Estimation of the acceptable risk level of emergency situation in the electric power engineering system using fuzzy models

Authors

DOI:

https://doi.org/10.15588/1607-6761-2019-2-4

Keywords:

acceptable risk, fuzzy model, fault, power system, expert estimation.

Abstract

Purpose. The development of a model for assessing the level of permissible risk of an emergency situation in the power system in the conditions of fuzzy input data, heterogeneity of the criteria for risk assessment, the absence of analytical links between them and the subjectivity of expert knowledge of decision makers.

Methodology. To solve this problem, methods and models of fuzzy logic are used which give satisfactory analytical result in the conditions of uncertainty of the input information and the absence of analytical connections between the individual parameters and characteristics of the object. The proposed fuzzy models are constructed using the Fuzzy Output Algorithm of Mamdani.

Findings. The result obtained by the fuzzy model gives the opportunity to assess reliably the acceptable level of risk of an emergency situation in the grid. Based on the magnitude of the risk, it is possible to make informed decisions regarding the expediency (or impracticability) of applying measures to reduce this risk. This enables the organization of preventive management of the risk of an emergency situation in the grid and the use of effective measures to reduce it.

Originality. The article is devised a fuzzy model for estimating the permissible risk level of an emergency situation in the electric power system, which takes into account such criteria as the minimum possible level of risk, the influence of meteorological conditions and errors of operational and operational personnel of power systems. In this case, it is possible to take into account the main factors influencing the reliability of the grid functioning, to assess the risk level of an emergency situation..

Practical value. The fuzzy models developed in the article provide an opportunity to carry out an express assessment of the level of permissible risk of an emergency situation in the conditions of limited data and evaluation criteria, to conduct a comparative analysis of the obtained result with the magnitude of the actual risk of an accident in the on-line mode and to make a decision as to the appropriateness of its reduction.

Author Biographies

M.V. Kosterev, National technical university of Ukraine “Kyiv polytechnic institute” named by I. Sikorski

Sci.D, Professor, Professor of the renewable sources of energy department of the National technical university of Ukraine “Kyiv polytechnic institute” named by I. Sikorski, Kiev

V.V. Litvinov, PJSC “Ukrhydroenergo”, branch “Dnipro HPP”

Ph.D, Technical department chief of Dnipro HPP PJSC “Ukrhydroenergo”, Zaporizhzhia

References

[1] Кosterev M.V., Litvinov V.V. (2015). Rozroblennia analitychnogo metodu otsniuvannia ryzyku vynyknennia avariinoi situatsii v energosystemi. Vostochno-evropeiskii zhurnal peredovyh technologiy. Sistemy upravlenia v promyshlennosti, 4/2 (76), 44 – 50. (in Ukrainian.)

[2] Sistemy otsenki riskov. Dopustimyi risk. http://www.scriru.com/5/85815577381.php (in Russian.)

[3] Litvinov V.V. (2012). Otsinka ryzyku porushennia stiikosti dvygunovogo navantazhennia pry vidmovah elektroobladnannia v pidsystemi EES. Avtoreferat dissertatsii na zdobuttia naukovogo stupenia kandidata technichnyh nauk, 20 (in Ukrainian).

[4] Кosterev M.V., E.I. Bardyk, Litvinov V.V. (2015). Risk Estimation of Induction Motor Fault in Power System. WSEAS Transactions on Power Systems, 4, 8, 217 – 226.

[5] Travis C.C., Hattemer-Frey H.A. (1988) Determining an acceptable level of risk. Environ. Science Technology, 22, 8, 873 – 876.

[6] Bell R., Glade T., Danscheid M. (2005). Challenges in defining acceptable risk levels, 10.

[7] Hunter P. Fewtrell L. (2010). Acceptable risk, 10, 207 – 227.

[8] Handschin E., Jurgens I., Neumann C. (2008) Long term optimization for risk-oriented asset management. 16th Power Systems Computation Conference.

[9] Schwan M., Schilling C., Zickler U. (2006). Component reliability prognosis in asset management methods. 9th International Conference of Probabilistic Methods Applied to Power Systems.

[10] Remennikov V. (2005). Upravlencheskie reshenia. Minsk: Uniti , 144. (in Russian.)

[11] Sysoev A.V. (2005). Printsypy otsenki nadiozhnosti ekspluatatsionnogo personala. Nauchnyi vestnik MGTU, 90(8), 156-160. (in Russian.)

[12] Shtovba S.D. (2007). Proektirovanie nechetkih system sredstvami MATLAB. M.: Goriachaia linia - Telekom, 288. (in Russian.)

[13] Leonenkov A.V. (2005). Nechetkoe modelirovanie v srede MATLAB I FuzzyTECH. SpB.: BHV - Peterburg, 736. (in Russian.)

[14] Kruglov V.V., Dli M.I., Golupov R.Yu. (2003). Nechetkaya logika i iskusstvennye neironnye seti. M.: Goriachaia linia - Telekom, 226. (in Russian.).

[15] Riid A. (2002). Transparent Fuzzy Systems: Modeling and Control. PhD Thesis, 227.

[16] Saaty T.L. (1990). Eigenweightor an logarithmic lease squares. Eur. J. Oper. Res., 48, N1, 156 – 160.

Published

2019-07-01

How to Cite

Kosterev, M., & Litvinov, V. (2019). Estimation of the acceptable risk level of emergency situation in the electric power engineering system using fuzzy models. Electrical Engineering and Power Engineering, (2), 43–50. https://doi.org/10.15588/1607-6761-2019-2-4