Diagnostics of the technical condition of electric network equipment based on fuzzy expert estimates

The paper describes a new possible method of diagnostics of the current technical condition of equipment using a mathematical model based on fuzzy expert estimates and the theory of fuzzy sets. The specifics of the task is determined mainly by the type of the obtained estimates, namely: causal relationships between the controlled parameters of the transformer equipment and defects that could entail their change and the possibility of further operation of the facility. At the same time, attention is paid to the problem of the degree of consistency of expert opinions that affects the quality of the assessment of the current technical condition of the studied object. The paper provides a comparative analysis of the arithmetic mean estimates and median estimates of the consistency of expert opinions. It is shown that the significant drawback of the arithmetic mean approach is its instability towards outliers of individual opinions moving the resulting value under the influence of the “dissident expert opinions”. On the other hand, the median estimate is free of such shortage; it is more outlier-resistant and simply discards a part of radically outlying expert opinions. For the first time, the Kemeny median has been used for technical diagnostics. Kemeny median is based on the introduction of a metric to the set of expert opinions, and axiomatic introduction of the distance between them. Also, the paper formulates a criterion on how to determine the optimal number of experts in the group. © 202

Comparison of Mathematical Methods for Compensating a Current Signal Under Current Transformers Saturation Conditions

Current measurements from electromagnetic current transformers are essential for the construction of secondary circuit systems, including for protection systems. Magnetic core of these transformers are at risk of saturation, as a result of which maloperation of protection algorithms can possibly occur. The paper considers methods for recovering a current signal in the saturation mode of current transformers. The advantages and disadvantages of methods for detecting the occurrence of current transformers core saturation are described. A comparative analysis of mathematical methods for recovering a current signal is given, their approbation was carried out, and the most promising of them was revealed. The stability and sensitivity of recovery methods were tested by adding white noise to the measured signal and taking into account the initial flux density (remanent magnetization) in the current transformers core. Their comparison is given on the basis of angular, magnitude, and total errors at a given simulation interval. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.Funding: This work was supported in part by the International Cooperation Project of National Natural Science Foundation of China under Grant 41761144079, in part by the Strategic Priority Research Program of the Chinese Academy of Sciences, in part by the Pan-Third Pole Environment Study for a Green Silk Road under Grant XDA20060303, in part by the K. C.Wong Education Foundation under Grant GJTD-2020-14, in part by the CAS PIFI Fellowship under Grant 2021PC0002, in part by the Xinjiang Tianchi Hundred Talents Program under Grant Y848041, in part by the CAS Interdisciplinary Innovation Team under Grant JCTD-2019-20, in part by the project of the Research Center of Ecology and Environment in Central Asia under Grant Y934031, and in part by the Regional Collaborative Innovation Project of Xinjiang Uygur Autonomous Regions under Grant 2020E01010

Power Flows and Losses Calculation in Radial Networks by Representing the Network Topology in the Hierarchical Structure Form

This paper proposes a structured hierarchical-multilevel approach to calculating the power flows and losses of electricity in radial electrical networks with different nominal voltages at given loads and voltages of the power source. The researched electrical networks are characterized by high dimensionality, dynamism of development, but also insufficient completeness and reliability of state information. The approach is based on the representation of the initial network graph in the form of a hierarchical-multilevel structure, divided into two stages with rated voltages Unom ≤ 35 kV and Unom ≥ 35 kV, and using the traditional (manual) engineering two-stage method, where the calculation is performed in a sequence from bottom to top (stage 1) and from top to bottom (stage 2), moving along the structure of the network. The application of the above approach makes it possible to obtain an algorithm for implementation on a computer, which is characterized by universality (for an arbitrary configuration and complexity of the network), high performance and low requirements for the computer memory. © 2022 by the authors. Licensee MDPI, Basel, Switzerland.Funding: This work was supported in part by the International Cooperation Project of National Natural Science Foundation of China under Grant 41761144079, in part by the Strategic Priority Research Program of the Chinese Academy of Sciences, in part by the Pan-Third Pole Environment Study for a Green Silk Road under Grant XDA20060303, in part by the K. C. Wong Education Foundation under Grant GJTD-2020-14, in part by the Research Fund for International Scientists of National Natural Science Foundation of China under Grant 42150410393, in part by the CAS PIFI Fellowship under Grant 2021PC0002, in part by the Xinjiang Tianchi Hundred Talents Program under Grant Y848041, in part by the CAS Interdisciplinary Innovation Team under Grant JCTD-2019-20, in part by the project of the Research Center of Ecology and Environment in Central Asia under Grant Y934031, and in part by the Regional Collaborative Innovation Project of Xinjiang Uygur Autonomous Regions under Grant 2020E01010

A Statistical-Based Approach to Load Model Parameter Identification

In the last few years, a great number of methods for identifying the load model parameters have been proposed. This article discusses the use of statistical approach to estimate the substation equivalent load model parameters for supplying to oil-producing industrial region. The disadvantages of existing statistical approach are the low accuracy obtained for the parameter estimates, especially when using samples size is small. To eliminate this deficiency, the current measurement data archive from SCADA system of electrical parameters for 15 months was collected. For the purpose of verifying the obtained results of statistical processing of SCADA data, a full-scale experiment was carried out in relation to the studied substation. The article describes the statistical method used to process the current SCADA measurement data, the results of archived statistical processing and experimental SCADA data. The electrical load models' parameters received from the experimental studies results are of practical importance. © 2013 IEEE.This work was supported in part by the Strategic Priority Research Program of the Chinese Academy of Sciences, in part by the Pan-Third Pole Environment Study for a Green Silk Road under Grant XDA20060303, in part by the K. C. Wong Education Foundation under Grant GJTD-2020-14, in part by the International Cooperation Project of National Natural Science Foundation of China under Grant 41761144079, in part by the CAS PIFI Fellowship under Grant 2021PC0002, in part by the Xinjiang Tianchi Hundred Talents Program under Grant Y848041, in part by the CAS Interdisciplinary Innovation Team under Grant JCTD-2019-20, in part by the project of the Research Center of Ecology and Environment in Central Asia under Grant Y934031, and in part by the Regional Collaborative Innovation Project of Xinjiang Uygur Autonomous Regions under Grant 2020E01010

Estimating Accuracy of Experimentally Obtained Power System Zip Load Models

Experimentally obtained ZIP load models are used for the power system analysis. Estimating accuracy of such models is presented in this paper. The dependence of ZIP load model error on the range in which voltage changes during the experiment, the number of measured values of voltage and power, standard deviation of the load change random process have been obtained using the computing experiment. The results could be used to estimate the accuracy of ZIP load models or to design the experiment to determine ZIP load models with prescribed accuracy

Estimating Accuracy of Experimentally Obtained Power System Zip Load Models

Experimentally obtained ZIP load models are used for the power system analysis. Estimating accuracy of such models is presented in this paper. The dependence of ZIP load model error on the range in which voltage changes during the experiment, the number of measured values of voltage and power, standard deviation of the load change random process have been obtained using the computing experiment. The results could be used to estimate the accuracy of ZIP load models or to design the experiment to determine ZIP load models with prescribed accuracy