Estimation of the derivatives of generation system reliability indices in Monte Carlo simulation

1993 ◽  
Vol 8 (4) ◽  
pp. 1448-1454 ◽  
Author(s):  
M. Masood Ahmad ◽  
A. Debs ◽  
Y. Wardi
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
System Reliability ◽  
Generation System ◽  
Reliability Indices ◽  
Derivatives Of

Reliability Assessment of Power System Using Importance Sampling Technique Based on Layer Optimization Simulation

2011 ◽  
Vol 88-89 ◽  
pp. 554-558 ◽  
Author(s):  
Bin Wang
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Power System ◽  
Importance Sampling ◽  
System Reliability ◽  
Sampling Method ◽  
Sampling Technique ◽  
Test System ◽  
Importance Sampling Method ◽  
Importance Sampling Technique

An improved importance sampling method with layer simulation optimization is presented in this paper. Through the solution sequence of the components’ optimum biased factors according to their importance degree to system reliability, the presented technique can further accelerate the convergence speed of the Monte-Carlo simulation. The idea is that the multivariate distribution’ optimization of components in power system is transferred to many steps’ optimization based on importance sampling method with different optimum biased factors. The practice is that the components are layered according to their importance degree to the system reliability before the Monte-Carlo simulation, the more forward, the more important, and the optimum biased factors of components in the latest layer is searched while the importance sampling is carried out until the demanded accuracy is reached. The validity of the presented is verified using the IEEE-RTS79 test system.

Evaluation of generation system reliability indices by fast transform techniques

1995 ◽  
Vol 17 (4) ◽  
pp. 281-287
Author(s):  
S.R. Lakshmi ◽  
S.C. Tripathy ◽  
K.S.P. Rao ◽  
R. Balasubramianian
Keyword(s):  
System Reliability ◽  
Generation System ◽  
Reliability Indices ◽  
Fast Transform

scholarly journals Effect of Grid Instability on Power Generation System's Reliability

2020 ◽  
pp. 27-37
Author(s):  
Joseph Benedict Bassey ◽  
Isaac F. Odesola
Keyword(s):  
Power Generation ◽  
Power Plant ◽  
Failure Rate ◽  
System Reliability ◽  
Power Distribution ◽  
Power Plants ◽  
Time To Failure ◽  
Generation System ◽  
Reliability Indices ◽  
Mean Time

Aims: Reliability assessment of power generation system may be performed with the concept of system adequacy, security or both. Grid being a major component in the power distribution chain is seen to have some influence on the state of the generation system reliability because of the perturbation that may arise from it. In this study, the generation system reliability is evaluated using both the system adequacy and security concept. Study Design: To capture the system security problems attributed to grid disturbance, the generation system is structured into two component systems (1 - generation component and 2 - transmission component) with a series arrangement. Methodology: The reliability indices such as, mean time to failure, mean time to repair, failure rate and repair rate are assessed on component bases and with respect to the entire generation system. Results: The effect of failure rate of the transmission component on the entire generation system failure rate was evaluated as 66.25%, 55.55%, 33.33%, 55.00% and 35.72% in year 2013, 2014, 2017 2018 and 2019 respectively for FIPL Power Plant and 52.94%, 82.35%, 61.38% and 100% effect was evaluated in the year 2016, 2017, 2018 and 2019 respectively for GT5 of Omoku Power Plant. Conclusion: These results showed that there is a significant influence of grid disturbances on the reliability state of the two gas turbine power plants in Nigeria. Measures on possible reliability state improvement of the power generation systems were suggested to include training and retraining of technical personnel on the management of major equipment in the generation and transmission stations. 

System Reliability Estimation for a Manufacturing Network with Joint Buffers

2018 ◽  
Vol 25 (04) ◽  
pp. 1850020 ◽  
Author(s):  
Ping-Chen Chang ◽  
Chia-Chun Wu ◽  
Chin-Tan Lee
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
System Reliability ◽  
Manufacturing System ◽  
Reliability Estimation ◽  
Experimental Result ◽  
Production Lines ◽  
Work In Process ◽  
Process Output ◽  
Manufacturing Network

This paper develops a Monte Carlo Simulation (MCS) approach to estimate the performance of a multistate manufacturing network (MMN) with joint buffers. In the MMN, products are allowed to be produced by two production lines with the same function to satisfy demand. A performance index, system reliability, is applied to estimate the probability that all workstations provide sufficient capacity to satisfy a specified demand and buffers possess adequate storage. The joint buffers with finite storage are considered in the MMN. That is, extra work-in-process output from different production lines can be stored in the same buffer. An MCS algorithm is proposed to generate the capacity state and to check the storage usage of buffers to evaluate whether the demand can be satisfied or not. System reliability of the MMN is estimated through this MCS algorithm. Besides, performability for demand pairs assigned to production lines can be obtained. A practical example of touch panel manufacturing system is used to demonstrate the applicability of the MCS approach. Experimental result shows that system reliability is overestimated when buffer storage is assumed to be infinite. Moreover, joint buffer for an MMN is more reliable than buffers are installed separately in different production lines.

Sign in / Sign up

Export Citation Format

Share Document