基于场景分区的随机潮流解析算法Probabilistic Power Flow Analytic Algorithm Based on Scenario Partition
连浩然;周保荣;秦鹏;王彤;别朝红;
摘要(Abstract):
可再生能源在电力系统中的渗透率日益提高,随机因素的波动范围逐渐增大,这对常规半不变量法的精度带来了很大的挑战。文中提出一种基于场景分区的随机潮流新算法:首先,采用场景削减算法获取系统典型运行场景,以此为基础生成多个场景集,完成对初始场景库的分区;然后,在各个场景集内部采用半不变量法进行随机潮流计算;最后,应用全概率公式获取电力系统整体潮流分布情况。文中提出的场景分区操作将随机因素的波动范围限制在其所在场景集,等效地减小了随机因素波动程度,从而克服了常规半不变量法无法准确获取含高比例可再生能源电力系统随机潮流特性的局限性。所提方法的有效性和正确性在IEEE-118算例系统上得到了验证。
关键词(KeyWords): 可再生能源;精度;场景分区;场景集;半不变量法;全概率公式
基金项目(Foundation): 南方电网公司重点科技项目(CSGTRC-K163007)~~
作者(Author): 连浩然;周保荣;秦鹏;王彤;别朝红;
Email:
DOI: 10.13335/j.1000-3673.pst.2017.1729
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