Increasing Certainty of Fault Identification in Power Transformers of Power Plants by Setting Parameters for Fuzzy Model

Authors

DOI:

https://doi.org/10.20535/1810-0546.2017.6.112488

Keywords:

Model, Fuzzy logic, Electrical equipment, Risk assessment, Damage, Failure

Abstract

Background. Problem of ensuring reliability and safety operation of thermal, nuclear and hydro power plants is exacerbated under increasing accident in modern electric power systems due to power equipment failures. Therefore, deve­lopment of adequate mathematical models for technical condition determination and risk assessment of power transformer failure in power plants is relevant.

Objective. The aim of the paper is to improve the diagnostic fuzzy model of power transformer technical condition by setting parameters and risk failure assessment under presence damage.

Methods. The mathematical model of power transformer used approaches based on fuzzy sets theory, fuzzy logic and nonlinear optimization methods. Risk assessment of power transformer failure under presence damage was solved based on formed hierarchy factors and parameters of influence on integral risk indicator of power transformer failure.

Results. The necessity of complex simulation of technical condition of power transformer and electric power system modes is substantiated. The fuzzy model of power transformer technical condition evaluation was upgraded by parametrically identifying the optimal function values of fuzzy terms of linguistic variables.

Conclusions. A mathematical model of risk assessment of power transformer failure with presence damage was proposed for emergency risk estimation in electric power systems under electrical equipment failures.

Author Biographies

Eugen I. Bardyk, Igor Sikorsky Kyiv Polytechnic Institute

Євген Іванович Бардик  

Nickolai V. Kosterev, Igor Sikorsky Kyiv Polytechnic Institute

Микола Володимирович Костерєв 

Nickolai P. Bolotnyi, Igor Sikorsky Kyiv Polytechnic Institute

Микола Петрович Болотний

References

B. Alekseev, Control of State of Power Transformers. Moscow, Russia: NC ENAS, 2002 (in Russian).

N. Kosterev and E. Bardyk, The Issue of Building Fuzzy Models of the Technical Condition Evaluation of the Objects of Electrical Systems. Kyiv, Ukraine: NTUU KPI, 2011 (in Ukrainian).

B. Stogniy et al., “Intelligent electricity networks: experience and prospects of Ukraine”, Pratsi IE NASU, spec. issue, pp. 5–19, 2011 (in Ukrainian).

CIGRE Working Group A2.18. Guide for Life Management Techniques For Power Transformers, CIGRE, Paris, 2003.

P. Lezhnuk et al., “Diagnosis of power transformers using fuzzy sets”, Visnyk Vinnytskogo Politekhnichnogo Instytutu, no. 1, pp. 43–51, 2005 (in Ukrainian).

N. Kosterev and E. Bardyk, “Fuzzy modeling of electrical equipment for technical condition assessment and decision-making about the strategy of further exploitation”, Tekhnichna Elektrodynamika. Tematychnyi Vypusk. Problemy Suchasnoi Elektrotekhniki, part 3, pp. 39–43, 2006 (in Russian).

S. Shtovba, Design of Fuzzy Systems by MATLab Means. Moscow, Russia: Telekom, 2007 (in Russian).

O.V. Shutenko et al., “Method of average risk determination when using the limiting values of gas concentrations in oil”, Energetika i Elektrifikacia, no. 2, pp. 5–19, 2012 (in Ukrainian).

N. Kosterev et al., “A method of diagnosing technical condition of the power transformer on the model of an object under fuzzy information”, Patent Ukraine 65667, 2011 (in Ukrainian).

E.I. Bardyk and N.P. Bolotnyi, “Electric power system simulation for risk assessment of power transformer failure at an external short-circuit fault”, in Proc. 2017 IEEE 1st Ukraine Conf. Electrical Comp. Eng., pp. 452–456, 2017. doi: 10.1109/UKRCON.2017.8100527

Y.-C. Huan and H.C. Sun, “Dissolved gas analysis of mineral oil for power transformer fault diagnosis using fuzzy logic”, IEEE Trans. Dielectr. Electr. Insul., vol. 20, no. 3, pp. 974–981, 2013. doi: 10.1109/TDEI.2013.6518967

R.A. Hooshmand et al., “Adaptive neuro-fuzzy inference system approach for simaltaneous diagnosis of the type and location of faults in power transformers”, IEEE Electr. Insul. Mag., vol. 28, no. 5, pp. 32–42, 2012. doi: 10.1109/MEI.2012.6268440

IEEE Guide for Interpretation of Gases Generated in Oil Immersed Transformer ANSI/IEEE, IEEE Standard C57.104.TM–2008. doi: 10.1109/IEEESTD.2009.4776518

E.I. Bardyk et al., “Fuzzy power transformer simulation for risk assessment of failure at the damage presence”, Pratsi IE NASU, pp. 189–198, 2013 (in Ukrainian).

E.I. Bardyk et al., “Improving reliability of operation of power companies based on risk assessment of emergency situations at the failures of electrical equipment”, Pratsi IE NASU, pp. 13–20, 2014 (in Ukrainian).

Diagnostics of Oil-Filled Transformer Equipment According to the DGA Results of Free Gases Selected from the Gas Relay and Gases Dissolved in the Insulating Oil, SOU-N EE 46.501.2006, 2007.

A.O. Nedosekin, Fuzzy Financial Management. Moscow, Russia: Audit and Financial Analysis, 2003 (in Russian).

R. Yager, “Families of OWA operators”, Fuzzy Sets and Systems, vol. 59, pp. 53–59, 1993.

Published

2017-12-27

Issue

Section

Art