The Techniques for Achieving High Power Equipment Reliability with Distributed Informational System

Arakelian Edik Koyrunovich; Sultanov Makhsud Mansurovich; Evseev Kirill Viktorovich

doi:doi:10.11648/j.epes.20190806.13

| Peer-Reviewed

The Techniques for Achieving High Power Equipment Reliability with Distributed Informational System

Arakelian Edik Koyrunovich, Sultanov Makhsud Mansurovich, Evseev Kirill Viktorovich

Published in American Journal of Electrical Power and Energy Systems (Volume 8, Issue 6)

Received: 1 August 2019 Accepted: 26 November 2019 Published: 24 December 2019

Views: Downloads:

Download PDF

Share This Article

Twitter
Linked In
Facebook

Abstract

The problem of power generating equipment reliability and safety of thermal (TPP), hydro (HPP) and nuclear (NPP) power plants at each its life cycle stage is set and the solution approach is proposed. The blockchain distributed data storage system to unite different members of the energy system is described. It is shown that the suggested technology allows decentralized data storage reliability increase due to the data exists till its last participant leaves and safety is ensured by the electric market participant consensus algorithm. The algorithm for the decentralized blockchain system is developed. The new technique for reliability design calculation based on using both constant and time-varying failure rate is introduced. It is suggested to use control action method expressed as the design, technological and operational parameters from the normative documents. The generalized model of reliability design calculation representing product of three components of failure free operation probability is developed. It is shown that developing new algorithms of statistical data obtaining and designing full repair processes allow planning equipment repair, obtaining and analyzing the corresponding reliability indeces when the equipment is in operation and then choose the most fitting repair time and amount optimization, operation mode selection and power plant long term equipment time in operation forecasting solutions. The technique for the power equipment condition forecasting by archival data stored in the distributed system, the data can be used to predict equipment failures and decide whether it should be repaired. It is shown that the desired prediction accuracy can be achived by using neural network due to its feature to reveal complex relations between input and output values.

Published in	American Journal of Electrical Power and Energy Systems (Volume 8, Issue 6)
DOI	10.11648/j.epes.20190806.13
Page(s)	158-164
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Power Equipment Reliability, Blockchain, Machine Learning

References

[1]	M. M. Sultanov, V. M. Truhanov, EH. K. Arakelyan, M. A. Kulikova Metody dostizheniya i obespecheniya vysokogo urovnya nadezhnosti i bezopasnosti ehnergeticheskogo oborudovaniya TEHS, GEHS, AEHS na vsekh ehtapah zhiznennogo cikla / «Novoe v Rossijskoj EHlektroehnergetike» - Ezhemesyachnyj nauchno-tekhnicheskij ehlektronnyj zhurnal; № 3, mart 2018 g; 6-15 cc.; ISSN 2312-055X
[2]	Sultanov M. M., truhanov V. M. Estimation technique of corrective effects for forecasting of reliability of the designed and operated objects of the generating systems // Applied Physics Letters. – 2017. Conf. Series 891. p 1–12.
[3]	Mamontova M. Y. Blokchejn i vozmozhnosti ego primeneniya v ehnergetike //Informacionnye tekhnologii v nauke, upravlenii, social'noj sfere i me. – 2017. – 417 p.
[4]	Melanie Swan, Blockchain: Blueprint for a New Economy – O’Reilly, 2015.– 152 p.
[5]	«Sovremennaya rynochnaya ehnergetika Rossiyskoy federacii». – M.: AHO «Uchebnyj centr NP «Sovet Rynka», - 368 p.ISBN 978-5-4253-0343-1
[6]	A. V. Mashkov Ekonomika kombinirovannogo proizvodstva teplovoy i elektricheskoy energii: uchebnoe posobie: M-vo obrazovaniya i nauki Rossiyskoy Federacii, Fil. federal'nogo gos. byudzhetnogo obrazovatel'nogo uchrezhdeniya vyssh. prof. obrazovaniya "Nac. issledovatel'skiy un-t "MEI" v g. Volzhskom, Kaf. "Teplovye elektricheskie stancii". - Volzhskiy: Fil. MEI v g. Volzhskom, 2012. – 125 s.; ISBN 978-5-94721-074-3
[7]	Vaskov A. Structure and Parameter Optimization of Renewable-Based Hybrid Power Complexes /A. Vaskov, M. Tyagunov, T. Shestopalova, G. Deryugina, I. Ishchenko //Handbook of Research on Renewable Energy and Electric Resources for Sustainable Rural Development. /Ed. V. Kharchenko (Russia) and P. Vasant (Malaysia), - Hershey, Pennsylvania, IGI Global, 2018 P. 352-382
[8]	Salomon D., Motta G. Handbook of data compression. – Springer Science & Business Media, 2010
[9]	Pravila organizacii tekhnicheskogo obsluzhivaniya i remonta oborudovaniya, zdanij i sooruzhenij ehlektrostancij i setej. SO 34.04.181-2003.-M.: OAO «CKB Energoremont»
[10]	Trukhanov V. M. Nadezhnost' v tekhnike. – 2-e izd., pererab. i dop. – M.: OOO Izdatel'skiy dom «Spektr», 2017. – 656 p.
[11]	Druzhinin G. V. Nadezhnost' sistem avtomatiki. – Izd. 2-e, pererab. i dop. – M.: Energiya, 1967. – 528 p.
[12]	Kozlov B. A., Ushakov I. A. Spravochnik po raschetu nadezhnosti apparatury radioelektroniki i avtomatiki. – M.: Sovetskoe radio, 1975. – 430 p.
[13]	Kapur K., Lamberson L. Nadezhnost' i proektirovanie sistem: Per. s angl. / Pod red. I. A. Ushakova. – M.: Mir, 1980. – 604 p.
[14]	Truhanov V. M. Novyy podhod k obespecheniyu nadezhnosti slozhnyh sistem. – M.: Izdatel'skiy dom «Spektr», 2010. – 247 p.
[15]	Truhanov V. M., Matveenko A. M. Nadezhnost' slozhnyh sistem na vsekh etapah zhiznennogo cikla.– M.: Izdatel'skij dom «Spektr», 2016. The 2^nd issue.– 664 p.
[16]	Sultanov M. M. Ocenka nadezhnosti, prodlenie resursa i optimizaciya remonta oborudovaniya TES i energeticheskih sistem: ucheb. posobie. – Volzhskiy: Filial FGBOU VO «NIU «MEI» v g Volzhskom, 2016. – 100 p.
[17]	Andryushin A. V., ArakelyanE. K., Cykunova S. Yu., Chernyaev A. N. Nadezhnost' sistem upravleniya. Osnovy teorii nadezhnosti: Ucheb.posobie.- Publisher INE NNRU MePHI, 2017, 88p.
[18]	Simon Haykin. Neural Networks and Learning Machines.– Pearson, 2008, 936 p.

Cite This Article

Plain Text BibTeX RIS

APA Style

Arakelian Edik Koyrunovich, Sultanov Makhsud Mansurovich, Evseev Kirill Viktorovich. (2019). The Techniques for Achieving High Power Equipment Reliability with Distributed Informational System. American Journal of Electrical Power and Energy Systems, 8(6), 158-164. https://doi.org/10.11648/j.epes.20190806.13

Copy | Download

ACS Style

Arakelian Edik Koyrunovich; Sultanov Makhsud Mansurovich; Evseev Kirill Viktorovich. The Techniques for Achieving High Power Equipment Reliability with Distributed Informational System. Am. J. Electr. Power Energy Syst. 2019, 8(6), 158-164. doi: 10.11648/j.epes.20190806.13

Copy | Download

AMA Style

Arakelian Edik Koyrunovich, Sultanov Makhsud Mansurovich, Evseev Kirill Viktorovich. The Techniques for Achieving High Power Equipment Reliability with Distributed Informational System. Am J Electr Power Energy Syst. 2019;8(6):158-164. doi: 10.11648/j.epes.20190806.13

Copy | Download

@article{10.11648/j.epes.20190806.13,
  author = {Arakelian Edik Koyrunovich and Sultanov Makhsud Mansurovich and Evseev Kirill Viktorovich},
  title = {The Techniques for Achieving High Power Equipment Reliability with Distributed Informational System},
  journal = {American Journal of Electrical Power and Energy Systems},
  volume = {8},
  number = {6},
  pages = {158-164},
  doi = {10.11648/j.epes.20190806.13},
  url = {https://doi.org/10.11648/j.epes.20190806.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.epes.20190806.13},
  abstract = {The problem of power generating equipment reliability and safety of thermal (TPP), hydro (HPP) and nuclear (NPP) power plants at each its life cycle stage is set and the solution approach is proposed. The blockchain distributed data storage system to unite different members of the energy system is described. It is shown that the suggested technology allows decentralized data storage reliability increase due to the data exists till its last participant leaves and safety is ensured by the electric market participant consensus algorithm. The algorithm for the decentralized blockchain system is developed. The new technique for reliability design calculation based on using both constant and time-varying failure rate is introduced. It is suggested to use control action method expressed as the design, technological and operational parameters from the normative documents. The generalized model of reliability design calculation representing product of three components of failure free operation probability is developed. It is shown that developing new algorithms of statistical data obtaining and designing full repair processes allow planning equipment repair, obtaining and analyzing the corresponding reliability indeces when the equipment is in operation and then choose the most fitting repair time and amount optimization, operation mode selection and power plant long term equipment time in operation forecasting solutions. The technique for the power equipment condition forecasting by archival data stored in the distributed system, the data can be used to predict equipment failures and decide whether it should be repaired. It is shown that the desired prediction accuracy can be achived by using neural network due to its feature to reveal complex relations between input and output values.},
 year = {2019}
}

Copy | Download

TY  - JOUR
T1  - The Techniques for Achieving High Power Equipment Reliability with Distributed Informational System
AU  - Arakelian Edik Koyrunovich
AU  - Sultanov Makhsud Mansurovich
AU  - Evseev Kirill Viktorovich
Y1  - 2019/12/24
PY  - 2019
N1  - https://doi.org/10.11648/j.epes.20190806.13
DO  - 10.11648/j.epes.20190806.13
T2  - American Journal of Electrical Power and Energy Systems
JF  - American Journal of Electrical Power and Energy Systems
JO  - American Journal of Electrical Power and Energy Systems
SP  - 158
EP  - 164
PB  - Science Publishing Group
SN  - 2326-9200
UR  - https://doi.org/10.11648/j.epes.20190806.13
AB  - The problem of power generating equipment reliability and safety of thermal (TPP), hydro (HPP) and nuclear (NPP) power plants at each its life cycle stage is set and the solution approach is proposed. The blockchain distributed data storage system to unite different members of the energy system is described. It is shown that the suggested technology allows decentralized data storage reliability increase due to the data exists till its last participant leaves and safety is ensured by the electric market participant consensus algorithm. The algorithm for the decentralized blockchain system is developed. The new technique for reliability design calculation based on using both constant and time-varying failure rate is introduced. It is suggested to use control action method expressed as the design, technological and operational parameters from the normative documents. The generalized model of reliability design calculation representing product of three components of failure free operation probability is developed. It is shown that developing new algorithms of statistical data obtaining and designing full repair processes allow planning equipment repair, obtaining and analyzing the corresponding reliability indeces when the equipment is in operation and then choose the most fitting repair time and amount optimization, operation mode selection and power plant long term equipment time in operation forecasting solutions. The technique for the power equipment condition forecasting by archival data stored in the distributed system, the data can be used to predict equipment failures and decide whether it should be repaired. It is shown that the desired prediction accuracy can be achived by using neural network due to its feature to reveal complex relations between input and output values.
VL  - 8
IS  - 6
ER  -

Copy | Download

Author Information

Arakelian Edik Koyrunovich

Department of Automation and Process Operation, National Research University “Moscow Power Engineering Institute”, Moscow, Russia
Sultanov Makhsud Mansurovich

Department of Heat Power Engineering, National Research University ?Moscow Power Engineering Institute?, Volzhsky, Russia
Evseev Kirill Viktorovich

Department of Heat Power Engineering, National Research University ?Moscow Power Engineering Institute?, Volzhsky, Russia

Download PDF

Sections

Plain Text BibTeX RIS

APA Style

Arakelian Edik Koyrunovich, Sultanov Makhsud Mansurovich, Evseev Kirill Viktorovich. (2019). The Techniques for Achieving High Power Equipment Reliability with Distributed Informational System. American Journal of Electrical Power and Energy Systems, 8(6), 158-164. https://doi.org/10.11648/j.epes.20190806.13

Copy | Download

ACS Style

Arakelian Edik Koyrunovich; Sultanov Makhsud Mansurovich; Evseev Kirill Viktorovich. The Techniques for Achieving High Power Equipment Reliability with Distributed Informational System. Am. J. Electr. Power Energy Syst. 2019, 8(6), 158-164. doi: 10.11648/j.epes.20190806.13

Copy | Download

AMA Style

Arakelian Edik Koyrunovich, Sultanov Makhsud Mansurovich, Evseev Kirill Viktorovich. The Techniques for Achieving High Power Equipment Reliability with Distributed Informational System. Am J Electr Power Energy Syst. 2019;8(6):158-164. doi: 10.11648/j.epes.20190806.13

Copy | Download

@article{10.11648/j.epes.20190806.13,
  author = {Arakelian Edik Koyrunovich and Sultanov Makhsud Mansurovich and Evseev Kirill Viktorovich},
  title = {The Techniques for Achieving High Power Equipment Reliability with Distributed Informational System},
  journal = {American Journal of Electrical Power and Energy Systems},
  volume = {8},
  number = {6},
  pages = {158-164},
  doi = {10.11648/j.epes.20190806.13},
  url = {https://doi.org/10.11648/j.epes.20190806.13},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.epes.20190806.13},
  abstract = {The problem of power generating equipment reliability and safety of thermal (TPP), hydro (HPP) and nuclear (NPP) power plants at each its life cycle stage is set and the solution approach is proposed. The blockchain distributed data storage system to unite different members of the energy system is described. It is shown that the suggested technology allows decentralized data storage reliability increase due to the data exists till its last participant leaves and safety is ensured by the electric market participant consensus algorithm. The algorithm for the decentralized blockchain system is developed. The new technique for reliability design calculation based on using both constant and time-varying failure rate is introduced. It is suggested to use control action method expressed as the design, technological and operational parameters from the normative documents. The generalized model of reliability design calculation representing product of three components of failure free operation probability is developed. It is shown that developing new algorithms of statistical data obtaining and designing full repair processes allow planning equipment repair, obtaining and analyzing the corresponding reliability indeces when the equipment is in operation and then choose the most fitting repair time and amount optimization, operation mode selection and power plant long term equipment time in operation forecasting solutions. The technique for the power equipment condition forecasting by archival data stored in the distributed system, the data can be used to predict equipment failures and decide whether it should be repaired. It is shown that the desired prediction accuracy can be achived by using neural network due to its feature to reveal complex relations between input and output values.},
 year = {2019}
}

Copy | Download

TY  - JOUR
T1  - The Techniques for Achieving High Power Equipment Reliability with Distributed Informational System
AU  - Arakelian Edik Koyrunovich
AU  - Sultanov Makhsud Mansurovich
AU  - Evseev Kirill Viktorovich
Y1  - 2019/12/24
PY  - 2019
N1  - https://doi.org/10.11648/j.epes.20190806.13
DO  - 10.11648/j.epes.20190806.13
T2  - American Journal of Electrical Power and Energy Systems
JF  - American Journal of Electrical Power and Energy Systems
JO  - American Journal of Electrical Power and Energy Systems
SP  - 158
EP  - 164
PB  - Science Publishing Group
SN  - 2326-9200
UR  - https://doi.org/10.11648/j.epes.20190806.13
AB  - The problem of power generating equipment reliability and safety of thermal (TPP), hydro (HPP) and nuclear (NPP) power plants at each its life cycle stage is set and the solution approach is proposed. The blockchain distributed data storage system to unite different members of the energy system is described. It is shown that the suggested technology allows decentralized data storage reliability increase due to the data exists till its last participant leaves and safety is ensured by the electric market participant consensus algorithm. The algorithm for the decentralized blockchain system is developed. The new technique for reliability design calculation based on using both constant and time-varying failure rate is introduced. It is suggested to use control action method expressed as the design, technological and operational parameters from the normative documents. The generalized model of reliability design calculation representing product of three components of failure free operation probability is developed. It is shown that developing new algorithms of statistical data obtaining and designing full repair processes allow planning equipment repair, obtaining and analyzing the corresponding reliability indeces when the equipment is in operation and then choose the most fitting repair time and amount optimization, operation mode selection and power plant long term equipment time in operation forecasting solutions. The technique for the power equipment condition forecasting by archival data stored in the distributed system, the data can be used to predict equipment failures and decide whether it should be repaired. It is shown that the desired prediction accuracy can be achived by using neural network due to its feature to reveal complex relations between input and output values.
VL  - 8
IS  - 6
ER  -

Copy | Download