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• W4362733433 abstract "Current microprocessor-based relay protection and automation (RPA) devices supported by IEC 61850 provide access to a large amount of information on the protected or controlled electric power facility in real time. The issue of using such information (Big Data) in order to improve the parameters of technical modification of intelligent electronic devices at digital substations remains unaddressed. Prerequisites arise for designing modern power systems with relay protection devices of a new generation based on new information algorithms. In particular, it is expedient to develop multi-parameter protections using more than one information parameter: modules of current, voltage, derivatives thereof, phase angles, active and reactive resistances, etc. An information approach based on multiple modeling and statistical processing of modeling results is also promising. This article explores the issues of enhanced sensitivity of multi-parameter relay protection using long-range redundancy protection as an example. Transition to “generalized features” is proposed in order to simplify multi-parameter protection and reduction in the computational load on the RPA device. Out of a large number of analyzed indicators (currents, voltages, their derivatives, resistances, increments of currents, angles between current and voltage, etc.), we specify the most informative by using the method of “data compression”. The transition to generalized features simplifies the parameterization of settings, and the process of making a decision by the relay protection device is reduced to obtaining a generalized feature and comparing it with a dimensionless setting in relative terms. For the formation of generalized information features, two mathematical methods are studied: the method of principal components and Fisher’s linear discriminant." @default.
• W4362733433 created "2023-04-10" @default.
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• W4362733433 date "2023-04-08" @default.
• W4362733433 modified "2023-10-18" @default.
• W4362733433 title "Enhanced Readability of Electrical Network Complex Emergency Modes Provided by Data Compression Methods" @default.
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• W4362733433 doi "https://doi.org/10.3390/info14040230" @default.
• W4362733433 hasPublicationYear "2023" @default.
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