scholarly journals Vulnerability in a Stochastic Dynamic Model

2003 ◽  
Author(s):  
Chris Elbers ◽  
Jan Willem Gunning
Keyword(s):  
Dynamic Model ◽  
Stochastic Dynamic

scholarly journals Linearization threshold condition and stability analysis of a stochastic dynamic model of one-machine infinite-bus (OMIB) power systems

2021 ◽  
Vol 6 (1) ◽  
Author(s):  
Lijuan Li ◽  
Yongdong Chen ◽  
Bin Zhou ◽  
Hongliang Liu ◽  
Yongfei Liu
Keyword(s):  
Power Systems ◽  
Power System ◽  
Dynamic Model ◽  
Threshold Model ◽  
Security Evaluation ◽  
Stochastic Dynamic ◽  
Threshold Condition ◽  
Stochastic Excitation ◽  
Predictor Corrector ◽  
One Machine

AbstractWith the increase in the proportion of multiple renewable energy sources, power electronics equipment and new loads, power systems are gradually evolving towards the integration of multi-energy, multi-network and multi-subject affected by more stochastic excitation with greater intensity. There is a problem of establishing an effective stochastic dynamic model and algorithm under different stochastic excitation intensities. A Milstein-Euler predictor-corrector method for a nonlinear and linearized stochastic dynamic model of a power system is constructed to numerically discretize the models. The optimal threshold model of stochastic excitation intensity for linearizing the nonlinear stochastic dynamic model is proposed to obtain the corresponding linearization threshold condition. The simulation results of one-machine infinite-bus (OMIB) systems show the correctness and rationality of the predictor-corrector method and the linearization threshold condition for the power system stochastic dynamic model. This study provides a reference for stochastic modelling and efficient simulation of power systems with multiple stochastic excitations and has important application value for stability judgment and security evaluation.

scholarly journals Stochastic Dynamic Model of Sulfate Corrosion Reactions in Concrete Materials considering the Effects of Colored Gaussian Noises

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-18 ◽  
Author(s):  
Tao Li ◽  
Bin Zhang
Keyword(s):  
Random Process ◽  
Dynamic Model ◽  
Mass Conservation ◽  
Corrosion Products ◽  
Chemical System ◽  
Stochastic Dynamic ◽  
Initial Reactant ◽  
Corrosion Reaction ◽  
Concrete Materials ◽  
Concentration Evolution

The corrosion reactions in concrete materials subjected to external environment attack can lead to the deterioration of concrete. However, the effects of internal fluctuations on the corrosion reaction process have not been reported in current studies on damage of concrete materials. To comprehensively describe the effects of internal fluctuations, the stochastic dynamic model of corrosion reactions in concrete materials subjected to sulfate attack is established based on the law of mass conservation and random process theory, in which internal fluctuations and the parameters of the chemical system are, respectively, regarded as colored Gaussian noises and a series of random variables. An experiment of sulfate corrosion reactions in concrete material is carried out to verify the effectiveness of the proposed method. Furthermore, the effects of variations of the initial reactant concentrations on the concentration evolution processes of the corrosion products are investigated. Results show that the stochastic dynamical responses of the corrosion reactions in concrete can be comprehensively investigated by the proposed stochastic mathematical model; the probabilistic information of the corrosion products can also be obtained conveniently. The concentration evolution process of sulfate corrosion products is a random process. The experimental data are only some samples of the random process. Concentrations of the corrosion products in concrete materials significantly fluctuate with the variations of the initial reactant concentrations.

scholarly journals Evaluation of the Capacity of Risk Carriers by Means of Stochastic-Dynamic Programming

1981 ◽  
Vol 12 (1) ◽  
pp. 1-21 ◽  
Author(s):  
T. Pentikäinen ◽  
J. Rantala
Keyword(s):  
Dynamic Programming ◽  
Dynamic Model ◽  
Working Group ◽  
Stochastic Dynamic Programming ◽  
Numerical Data ◽  
Stochastic Dynamic ◽  
Political Interference ◽  
Near Future ◽  
Special Working ◽  
Special Working Group

The Ministry of Social Affairs and Health, being the Supervising Office of Insurance in Finland, has established a special working group to investigate the problems involved with the solvency of insurers. A report will be compiled in a near future. The capacity of risk carriers is one of the problems dealt with, and it will be preliminarily reviewed in this paper.The problem was treated by the working group parallelly by means of1. an empirical approach observing actual fluctuations in underwriting gains of insurers, and2. a theoretical approach, constructing a stochastic-dynamic model and studying its behaviour, especially its sensitivity to numerous background factors.First the methods of investigation are described and their application is then demonstrated using some numerical data. Because a comprehensive report will be published by the working group separately, only the main schedule is given. For the same reason the consideration is limited here to stochastic risks, omitting the fact that the solvency of an insurer is also jeopardized by numerous “non-stochastic” risks such as failure in investments, political interference of the authorities, mismanagement of the company, or misappropriation of its property.

scholarly journals A stochastic dynamic model of a dairy farm to evaluate the technical and economic performance under different scenarios

2018 ◽  
Vol 101 (8) ◽  
pp. 7517-7530 ◽  
Author(s):  
S. Calsamiglia ◽  
S. Astiz ◽  
J. Baucells ◽  
L. Castillejos
Keyword(s):  
Dynamic Model ◽  
Economic Performance ◽  
Dairy Farm ◽  
Stochastic Dynamic

Stochastic Dynamic Model of the Vibration Signals of Rolling Bearing and their Analysis

2014 ◽  
Vol 49 (4) ◽  
pp. 549-559
Author(s):  
I. I. Mats’ko ◽  
I. M. Yavors’kyi ◽  
R. M. Yuzefovych ◽  
Z. Zakrzewski
Keyword(s):  
Dynamic Model ◽  
Rolling Bearing ◽  
Stochastic Dynamic ◽  
Vibration Signals
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