scholarly journals Reliability Analysis of a Home-scale Microgrid Based on a Threshold System

2021 ◽  
pp. 14-26
Author(s):  
Taufal Hidayat ◽  
Ali Muhammad Rushdi
Keyword(s):  
System Reliability ◽  
Recursive Algorithm ◽  
Computing System ◽  
System Model ◽  
Threshold Function ◽  
Scale Model ◽  
Switching Function ◽  
Power Method ◽  
Banzhaf Index ◽  
Success Function

The reliability of a microgrid power system is an important aspect to analyze so as to ascertain that the system can provide electricity reliably over a specified period of time. This paper analyzes a home-scale model of a microgrid system by using the threshold system model (inadvertently labeled as the weighted k-out-of-n:G system model), which is a system whose success is treated as a threshold switching function. To analyze the reliability of the system, we first proved that its success is a coherent threshold function, and then identified possible (non-unique) values for its weights and threshold.  Two methods are employed for this. The first method is called the unity-gap method and the second is called the fair-power method. In the unity-gap method, we utilize certain dominations and symmetries to reduce the number of pertinent inequalities (turned into equations) to be solved. In the fair-power method, the Banzhaf index is calculated to express the weight of each component as its relative power or importance. Finally, a recursive algorithm for computing system reliability is presented. The threshold success function is verified to be shellable, and the non-uniqueness of the set of weights and thresholds is demonstrated to be of no detrimental consequence, as different correct sets of weights and threshold produce equivalent expressions of system reliability.

Recursive Technique For Computing System Reliability

1987 ◽  
Vol R-36 (1) ◽  
pp. 38-44 ◽  
Author(s):  
Suresh Rai ◽  
Arun Kumar
Keyword(s):  
System Reliability ◽  
Computing System

Reliability Interval Estimation for a System Model with Element Duplication in Different Subsystems

2020 ◽  
pp. 4-13
Author(s):  
I.V. Pavlov ◽  
L.K. Gordeev
Keyword(s):  
System Reliability ◽  
Sliding Mode ◽  
Interval Estimation ◽  
Computational Procedure ◽  
Reliability Function ◽  
System Model ◽  
System Failure ◽  
Reliability Parameters ◽  
Lower Confidence ◽  
Analytical Expressions

The problem was considered of estimating reliability for a complex system model with element duplication of various subsystems and ensuring possibility of additional redundancy in a more flexible dynamic (or 'sliding') mode in each of the subsystems, which significantly increases reliability of the system in general. For the system considered, general model and analytical expressions were obtained in regard to the main reliability indicators, i.e., probability of the system failure-free operation (reliability function) for a given time and mean time of the system failure-free operation. On the basis of these analytical expressions, the lower confidence limit for the system reliability function was found in a situation, where the element reliability parameters were unknown, and only results of testing the system elements for reliability were provided. It was shown that the system resource function was convex in the reliability parameters vector of the system separate elements various types. Based on this, the lower confidence boundary construction for the system reliability function was reduced to the problem of finding the convex function extremum on a confidence set in the system element parameter space. In this case, labor consumption of the corresponding computational procedure increases linearly with an increase in the problem dimension. Numerical examples of calculating the lower confidence boundary for the system reliability function were provided

Estimated Guaranteed Life for a System Model with Redundancy of Heterogeneous Elements

2019 ◽  
pp. 4-17
Author(s):  
I.V. Pavlov ◽  
S.V. Razgulyaev
Keyword(s):  
System Reliability ◽  
High Reliability ◽  
Analytical Calculation ◽  
Reliability Function ◽  
System Model ◽  
Confidence Estimation ◽  
Reliability Indicators ◽  
Lower Confidence ◽  
Asymptotic Expressions ◽  
System Life

The paper focuses on the problem of confidence estimation of reliability indicators for a system model with loaded redundancy of elements of various sub-systems. The lower confidence limits are constructed for the system reliability function, as well as for the indicator associated with it, the indicator having a given guaranteed level of the system uptime, i.e., its gamma-percentile life. Within the research, we obtained approximate asymptotic --- for the case of high reliability --- expressions for confidence estimates of these basic indicators of system reliability. Rather simple approximate analytical calculation formulas based on these asymptotic expressions are given for the lower confidence boundary of the system reliability function and a similar confidence boundary for the guaranteed system life.

scholarly journals Transient simulations of the present and the last interglacial climate using the Community Climate System Model version 3: effects of orbital acceleration

2016 ◽  
Vol 9 (11) ◽  
pp. 3859-3873 ◽  
Author(s):  
Vidya Varma ◽  
Matthias Prange ◽  
Michael Schulz
Keyword(s):  
Climate System ◽  
System Model ◽  
Scale Model ◽  
Last Interglacial ◽  
Community Climate System Model ◽  
Climate System Model ◽  
Model Version ◽  
Surface Climate ◽  
Transient Simulations ◽  
Community Climate

Abstract. Numerical simulations provide a considerable aid in studying past climates. Out of the various approaches taken in designing numerical climate experiments, transient simulations have been found to be the most optimal when it comes to comparison with proxy data. However, multi-millennial or longer simulations using fully coupled general circulation models are computationally very expensive such that acceleration techniques are frequently applied. In this study, we compare the results from transient simulations of the present and the last interglacial with and without acceleration of the orbital forcing, using the comprehensive coupled climate model CCSM3 (Community Climate System Model version 3). Our study shows that in low-latitude regions, the simulation of long-term variations in interglacial surface climate is not significantly affected by the use of the acceleration technique (with an acceleration factor of 10) and hence, large-scale model–data comparison of surface variables is not hampered. However, in high-latitude regions where the surface climate has a direct connection to the deep ocean, e.g. in the Southern Ocean or the Nordic Seas, acceleration-induced biases in sea-surface temperature evolution may occur with potential influence on the dynamics of the overlying atmosphere.

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