done to bolster common conclusions which are so widely reported. In order to address this gap, we set out to assess all reported events of either conflict or cooperation between nations over water resources during the last 50 years and to use these events to inform the identification of basins at greatest risk of political stress in the near future (5-10 years). The study is divided into three components:Compilation and assessment of relevant biophysical, socio-economic and geopolitical data in a global Geographic Information System (GIS), and use of these factors to determine history-based indicators for future tensions along international waterways.Using these indicators, identification of basins at risk for the coming decade.Identification and assessment of the potential for mitigating factors and new technologies resulting in a future different than that predicted by history-based indicators. In general, we find that most of the parameters regularly identified as indicators of water conflict are actually only weakly linked to disputes, but that institutional capacity within a basin, whether defined as water management bodies or treaties, or generally positive international relations are as important, if not more so, than the physical aspects of a system. It turns out then that very rapid changes, either on the institutional side or in the physical system, which outpace the institutional capacity to absorb that change, are at the root of most water conflict, as reflected in two sets of indicators: 1) “internationalized” basins, i.e. basins which include the management structures of newly independent states, and 2) basins which include unilateral development projects and the absence of cooperative regimes. By taking our parameters of rapid change as indicators-internationalized basins and major planned projects in hostile and/or institution-less basins-we are able to identify the basins with settings which suggest the potential for political stresses in the coming five to ten years. These basins include: the Ganges-Brahmaputra, Han, Incomati, Kunene, Kura-Araks, Lake Chad, La Plata, Lempa, Limpopo, Mekong, Ob (Ertis), Okavango, Orange, Salween, Senegal, Tumen and Zambezi. We then identify “red flags,” or markers related to these indicators, which might be monitored in the future. Finally, recognizing that history-based indicators may lose validity over time in a rapidly changing world, we ask, “what about the future, which may look nothing like the past,” and focus on four topics: new technologies for negotiation and management; globalization, privatization and the WTO; the geopolitics of desalination; and the changing sources of water and the changing nature of conflict.

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Kravchenko, Angelina. "Religion in the identity structure based on Serhiy Zhadan novels." Synopsis: Text Context Media 26, no. 2 (2020): 32–41. http://dx.doi.org/10.28925/2311-259x.2020.2.3.

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Religion is an important component of Ukrainian society and culture, but we are currently in a situation of reconstructing national identity, so the question is which place religion will take in the new construct? The formation of religion in the structure of identity, in addition to the media, is also influenced by literature, but this influence is more complex and contains hidden intentions, so the analysis of religion in the identity structure of modern literary works is relevant and not enough studied. The works by Serhiy Zhadan stand out with a special outrageousness, including images of a religious orientation. At first glance, it seems that in these texts the author deconstructs, destroys and speaks ironically of the established religious images and symbols, demonstrating the uselessness of religion in modern society. However, the outward outrage hides the attempts to cite examples of identity construction, in which religion is given a certain place. The aim of the article is to consider the representation, dynamics of development, artistic functions, and role of religion in the structure of character identity in Serhiy Zhadan's novels of 2004–2017 (“Depesh Mod” “Voroshylovhrad”, “Internat”). Methods of classification and modelling, sociopsychological, and hermeneutic interpretation, comparison, deconstruction, and methods of postcolonial studies have been used in the analysis. The study has found that religion has a different role and value in each of the novels. In “Depesh Mod”, religion is presented as an “another” phenomenon that is abstract and incomprehensible and has no real embodiment; the narrator speaks ironically of the bearers of religious identity, but at the same time takes quite seriously the image of Jesus. In “Voroshylovhrad” religion acts as a phenomenon of “own” and plays almost the most important role in the formation of group identity of the character; moreover, here we have a sample of religion, where abstract ideas are reconciled with the material world and values. In the “Internat” the emphasis is on the formation of national identity, and therefore the author addresses religion much less, demonstrating its inability to answer the question “own – another's” in terms of national identification. These three texts also present examples of the deconstruction of religion: religious images and symbols are presented in real-life situations far removed from the traditional religious context of Scripture or the temple. The novelty of the article lies in the problem posed, because the study of religion in the structure of the identity of works of art has little attention (in contrast to the study of intertextual links between literature and the Bible). The practical significance is an idea of studying religion in the structure of identity through the involvement in the analysis of strata of national-ethnic, cultural, ethical, traditional, and moral issues.

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Васильева, Дарина Сергеевна. "POSSIBILITIES OF FRAME ANALYSIS WHEN SIMULATING THE SENSE SPACE OF A TALK-SHOW (ON THE MATERIAL OF ANNOTATIONS TO TELEVISION SHOW “ANDREY MALAKHOV. PRYAMOY EFIR”)." Tomsk state pedagogical university bulletin, no. 3(221) (May 16, 2022): 15–22. http://dx.doi.org/10.23951/1609-624x-2022-3-15-22.

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Введение. Ток-шоу представляют собой популярный жанр современного телевидения, что обусловливает интерес к их изучению. Жесткий сценарий с распределенными ролями участников, конфликтный характер коммуникации между ними формируют смысловое пространство, в котором сталкиваются противоречивые нормы, ценности, оценки. Фреймирование межличностных отношений, транслируемых в передачах, позволяет реконструировать модель мира, которую транслирует этот жанр.Цель – моделирование фреймов, отражающих смысловое пространство передач «Андрей Малахов. Прямой эфир».Материал и методы. В работе рассматриваются названия и аннотации выпусков одного из развлекательных ток-шоу на российском телевидении «Андрей Малахов. Прямой эфир» за первое полугодие 2018 года. Тексты взяты с официального сайта канала «Россия 1». Объем исследуемого материала – 110 аннотаций с названиями. По отношению к исходным видеозаписям аннотации являются вторичными текстами интерпретирующего типа. В качестве методов, предваряющих фреймирование, применены интроспекция, контент-анализ частотных речевых единиц, контекстуальный анализ всех речевых предикатов. Таким образом, процедура выделения фреймов основана на качественно-количественных методиках анализа лексических и синтаксических единиц. Результаты и обсуждение. Фреймы, выделенные по текстам аннотаций ток-шоу «Андрей Малахов. Прямой эфир», состоят из четырех слотов: «субъект X» – главный герой передачи, «объект Y» – его оппонент (в некоторых фреймах он деактуализирован), «предикат РД» – доминирующее речевое действие, «предмет Р» – обсуждаемые в передаче ситуации. Один из распространенных фреймов «X обвиняет Y’а в P» содержится в аннотациях к 22 передачам. X и (или) Y как правило публичные люди или связанные с ними лица. Субъект и объект выражены идентифицирующими именами собственными, номинациями по принадлежности к социальной группе, терминами правового дискурса, характеризующими лексемами. Негативно окрашенные характеристики X’ам и Y’ам даются со стороны носителей противоположной точки зрения. В большинстве обозначений участников передачи изначально заложена конфликтность. Предикат речевого действия – глагол «обвиняет». В составе аннотаций обвинение выражается эксплицитно («обвинила») либо нейтральными словами с семантикой речи, вводящими негативно-оценочную информацию (рассказала, что Y испортила ей жизнь), либо лексемами, обозначающими негативное эмоциональное состояние обвиняющего (возмущается). Основание для обвинения, «ситуация Р», как правило, выражено эксплицитно, прямо соотносится с темами передач; эксплицитные номинации чередуются с такими, где указание на повод для обвинения содержится в пресуппозитивном компоненте высказывания.Заключение. Посредством фреймирования аннотаций показано, как устроено смысловое пространство токшоу «Андрей Малахов. Прямой эфир». На основе сопоставления текстов, выявления их сходств и различий по разным параметрам выделено восемь глобальных речевых действий, используемых в формате данной программы. Одним из наиболее частотных речевых действий является обвинение. Моделирование фрейма «X обвиняет Y’а в Р» позволило определить типовых участников коммуникации, типовые жизненные ситуации, обобщить эти сведения в границах слотов. Очевидно, что предикат «речевое действие обвинение» имеет конфликтный характер. Наполнение слотов «субъект X», «объект Y», «ситуация Р – основание для обвинения» подтвердило конфликтную заряженность смыслового пространства ток-шоу. Одна и та же оценочная номинация в рамках передачи может быть амбивалентной – соотноситься с обвиняющим и обвиняемым, что размывает позицию создателей ток-шоу. Оценочная амбивалентность, а также публичность участников, обыгрывание ситуации судебного расследования посредством использования маркеров правового дискурса повышают степень конфликтности рассматриваемого телевизионного жанра. Introduction. Talk-shows are a popular genre of modern television, which leads to an interest in their study. A tough scenario with distributed roles of participants, the conflicting nature of communication between them form a semantic space in which conflicting norms, values, and assessments collide. The framing of interpersonal relations, broadcast in the programs, allows you to reconstruct the model of the world that this genre is broadcasting. Aim and objectives – modeling of frames reflecting the semantic space of programs “Andrey Malakhov. Pryamoy efir”. Material and methods. The article examines the titles and annotations of episodes of one of the entertaining talk shows on Russian television “Andrey Malakhov. Pryamoy efir” for the first half of 2018. The texts were taken from the official website of the Russia 1 channel. The volume of the material under study is 110 annotations with titles. In relation to the original video recordings, annotations are interpretive type secondary texts. Introspection, content analysis of frequency speech units, contextual analysis of all speech words are used as methods preceding framing. Thus, the procedure for allocating frames is based on qualitative and quantitative analysis methods. Results and discussion. Frames selected from the annotation texts of the talk show “Andrey Malakhov. Pryamoy efir”, consist of four slots: “subject X” – the main character of the program, “object Y” – his opponent (in some frames it is deactivated), “predicate RD” – the dominant speech action, “subject P” – discussed in the program situations. One of the common frames “X blames Y-a for P” is contained in the annotations for the 22nd programs. X and / or Y are usually public figures or persons associated with them. The subject and the object are expressed by identifying proper names, nominations for belonging to a social group, terms of legal discourse, characterizing lexemes. The negatively colored characteristics of X-am and Y-am are given from the side of the carriers of the opposite point of view. In most of the designations of the participants in the program, conflicts are initially laid down. The predicate of speech action is the verb “accuse”. As part of the annotations, the accusation is expressed explicitly (“accused”), either in neutral speech words that introduce defamatory information (she said that...), or lexemes denoting the negative emotional state of the accuser (outraged). The basis for the accusation, “Situation P”, is usually expressed explicitly, directly related to the topics of the programs; explicit nominations alternate with those where an indication of the reason for the accusation is contained in the presupposive component of the statement. Conclusion. By framing annotations, it is shown how the semantic space of the talk show “Andrey Malakhov. Pryamoy efir” is arranged. Based on the comparison of texts, identification of their similarities and differences in different parameters, eight global speech actions used in the format of this program were identified. One of the most frequent speech actions is accusation. Modeling the frame “X blames Y-a for P” made it possible to determine the typical participants in communication, typical life situations, to generalize this information within the boundaries of the slots. It is obvious that the predicate “speech act of accusation” is of a conflicting nature. The filling of the slots “subject X”, “object Y”, “situation P – grounds for accusation” confirmed the conflicting charge of the talk show’s semantic space. The same appraisal nomination within the program can be ambivalent – correlated with the accuser and the accused, which “dilutes” the position of the talk show creators. Along with evaluative ambivalence, the publicity of the participants and their placement in the field of legal discourse increase the degree of conflict of the considered television genre.

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Wu, Huayi, Zhao Xu, Youwei Jia, and Xu Xu. "Adaptive Distributed Graph Model for Multiple-Line Outage Identification in Large-Scale Power System." IEEE Systems Journal, 2022, 1–11. http://dx.doi.org/10.1109/jsyst.2022.3210009.

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50

Li, Lijuan, Yiwei Zeng, Jie Chen, Yue Li, Hai Liu, and Gangwei Ding. "Electrical DebtRank Algorithm–Based Identification of Vulnerable Transmission Lines in Power Systems." Frontiers in Energy Research 9 (November 24, 2021). http://dx.doi.org/10.3389/fenrg.2021.786439.

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With the increase of complexity of the power system structure and operation mode, the risk of large-scale power outage accidents rises, which urgently need an accuracy algorithm for identifying vulnerabilities and mitigating risks. Aiming at this, the improved DebtRank (DR) algorithm is modified to adapt to the property of the power systems. The overloading state of the transmission lines plays a notable role of stable operation of the power systems. An electrical DR algorithm is proposed to incorporate the overloading state to the identification of vulnerable lines in the power systems in this article. First, a dual model of power system topology is established, the nodes of which represent the lines in the power systems. Then, besides the normal state and failure state having been considered, the definition of the overloading state is also added, and the line load and network topology are considered in the electrical DR algorithm to identify vulnerable lines. Finally, the correctness and reasonability of the vulnerable lines of the power systems identified by the electrical DR algorithm are proved by the comparative analysis of cascade failure simulation, showing its better advantages in vulnerability assessment of power systems.

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