摘要
基于随机抽样的蒙特卡罗方法(MC_RS)由于原理简单、易于实现,常用于电力系统的可靠性评估,但在大规模风电接入,特别是以单个小容量的机组接入的情况下会存在样本容量大、效率低等不足。因此提出使用基于拉丁超立方采样的蒙特卡罗(MC_LHS)方法来解决含风电的电力系统概率可靠性评估问题,此方法由于使用了拉丁超立方采样,能有效地改善样本值对输入随机变量的分布空间的覆盖程度和使用Cholesky分解来降低输入变量之间的相关性系数,从而提高了采样效率、增加收敛速度和提高评估准确度。把提出的MC_LHS方法应用到改进IEEE-RTS79算例中,并与常规MC_RS进行比较,结果验证了该方法的有效性。
The reliability of power system is often evaluated through Monte-Carlo（MC） simulation with random sampling, namely MC_RS. But it is inappropriate for the power system with large scale wind power integration, because the sample size is large and the assessment efficiency is low. This paper proposes an improved assessment method by MC_LHS, combined the traditional MC method with LHS（Latin hypercube sampling） method, to improve the coverage of sample values for input spaces of random variables and increase the sampling efficiency. Consequently the integrated assessment method could improve the assessment efficiency and stability, as well as reduce the correlation coefficients of repeated assessment results. The analysis of improved IEEE-RTS 79 reliability test system shows that the proposed assessment method is effective.
出处
《电工技术学报》
EI
CSCD
北大核心
2016年第10期193-206,共14页
Transactions of China Electrotechnical Society
基金
国家高技术研究发展计划(863计划)资助项目(2012AA050201)
