Stochastic Diffusion Process-based Multi-Level Monte Carlo for Predictive Reliability Assessment of Distribution System

Reliability assessment of electrical distribution systems is an important criterion to determine system performance in terms of interruptions. Probabilistic assessment methods are usually used in reliability analysis to deal with uncertainties. These techniques require a longer execution time in ord...

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Autores principales:	Manohar Potli, Chandrasekhar Reddy Atla
Formato:	article
Lenguaje:	EN
Publicado:	Universidade do Porto 2021
Materias:	multi level monte carlo power distribution system reliability reliability indices stochastic diffusion process euler maruyama discretization Engineering (General). Civil engineering (General) TA1-2040 Technology (General) T1-995
Acceso en línea:	https://doaj.org/article/cc29d6dbf779439fae339b82e425168a
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spelling	oai:doaj.org-article:cc29d6dbf779439fae339b82e425168a2021-11-26T12:34:56ZStochastic Diffusion Process-based Multi-Level Monte Carlo for Predictive Reliability Assessment of Distribution System2183-649310.24840/2183-6493_007.004_0007https://doaj.org/article/cc29d6dbf779439fae339b82e425168a2021-11-01T00:00:00Zhttps://journalengineering.fe.up.pt/index.php/upjeng/article/view/961https://doaj.org/toc/2183-6493Reliability assessment of electrical distribution systems is an important criterion to determine system performance in terms of interruptions. Probabilistic assessment methods are usually used in reliability analysis to deal with uncertainties. These techniques require a longer execution time in order to account for uncertainty. Multi-Level Monte Carlo (MLMC) is an advanced Monte Carlo Simulation (MCS) approach to improve accuracy and reduce the execution time. This paper provides a systematic approach to model the static and dynamic uncertainties of Time to Failure (TTF) and Time to Repair (TTR) of power distribution components using a Stochastic Diffusion Process. Further, the Stochastic Diffusion Process is integrated into MLMC to estimate the impacts of uncertainties on reliability indices. The Euler Maruyama path discretization applied to evaluate the solution of the Stochastic Diffusion Process. The proposed Stochastic Diffusion Process-based MLMC method is integrated into a systematic failure identification technique to evaluate the distribution system reliability. The proposed method is validated with analytical and Sequential MCS methods for IEEE Roy Billinton Test Systems. Finally, the numerical results show the accuracy and fast convergence rates to handle uncertainties compared to Sequential MCS method.Manohar PotliChandrasekhar Reddy AtlaUniversidade do Portoarticlemulti level monte carlopower distribution system reliabilityreliability indicesstochastic diffusion processeuler maruyama discretizationEngineering (General). Civil engineering (General)TA1-2040Technology (General)T1-995ENU.Porto Journal of Engineering, Vol 7, Iss 4, Pp 87-102 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	multi level monte carlo power distribution system reliability reliability indices stochastic diffusion process euler maruyama discretization Engineering (General). Civil engineering (General) TA1-2040 Technology (General) T1-995
spellingShingle	multi level monte carlo power distribution system reliability reliability indices stochastic diffusion process euler maruyama discretization Engineering (General). Civil engineering (General) TA1-2040 Technology (General) T1-995 Manohar Potli Chandrasekhar Reddy Atla Stochastic Diffusion Process-based Multi-Level Monte Carlo for Predictive Reliability Assessment of Distribution System
description	Reliability assessment of electrical distribution systems is an important criterion to determine system performance in terms of interruptions. Probabilistic assessment methods are usually used in reliability analysis to deal with uncertainties. These techniques require a longer execution time in order to account for uncertainty. Multi-Level Monte Carlo (MLMC) is an advanced Monte Carlo Simulation (MCS) approach to improve accuracy and reduce the execution time. This paper provides a systematic approach to model the static and dynamic uncertainties of Time to Failure (TTF) and Time to Repair (TTR) of power distribution components using a Stochastic Diffusion Process. Further, the Stochastic Diffusion Process is integrated into MLMC to estimate the impacts of uncertainties on reliability indices. The Euler Maruyama path discretization applied to evaluate the solution of the Stochastic Diffusion Process. The proposed Stochastic Diffusion Process-based MLMC method is integrated into a systematic failure identification technique to evaluate the distribution system reliability. The proposed method is validated with analytical and Sequential MCS methods for IEEE Roy Billinton Test Systems. Finally, the numerical results show the accuracy and fast convergence rates to handle uncertainties compared to Sequential MCS method.
format	article
author	Manohar Potli Chandrasekhar Reddy Atla
author_facet	Manohar Potli Chandrasekhar Reddy Atla
author_sort	Manohar Potli
title	Stochastic Diffusion Process-based Multi-Level Monte Carlo for Predictive Reliability Assessment of Distribution System
title_short	Stochastic Diffusion Process-based Multi-Level Monte Carlo for Predictive Reliability Assessment of Distribution System
title_full	Stochastic Diffusion Process-based Multi-Level Monte Carlo for Predictive Reliability Assessment of Distribution System
title_fullStr	Stochastic Diffusion Process-based Multi-Level Monte Carlo for Predictive Reliability Assessment of Distribution System
title_full_unstemmed	Stochastic Diffusion Process-based Multi-Level Monte Carlo for Predictive Reliability Assessment of Distribution System
title_sort	stochastic diffusion process-based multi-level monte carlo for predictive reliability assessment of distribution system
publisher	Universidade do Porto
publishDate	2021
url	https://doaj.org/article/cc29d6dbf779439fae339b82e425168a
work_keys_str_mv	AT manoharpotli stochasticdiffusionprocessbasedmultilevelmontecarloforpredictivereliabilityassessmentofdistributionsystem AT chandrasekharreddyatla stochasticdiffusionprocessbasedmultilevelmontecarloforpredictivereliabilityassessmentofdistributionsystem
_version_	1718409378092023808

Stochastic Diffusion Process-based Multi-Level Monte Carlo for Predictive Reliability Assessment of Distribution System

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