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An Automated System for Taking Decisions to Assess the Actual State of Electrical Equipment1

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Power Technology and Engineering Aims and scope

An automated system for taking decisions for a complex estimate of the technical state of the electrical network equipment of electric power plants and substations, in order to increase its operating efficiency and to correct repair cycles, is proposed. The main states of the system, which are based on methods of artificial intelligence—artificial neural networks and fuzzy logic methods, which provide the system with self-teaching and self-adjustment properties, are described. An example of the estimate of the technical state of a 110 kV power transformer based on data of a chromatography analysis of the gases dissolved in the oil and using this system is given.

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References

  1. A. I. Khal’yasmaa, S. A. Dmitriev, and S. E. Kokin, “Problems of constructing systems for estimating the actual state of electrical equipment for power companies,” Nauch. Obozrenie, No. 4 (2014).

  2. A. I. Khal’yasmaa, S. A. Dmitriev, and S. E. Kokin, “A system for controlling technically active electric network enterprises,” Promyshl. Énerget., No. 2 (2014).

  3. A. I. Khal’yasmaa, S. A. Dmitriev, S. E. Kokin, D. A. Glushkov, and M. V. Osotova, “Principles for estimating the technical state of the electrical equipment in substations,” Élektrichestvo, No. 10 (2014).

  4. A. I. Khal’yasmaa, S. A. Dmitriev, and S. E. Kokin, “Prerequisites and principles for using artificial neural network methods to analyze technical diagnostic data of electric equipment for 35 – 110 kV substations,” Nauch. Obozrenie, No. 2 (2013).

  5. A. I. Khal’yasmaa, S. A. Dmitriev, and S. A. Eroshenko, “Membership functions for the formation of the electrical equipment state estimation for power stations and substations,” Adv. Mater. Res., 805 – 806 (2013).

  6. Regulating Document RD 153-34.046.302–00. Systematic Indications on the Diagnostics of Developing Defects of Transformer Equipment from the Results of a Chromatography Analysis of Gases Dissolved in the Oil [in Russian].

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Authors and Affiliations

  1. First President of Russia B. N. El’tsin Ural Federal University, Ural Power Institute, Yekaterinburg, Russia

    A. I. Khal’yasmaa, S. A. Dmitriev & S. E. Kokin

Authors
  1. A. I. Khal’yasmaa
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  2. S. A. Dmitriev
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  3. S. E. Kokin
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Corresponding author

Correspondence to A. I. Khal’yasmaa.

Additional information

Translated from Élektricheskie Stantsii, No. 8, August 2015, pp. 39 – 42.

1This paper was prepared from the proceedings of the conference “Electric Power with Youthful Eyes – 2014” (Section “Modeling and Control of Electric Power Systems”).

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Khal’yasmaa, A.I., Dmitriev, S.A. & Kokin, S.E. An Automated System for Taking Decisions to Assess the Actual State of Electrical Equipment1 . Power Technol Eng 49, 389–392 (2016). https://doi.org/10.1007/s10749-016-0634-6

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  • DOI: https://doi.org/10.1007/s10749-016-0634-6

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