摘要
概率潮流(probabilistic load flow,PLF)计算是电力系统稳态运行分析的重要工具。针对大多数现有PLF计算方法要求已知输入随机变量的概率分布函数,而其概率分布函数难以准确建模这一问题,提出一种基于多项式正态变换和拉丁超立方采样的PLF计算方法。该方法根据输入随机变量的数字特征,通过多项式正态变换技术建立其概率分布模型,进而由基于拉丁超立方采样的蒙特卡罗仿真法得到系统节点电压和支路潮流的数字特征及其概率分布曲线。采用IEEE 30节点和IEEE 118节点系统对所提方法的有效性进行了验证。仿真结果表明:所提方法是有效的,该方法不仅具有计算速度快、精度高和稳健性好的优点,还能灵活处理输入随机变量间的相关性,具有较好的工程实用价值。
Probabilistic load flow （PLF） calculation is an important tool for power system steady state performance analysis. Most of the existing PLF methods require to know the probability distribution functions of input random variables, which are very difficult to be modeled accurately. In the paper, a PLF method based on polynomial normal transformation and Latin hypercube sampling was proposed. This method used the numerical characteristics of input random variables to establish their probability distribution models by polynomial normal transformation technique, and then adopted Monte Carlo simulation method based on Latin hypercube sampling to obtain the numerical characteristics and probability distribution curves of bus voltage and branch power. The validity of proposed method was tested on IEEE 30 bus system and IEEE 118 bus system. The simulation results show that the proposed method is effective, which not only has the advantages of fast computation, high accuracy and good robustness, but also can deal with the correlation between input random variables flexibly. The proposed method is of some practical engineering value.
出处
《中国电机工程学报》
EI
CSCD
北大核心
2013年第13期92-100,共9页
Proceedings of the CSEE
基金
国家重点基础研究发展计划项目(973项目)(2009CB219701)
国家863高技术基金项目(2011AA05A101
2011AA05A109)
国家自然科学基金项目(50937002)
南方电网公司科技项目(CSG[2013]0301ZD1)~~
关键词
概率潮流
多项式正态变换
拉丁超立方采样
相关性
数字特征
probabilistic load flow （PLF）
polynomialnormal transformation
latin hypercube sampling
correlation
