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Once the short circuit damage accident of a large capacity 500 kV transformer occurs suddenly, it will seriously affect the safe operation of the power grid. The article expounds on the calculation principle and evaluation method of the transformer's ability to withstand short circuit, then introduces the design structure of 400 MVA/500 kV short circuit autotransformer and calculates the electromagnetic force and evaluates the ability to withstand short circuit under high voltage ‐ medium voltage (HV‐MV) and medium voltage ‐ low voltage (MV‐LV) conditions. By comparing with typical 110 kV and 220 kV transformers, the short‐circuit characteristics are analysed, the control strategy is proposed, and the largest capacity short circuit prototype with 400 MVA/500 kV autotransformer is developed. Last, the sudden short circuit test is carried out in the large current test centre. The results show that the large capacity autotransformer passed the big current impulse under HV‐MV and MV‐LV short circuit conditions for the first time in the world, and all indicators are good, which confirms the accuracy of the strength check and the effectiveness of the short circuit evaluation method and also proves that the 500 kV autotransformer has strong strength to withstand short circuits. [ABSTRACT FROM AUTHOR]

Network reconfiguration is a vital analysis process for optimising and controlling distribution systems (DSs). Given a stable initial DS, the distribution feeders can be reconfigured by changing the status of the switches to improve the operational performance. Owing to the fault trip, equipment maintenance, and system extension, the removal or addition of a branch can change the structure of the initial topology. This study proposes a dynamic reconfiguration method that considers the real‐time initial topology variation. The method combines the dynamic topology analysis with network reconfiguration to address the optimisation problem of the real‐time distribution network. A set of independent topological parameters represents the initial topology of a DS. After the changes in the initial topology are detected, the dynamic topology analysis is used to restore network connectivity and identify out‐of‐service areas. Then the real‐time initial topology is obtained by updating the topological parameters. In accordance with network reconfiguration, the optimal configuration is identified to reduce power loss and improve the voltage profile of the real‐time distribution network. Illustrative examples verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

• A new method for calculating and evaluating the radial stability of winding is proposed, and this method is more concise, applicable and accurate. • The critical radial instability of the transformer can be obtained accurately by accumulating and increasing the value of short-circuit current. • The sudden change of reactance during the short-circuit test can reflect the characteristics of sudden deformation and instability of windings, also it can be used as a judgment basis for critical instability. • The test proves that the transformer has an obvious cumulative effect with short-circuit. The radial instability of transformer winding under short-circuit condition is one of the vital factors which lead to failures. There have been many analytic and simulative investigations in the past. However, few contributions show experiments on transformers for radial stability due to the limitation of test conditions and high costs. This paper introduces the calculation of short-circuit force and puts forward the evaluation method of radial stability. Experiments are performed on real 110 kV transformers in order to validate the proposed method. To obtain the radial critical instability state and short-circuit accumulation characteristics, dozens of short-circuit and accumulation tests have been carried out under high voltage - medium voltage (HV-MV) short-circuit conditions. The experimental results prove that the accuracy of the evaluation method of radial stability and the current deviation is less than 5%. The tests show that the critical radial instability of the transformer can be obtained accurately by accumulating and increasing the value of short-circuit current. The sudden change of reactance during the test can reflect the characteristics of sudden deformation and instability of windings, which can be used as a judgment basis for critical instability. Moreover, the tests confirm the existence of short-circuit cumulative effect in a transformer. [ABSTRACT FROM AUTHOR]

Node importance degree is a vital index in distribution network reconfiguration because it reflects the robustness of the network structure by evaluating node importance. Since the traditional reconfiguration ignores this index, the reconstructed network structure may be vulnerable which would reduce the security and stability of the distribution systems. This paper presents a novel reconfiguration strategy considering the node importance. The optimization objectives are the improvement of the node importance degree and the reduction of power loss. To balance the objectives, the reconfiguration mathematical model is formulated as a compound objective function with weight coefficients. Then the quantum particle swarm algorithm is employed to address this compound objective optimization problem. The strategy can model different scenarios network reconfiguration by adjusting the weight vector based on the tendencies of the utility decision maker. Illustrative examples verify the effectiveness of the proposed strategy. [ABSTRACT FROM AUTHOR]

The structure of a distribution network has great effects on economy, power supply reliability and investment of a power system. To obtain an optimal topology from possible topologies, we need to solve an optimisation problem which aims to find a radial structure satisfying operating constraints. As a basis of solving this optimisation problem, the encoding scheme, is to represent the candidate configurations by a series of codes. Numerical candidate topologies and unfeasible codes would lead low efficiency or premature convergence. This paper presents an effective scheme which can rapidly produce all radial configurations of a distribution network. In order to reduce the computational requirement of solution space, initial network is simplified as a topological graph which reserves loop branches and T-nodes. And a loop-branch chain incidence matrix is derived from analyzing the relationship between any two loops. Then the principles of selecting switches of each variable are designed to determine the ranges of the variables. All radial candidate solutions are available rapidly through applying the theory of combination. The scheme presented minimizes the number of solutions and avoids tedious radial checking procedure in view of avoiding any infeasible solutions. The validity of the proposed scheme is verified by illustrative examples. [ABSTRACT FROM AUTHOR]

This work presents a methodology for distribution system feeder reconfiguration considering different model of DGs with an objective of minimizing real power loss. The distributed generation availability of wind turbines, solar photovoltaic panels and fuel cell etc., are classified into different models according to their operation modes and control characteristics. Decimal coded quantum particle swarm optimization (DQPSO) has been applied to solve feeder reconfiguration of DGs. The method applies decimal encoding to quantum particle swarm optimization (QPSO), which can decrease the particle length, generate few infeasible solutions and have better search efficiency. Aiming to the problem that the reactive power output of PV model sometimes exceeds the limit, this paper researches the impact factors of the output reactive power during reconfigurations, such as rated active power and rated voltage magnitude. The method has been tested on IEEE 33-bus and PG&E 69-bus radial distribution systems to demonstrate the performance and effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Abstract: A novel method for fault diagnosis in analog circuits using S-transform (ST) as a preprocessor and a quantum neural network (QNN) as a classifier is proposed in this paper. The ST provides a frequency-dependent resolution and the features obtained from ST are distinct, and easy to understand. The QNN identifier, a computational tool for fuzzy classification combining the advantages of neural modeling and fuzzy-theoretic principles, has the ability to autonomously detect the presence of uncertainty, adaptively learn the existing uncertainty, properly approximate any membership profile, and autonomously quantify uncertainty in sample data. The comparison between the ST-based method and the wavelet-transform-based method, and comparison between the QNN method and the traditional NN method for analog fault diagnosis is provided. Simulation results show that the proposed method is effective in enhancing the efficiency of the training phase and the performance of the fault diagnostic system. The results clearly indicate more than 97.61% correct classification of fault classes in the example circuits of various sizes in the presence of similar faults. [Copyright &y& Elsevier]

In this paper, an identification scheme for sandwich systems with a dead zone is proposed. In this scheme, a so-called combinational input is proposed to transform the sandwich model with a dead zone into a model with separated parameters. Then, the recursive general identification algorithm can be applied to the parameter-estimation, since the transformed model has a form that is linearized in coefficients. Finally, the proposed method is applied to the identification of an X–Y moving positioning stage. [ABSTRACT FROM PUBLISHER]

A novel method of stimuli design for analogue circuit fault diagnosis is presented based on a genetic algorithm and wavelet packet decomposition. The method is characterised by reduced fault ambiguity and more accurate fault classification. Computation is also reduced because the method does not require matrix inversion and calculation. The proposed method is suitable for transient and AC input sources and can be applied to both linear and nonlinear circuits. [ABSTRACT FROM AUTHOR]

A novel method for fault diagnosis of analog circuits with tolerance based on wavelet packet (WP) decomposition and probabilistic neural networks using genetic algorithm (GPNN) is proposed in this paper. The fault feature vectors are extracted after feasible domains on the basis of WP decomposition of responses of a circuit being solved. Then by fusing various uncertain factors into probabilistic operations, GPNN methods to diagnose faults are proposed whose parameters and structure obtained form genetic optimisations resulting in best detection of faults. Finally, simulations indicated that GPNN classifiers are correct 7% more than BPNN of the test data associated with our sample circuits. [ABSTRACT FROM AUTHOR]

In cyber–physical power systems (CPPSs), the interaction mechanisms between physical systems and cyber systems are becoming more and more complicated. Their deep integration has brought new unstable factors to the system. Faults or attacks may cause a chain reaction, such as control failure, state deterioration, or even outage, which seriously threatens the safe and stable operation of power grids. In this paper, given the interaction mechanisms, we propose an interdependent model of CPPS, based on a characteristic association method. Utilizing this model, we can study the fault propagation mechanisms when faulty or under cyber-attack. Simulation results quantitatively reveal the propagation process of fault risks and the impacts on the CPPS due to the change of state quantity of the system model. [ABSTRACT FROM AUTHOR]

A principal component analysis‐based blind wideband spectrum sensing (WSS) algorithm is presented, in which the WSS issue is transformed into a sequential binary hypothesis test under the framework of the general likelihood ratio test. The proposed method operates simultaneously over all the subbands rather than one single subband each time. Furthermore, the new method overcomes the noise uncertainty problem, and can also perform well without information about the channel, the primary signal, and the noise power. Most importantly, unlike the existing classical blind wideband detectors based on the information theoretic criterion, the decision threshold for the proposed detector can be flexibly determined according to the target false‐alarm probability. Simulation results verify its effectiveness and superiority to the existing sensing algorithms. [ABSTRACT FROM AUTHOR]

In this paper, a model of the Kelvin probe is established in COMSOL Multiphysics based on electrostatic field theory, and it is verified by measuring the surface potentials. The influence of the probe is also investigated. An improved charge inversion method based on surface potentials measured online is proposed. The surface charge density is directly obtained by the Gauss's theorem to avoid the calculation of the inversion matrix. The improved method is verified by comparing the surface charge density calculated by the analytical method. When considering the effect of the probe, the maximum difference in surface charge density is 0.3 µC/m2 comparing to that when ignoring its effect, and the percentage of the difference is as high as 41%. The results indicate that the effects of the voltage of the probe under online measurement conditions must be considered. [ABSTRACT FROM AUTHOR]