Advanced reliability analysis for distribution network

Pylvänäinen, Jouni; Järvinen, Jussi; Verho, Pekka

doi:10.1109/drpt.2004.1338016

Cited by 6 publications

(4 citation statements)

References 1 publication

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“…An exclusive measurement of failure rates for distributed software has been done in (Chillarege, Biyani, & Rosenthal, 1995) but it does not take into account the failure of the computing and network resources. A reliability analysis confined only for the distribution network is also reported developing a failure rate model based on failure statistics of the network (Pylvanainen, Jarvinen and Verho, 2004;Chen, 2004). The work provides guidance to consider the environmental and component based aspects in network management for controlling the planning process and can be used for optimizing the total life cycle costs of the network components.…”

Section: Related Modelsmentioning

confidence: 99%

Reliability Based Scheduling Model (RSM) for Computational Grids

Raza

Vidyarthi

2011

International Journal of Distributed Systems and Technologies

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Computational Grid attributed with distributed load sharing has evolved as a platform to large scale problem solving. Grid is a collection of heterogeneous resources, offering services of varying natures, in which jobs are submitted to any of the participating nodes. Scheduling these jobs in such a complex and dynamic environment has many challenges. Reliability analysis of the grid gains paramount importance because grid involves a large number of resources which may fail anytime, making it unreliable. These failures result in wastage of both computational power and money on the scarce grid resources. It is normally desired that the job should be scheduled in an environment that ensures maximum reliability to the job execution. This work presents a reliability based scheduling model for the jobs on the computational grid. The model considers the failure rate of both the software and hardware grid constituents like application demanding execution, nodes executing the job, and the network links supporting data exchange between the nodes. Job allocation using the proposed scheme becomes trusted as it schedules the job based on a priori reliability computation.

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Section: Related Modelsmentioning

confidence: 99%

Reliability Based Scheduling Model (RSM) for Computational Grids

Raza

Vidyarthi

2011

International Journal of Distributed Systems and Technologies

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“…Most of the work reported in the literature lags in providing the most reliable execution environment to the job. The reliability estimations are done over the distributed computing system with one or the other parameters like reliability of the application, nodes or the distribution network [4,13,19]. Majority of the models do not consider the job scheduling based on the reliability aspect and calculate the reliability of the system after scheduling, making them unrealistic.…”

Section: Scheduling and Reliability For A Gridmentioning

confidence: 99%

Maximizing Reliability with Task Scheduling In a Computational Grid Using GA

Raza¹,

Vidyarthi²

2009

IJACT

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Grid is a service aggregation of both the information and the computational resources. Scheduling becomes a challenging job in such a complex and dynamic environment as both the application and the computational resources are heterogeneous. The problem is further complicated by the fact that these resources may fail at any point of time. Thus a scheduling strategy which schedules the job based on the failure possibility of the grid constituents becomes very important for the reliable execution of the job. Genetic algorithm has evolved as an effective search tool to solve the optimization problems consisting of large search space. It is a type of evolutionary search strategies applied on the search space and is based on the principle of "survival of the fittest". The model addresses the important issue of scheduling to provide the most reliable environment for the job execution by scheduling the job, ensuring maximum reliability to the job execution using Genetic Algorithm. The model presents a realistic picture of the grid by scheduling the job based on the reliability of the computational resources, networking resources and application (job) along with the pre-assigned workload on the nodes in order to provide the most reliable environment to the job. Simulation study proves the effectiveness of the model by comparing the performance of the model with another similar model.

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“…There are several factors that must be known and calculated before carrying out an analysis of the reliability of the electrical distribution system, among others: the frequency of failure and duration / duration of failure, which comes from the failure of distribution network equipment or failure at its load point [8].…”

Section: Introductionmentioning

confidence: 99%

Reliability Analysis of 20 kV Medium Voltage Air Line Distribution System at Semangga Switch Substation in Merauke Regency

Mangera¹

2022

etj

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The breakdown of electrical energy can be caused by the unwanted failures that occur in the electric power system, especially in the distribution system, and have an impact on service continuity which can be a permanent failure, temporary failure, three phase short circuit failure, double phase short circuit failure, and black out. To anticipate this, a study needs to be done to analyze and find out how well the distribution system reliability index. Determination of the analysis was done by the method of data retrieval related to the analysis variable. Besides, in determining the results of the analysis, calculations using System Average Interruption Frequency Index (SAIFI), Customer Interruption Frequency Index (CAIFI), System Average Interruption Duration Index (SAIDI) and Customer Average Interruption Duration Index (CAIDI) analyses were performed. Based on the reliability of the distribution network, the SAIFI and CAIDI maximum threshold value setup by PT. PLN (The National Electricity Company) at the Semangga substation each worth 3.00 failures/customer.year and 3.00 failures/customerr while SAIDI and CAIDI each worth value of 3.40 hours/customer.year and 3.40 hours/customer.failure. All feeders installed at Semangga switch substation in realization gives reliability indices smaller than the target that has been set., it is mean that 20 kV medium voltage air line distribution system at Semangga switch substation still reliable and the duration of the failure time for each feeder was an average of 3 minutes of each failure and the number of failures every month was an average of 15 times of each feeder.

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Advanced reliability analysis for distribution network

Cited by 6 publications

References 1 publication

Reliability Based Scheduling Model (RSM) for Computational Grids

Reliability Based Scheduling Model (RSM) for Computational Grids

Maximizing Reliability with Task Scheduling In a Computational Grid Using GA

Reliability Analysis of 20 kV Medium Voltage Air Line Distribution System at Semangga Switch Substation in Merauke Regency

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