scholarly journals Improving Power System Risk Evaluation Method Using Monte Carlo Simulation and Gaussian Mixture Method

2009 ◽  
Vol 9 (2) ◽  
pp. 38-44 ◽  
Author(s):  
O. A. MOUSAVI ◽  
M. S. FARASHBASHI-ASTANEH ◽  
G. B. GHAREHPETIAN
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Power System ◽  
Risk Evaluation ◽  
Evaluation Method ◽  
Gaussian Mixture ◽  
System Risk

Power System Risk Assessment Using a Hybrid Method of Fuzzy Set and Monte Carlo Simulation

2008 ◽  
Vol 23 (2) ◽  
pp. 336-343 ◽  
Author(s):  
Wenyuan Li ◽  
Jiaqi Zhou ◽  
Kaigui Xie ◽  
Xiaofu Xiong
Keyword(s):  
Risk Assessment ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Power System ◽  
Fuzzy Set ◽  
Hybrid Method ◽  
System Risk

Mircogrid Voltage Risk Evaluation Using Distributed Parallel Monte-Carlo Simulation

2020 ◽  
Author(s):  
Jiangdong Liu ◽  
Zhijian Wu ◽  
Zhenyong Huang ◽  
Shi Pu ◽  
Hong Chen ◽  
...  
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Risk Evaluation

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.

scholarly journals Power system stochastic transient stability assessment based on Monte Carlo simulation

2019 ◽  
Vol 2019 (16) ◽  
pp. 1051-1055
Author(s):  
Jiayu Liu ◽  
Jun Liu ◽  
Jie Zhang ◽  
Wanliang Fang ◽  
Longchu Qu
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Power System ◽  
Transient Stability ◽  
Stability Assessment
Sign in / Sign up

Export Citation Format

Share Document