A dual-threshold state analysis and fault location method for power system based on random matrix theory

Zhang, Juan; Wu, Dinghui

doi:10.1007/s11071-021-07056-0

Cited by 4 publications

(2 citation statements)

References 21 publications

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“…e coefficient of variation is an important statistical indicator reflecting the dispersion and fluctuation of data, it is mainly for the comparison of data that cannot be measured uniformly using variance and standard deviation and whose units or means are different, the coefficient of variation is the ratio of the standard deviation and the arithmetic mean of the data, and it is a normalized measure of the degree of dispersion and facilitates the comparison of data [23]. By definition, it can be seen that the value of the coefficient of variation is influenced by the mean value and standard deviation.…”

Section: Reliability Results Of Sports Training Evaluation Indexmentioning

confidence: 99%

Reliability Analysis of Sports Training Evaluation Index Based on Random Matrix

Chen

Jiang

2022

Mathematical Problems in Engineering

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This paper presents an in-depth study and analysis of the reliability of indicators for the evaluation of sports training using the algorithm of random matrices. Random matrix theory is used to obtain the degree of randomness of the data and the overall correlation characteristics of the data through statistical analysis of the energy spectrum and eigenstates of complex systems. Using the results of random matrix theory on the eigenvalues of the sample covariance matrix, the energy of each subspace is estimated, and the estimated energy is then used to construct the subspace weighting matrix. The problem of reliable finite-time stability of the model under several types of uncertain time-lagged bounded transfer probability Markov jump parameter compatibility indicators is also explored. The four basic theoretical issues, namely, value orientation, construction basis, construction principles, and conceptual model of the sports training work evaluation index system, are studied. This paper takes the construction of a sports training evaluation index system as the research object and uses the literature method, expert interview method, questionnaire survey method, data analysis method, Delphi method, and hierarchical analysis method as the main research methods to construct a set of sports training evaluation index system as the research task, to enrich the idea of sports training evaluation work, and to provide a reference for the future government to be able to develop a sports training evaluation index system that is in line with the development of the times. The research method was used to collect the opinions of experts. The subjective opinions given by experts were collected using the assignment method, and the weight coefficients of each index were calculated using the AHP hierarchical analysis method. The result is that the index of basic conditions (0.3591) has the largest weight in the whole system. After that, organization and management (0.1911), work effectiveness (0.1376), staffing (0.103), activity development (0.0828), financial and fund management (0.0562), publicity and reporting (0.0382), and material provision (0.032) are in order. The evaluation results of the index system are consistent with the current actual situation of specialization teaching, indicating that the index system for evaluating the effectiveness of high school sports training has good validity.

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Section: Reliability Results Of Sports Training Evaluation Indexmentioning

confidence: 99%

Reliability Analysis of Sports Training Evaluation Index Based on Random Matrix

Chen

Jiang

2022

Mathematical Problems in Engineering

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“…Among them, the fault ranging method mainly includes the injection method [6,7], the impedance method [8][9][10] and the traveling wave method [11][12][13][14]. Fault zone location methods mainly include the zero sequence current comparison method [15,16], the harmonic component method [17,18], the medium resistance method [19,20], the matrix method [21][22][23][24] and the artificial intelligence method [25][26][27][28][29].…”

Section: Introductionmentioning

confidence: 99%

Distribution Network Regionalized Fault Location Based on an Improved Manta Ray Foraging Optimization Algorithm

Zhang

Liu

2022

Electronics

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To address the problem that the accuracy of traditional intelligent algorithms in distribution network fault location decreases with the expansion of distribution network scale, a regionalized fault location method for distribution networks containing distributed power sources based on the improved manta ray foraging optimization (IMRFO) algorithm is proposed. First, the global convergence property of the basic manta ray foraging optimization (MRFO) algorithm is improved by fusing the restart strategy and the opposition-based learning strategy. Then, based on the two-port equivalence principle, a topological model for regionalized fault hierarchical localization in distribution networks is constructed. Finally, the algorithm is improved by binary discretization using the Sigmoid function to output the fault vector and complete the fault location of the distribution network. Simulation experiments are conducted using MATLAB for IEEE-33 node distribution networks and the simulation results show that the IMRFO algorithm combined with the regionalization of complex distribution networks has a better effect of dimensionality reduction. Compared with the traditional distribution network simulation model, the fault location fault tolerance is greatly improved and its accuracy rate is increased by 1.8% and the location speed is improved by 15.537 ms.

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