Modeling reliability of power systems substations by using stochastic automata networks

Šnipas, Mindaugas; Radziukynas, Virginijus; Valakevičius, Eimutis

doi:10.1016/j.ress.2016.08.006

Cited by 13 publications

(3 citation statements)

References 41 publications

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“…A study on the modeling of reliability in power system network using Stochastic Automata Network (SAN) in conjunction with Markov chain was carried out by Snipas et al, [42]. However, the authors were skeptical about the results obtained from the work owing to the fact that other techniques might yield better result due to the inability of the SAN in specifying functional deficiencies within the automata.…”

Section: Review Of Literaturementioning

confidence: 99%

Reliability Assessment of Power System Network: A Detailed Review

Airoboman

2022

IJET

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Due to an increase in technological advancement and population, there is also a corresponding increase in the demand of electrical energy within Nigeria. Utility is presently characterized by suppressed demand due to the poor reliability inherent in the system. Utility, therefore, considers load shedding as a way out to ensure that the available power from each of the feeders from a network gets to its respective customers at any giving time they choose for the customer while the time the customers choose for themselves remains immaterial. However, in recent times, increased in downtime has been observed as a result of various faults and failures noticeable on the network and this has led to outrage by the customers who only considered protests as the only way out in expressing their dis-satisfaction with the system. This anomaly, therefore, arouses the interest for this study to carry out a detailed approach to carry out a review on the state of the reliability of the power system network in Nigeria and juxtaposing it with what is tenable outside the country with a view to determine the present state of the network and how it has fared with respect to time.

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Section: Review Of Literaturementioning

confidence: 99%

Reliability Assessment of Power System Network: A Detailed Review

Airoboman

2022

IJET

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“…In the paper [17], reliability assessment of active distribution networks including islanding dynamics was presented, where the reliability analysis was performed by Non-Sequential Monte Carlo modelling, whereas the islanding process is assessed by a transient stability simulation with complete models of synchronous machine and its speed and voltage regulators. In [18], in order to model failure and reliability evaluation of power system substations, Stochastic Automata Networks (SANs) formalism is applied; authors in [19,20] introduce new prediction models based on hybrid forecast engine for power market forecasting in power systems; and finally, the paper [21] proposed an integrated approach relies on cleverly cooperation of time rate-based Demand Response Program (DRP) and heterogeneous Distributed Energy Sources (DESs) deployment with goal to reliability-oriented planning of multiple Micro-Grids (MGs).…”

Section: Literature Reviewmentioning

confidence: 99%

An analytical methodology for reliability assessment and failure analysis in distributed power system

2018

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Minimizing total system failure could improve the reliability of power network in order to optimize power system operation. In this way, reliability analysis has been proposed by researchers to tackle the mentioned problem. This paper investigates an analytical methodology for reliability assessment and failure analysis techniques in an actual distributed power system. We use reliability analysis to evaluate system design and gathering outage data in this paper. Modelling and simulation of our assumed system are implemented in electrical transient analyzer program (ETAP) software. The results of theoretical/practical reliability and failure analysis including mean time between failure, mean time to repair, availability, system average interruption frequency index, system average interruption duration index, consumer average interruption duration index, average service availability index, average service unavailability index, expected energy not supplied, expected interruption costs, and interrupted energy assessment rate are compared with the summary of reliability assessment simulation. The capability and effectiveness of reliability evaluation are demonstrated according to the simulation results through ETAP which obtained by applying it to this power system.

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“…Theoretical analysis and experimental results show that the improved method improves the reliability and timeliness of the evaluation results. Mindaugas et al (2016) [16] proposed stochastic automata networks to allow reducing the size of state space of Markov chain model and simplifying system specification. Modelling results showed that the implementation of Markov chain model by using SAN method is a relatively easy task.…”

Section: Markov Chain Modelmentioning

confidence: 99%

A Review of Risk Assessment Methods for Power System

Zhao

Mao

et al. 2017

MATEC Web Conf.

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Abstract.In view of the current social background of power system becoming more and more complicated, and the current research situation of related fields, this paper discusses the common methods of power system risk assessment, including the method of hierarchy analysis, Markov chain model, Monte Carlo method, fuzzy comprehensive evaluation and related research progress.The advantages and disadvantages of the four methods are enumerated respectively. It is considered that the power system should be evaluated synthetically in the practical application and the effective risk assessment method should be adopted rationally.

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Modeling reliability of power systems substations by using stochastic automata networks

Cited by 13 publications

References 41 publications

Reliability Assessment of Power System Network: A Detailed Review

Reliability Assessment of Power System Network: A Detailed Review

An analytical methodology for reliability assessment and failure analysis in distributed power system

A Review of Risk Assessment Methods for Power System

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