摘要
评估组合系统可靠性时,蒙特卡罗模拟法不受系统规模及非线性的影响,且结果准确的特性使其在大型电力系统可靠性评估中具有优越性。但为了获得精度较高的可靠性指标,其往往需要较长计算时间。针对这一问题,采用重要抽样法与离散拉丁超立方抽样相结合的方法,从减小样本方差与增加样本均匀性两方面提高蒙特卡罗模拟的收敛性。对于大规模发输电系统,运用灵敏度分析与线性规划相结合的方法进行系统过负荷校正,既能保证求解最优性又可以提高求解速度。将该算法应用于IEEE RTS79系统、IEEE RTS96系统和某电网500 k V及以上电压等级电力系统计算可靠性指标,验证了该算法的可行性。
As its sampling frequency is independent of the scale of the system and non-linear performance, Monte-Carlo simulation is widely applied to reliability evaluation of a complex large transmission system because of its accurate result. However, it takes a relatively long period of time to obtain a higher accurate reliability index. In order to solve this problem, the combination of importance sampling method and discrete Latin hypercube sampling method is able to reduce the variance of the sample space and uniformly sample it simultaneously, which improves the convergence of Monte-Carlo simulation. This paper points out that, the combination of sensitivity analysis and linear programming in the process of overload correction is able to guarantee the solution optimality as well as improve the solving speed. Finally, the algorithm is presented for IEEE RTS79, IEEE RTS96 and a certain system to obtain the reliability index, the result proves its practicability.
出处
《电力系统保护与控制》
EI
CSCD
北大核心
2016年第13期96-103,共8页
Power System Protection and Control
基金
国家自然科学基金重点项目(51337005)
国家电网公司基础性前瞻性项目(XT71-14-002)~~
