基于场景分区的随机潮流解析算法

发布时间：2018-01-16 10:37

本文关键词：基于场景分区的随机潮流解析算法　出处：《电网技术》2017年10期 　论文类型：期刊论文

【摘要】：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。
[Abstract]:The permeability of renewable energy in power system is increasing day by day, and the fluctuation range of random factors is increasing gradually. This brings a great challenge to the accuracy of the conventional semi-invariant method. In this paper, a new stochastic power flow algorithm based on scene partition is proposed. Firstly, the scene reduction algorithm is used to obtain the typical running scenarios of the system. On this basis, multiple scene sets are generated to complete the partition of the initial scene library. Then, the semi-invariant method is used to calculate the random power flow in each scene set. Finally, the overall power flow distribution of power system is obtained by using the full probability formula. The scene partition operation proposed in this paper limits the fluctuation range of random factors to its scene set. The fluctuation degree of random factors is reduced effectively. Therefore, the limitation of conventional semi-invariant method for accurately obtaining the stochastic power flow characteristics of power system with high proportion of renewable energy is overcome. The validity and correctness of the proposed method are obtained by IEEE-118 example system. Verified.
【作者单位】：电力设备电气绝缘国家重点实验室陕西省智能电网重点实验室(西安交通大学电气工程学院);南方电网科学研究院;
【基金】：南方电网公司重点科技项目(CSGTRC-K163007)~~
【分类号】：TM744
【正文快照】： 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。0引言随着化石能源枯竭和全球气候变暖,大力发展可再生能源是实现能源可持续发展的重要途径

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