基于场景分区的随机潮流解析算法  

Probabilistic Power Flow Analytic Algorithm Based on Scenario Partition

作　　者：连浩然 周保荣 秦鹏 王彤 别朝红[1] 

机构地区：[1]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),陕西省西安市710049 [2]南方电网科学研究院,广东省广州市510080

出　　处：《电网技术》2017年第10期3153-3160,共8页Power System Technology

基　　金：南方电网公司重点科技项目(CSGTRC-K163007)~~

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。With increasing penetration of renewable energy in power system, fluctuation of random factors ranges more widely, posing a great challenge to accuracy of conventional cumulant method. In this paper, a new probabilistic power flow method based on scenario partition is proposed. Scenario reduction algorithm is used to obtain typical working scenario of power system, and, on this basis, several scenario sets are generated. In each scenario set, the cumulant method is used to calculate probabilistic power flow. Overall distribution of power flow is obtained using total probability formula. The new probabilistic power flow algorithm based on scenario partition proposed in this paper completes partitioning operation of initial scenario database, and fluctuation range of the random factors is limited to the scenario set where they lie. Thus, the fluctuation of random factors is reduced equivalently, so the drawback is eliminated that the probabilistic power flow of power system with high proportion renewable energy cannot be accurately obtained with conventional cumulant method. Effectiveness and accuracy of the proposed method are verified on the modified IEEE-118 system.

关 键 词：可再生能源 精度 场景分区 场景集 半不变量法 全概率公式 

分 类 号：TM721[电气工程—电力系统及自动化]