交叉熵重要抽样法中多级别参数对电网可靠性评估的影响分析
首发时间:2021-03-25
摘要:交叉熵重要抽样法(CE-IS)通过参数寻优的迭代算法实现了对重要抽样概率密度函数(IS-PDF)的求解,显著提高了蒙特卡洛模拟的仿真效率,因而被广泛运用于电网可靠性评估中,但这种迭代算法的收敛标准通常是基于主观确定的多级别参数。为了研究这一主观参数对可靠性评估的影响,本文基于参数寻优的迭代算法,从理论上分析了多级别参数与IS-PDF参数寻优结果的关系。此外,为获取最佳的重要抽样仿真效率,本文还为CE-IS法中多级别参数的选择提供了选择依据。最后以IEEE-RTS79可靠性测试系统验证了本文理论的适用性与有效性。
关键词: 可靠性评估 重要抽样 交叉熵 参数迭代寻优 多级别参数
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Analysis of the influence of multilevel parameter on power system reliability evaluation in cross-entropy based importance sampling method
Abstract:The cross-entropy based importance sampling method (CE-IS) realizes the solution of the importance sampling probability density function (IS-PDF) through the iterative algorithm of parameter optimization, which significantly improves the simulation efficiency of Monte Carlo simulation and is widely used in power system reliability evaluation. However, the convergence criterion of the iterative algorithm is usually based on subjectively determined multilevel parameter. In order to analyze the influence of this subjective parameter on reliability evaluation, based on the iterative process of parameter optimization, this paper theoretically analyzes the relationship between multilevel parameter and IS-PDF parameter optimization result. In addition, in order to obtain the best simulation efficiency of important sampling, this paper provides a basis for the selection of multilevel parameter in the CE-IS method. Finally, the applicability and effectiveness of the proposed theory are verified by IEEE-RTS79 reliability test system.
Keywords: Reliability evaluation importance sampling cross-entropy parameter iterative optimization multilevel parameter
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交叉熵重要抽样法中多级别参数对电网可靠性评估的影响分析
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