基于CMCS-LIS法的主动配电网概率潮流计算

摘要

潮流计算是电力系统运行和规划或开展各种学术研究的基础,在含间歇性、随机性功率输出的风力发电机等分布式电源的主动配电网潮流计算中,概率潮流(probabilistic load flow,PLF)的应用最为广泛,可以有效考虑间歇性、随机性分布式电源接入配电网后电网运行参数或变量的不确定性大大增强问题。然而,由于某一区域内风速大小变化的趋势基本相近,导致各风力发电机所处位置的风速之间存在较强的相关性,现有概率潮流计算研究中未能有效处理风速等随机变量的相关性问题,导致概率潮流计算效率低,计算结果精度不高,影响电力系统中各种研究的结论正确性,甚至危及电网安全、可靠运行。为解决上述问题,提出利用统计学中的秩相关系数描述风速等随机变量的相关性,以提高概率潮流计算结果的精度；在风速、负荷等随机变量的采样过程中,提出在传统Monte-Carlo模拟法的随机抽样基础上利用拉丁超立方重要抽样技术(latin hypercube important sampling, LIS),以提高概率潮流计算的效率。为验证提出方法(简称CMCS-LIS法)的有效性,基于IEEE33节点系统并利用MATLAB软件编制计算机程序进行仿真试验。仿真结果表明：提出方法能够灵活处理风速等随机变量间的相关性,且计算效率高,具有良好的工程应用参考价值。%Power flow calculation of power system is the basis of the operation and planning or implementation of a variety of academic research. With intermittent, random power output of wind generators and other evenly distributed power systems included in the calculation of the power active power flow, the probabilistic load flow is most widely used, which can effectively take great enhancement of the operating parameters or variables of uncertainty of the power grid into consideration after connecting the intermittent, random distributed power supply to the distribution network. However, due to the basically similar trend of the size of wind speed change within a region, which explains the existence of the strong correlation between the location of the wind power generators. The existing probabilistic load flow calculation research cannot effectively deal with questions about the relevance of wind speed random variables, which leads to lower efficiency of the probabilistic load flow computation and the lower accuracy of the results, and influences the correctness of a variety of research conclusion in the power system, or even endangers the power system security and reliable operation. In order to resolve the above problems, the rank correlation coefficient in statistics describing the correlation of wind speed random variables has been put forward to improve the accuracy of probabilistic load flow calculation. In the process of sampling of the wind speed, load and so on, the use of the Latin hypercube importance sampling technique based on the traditional Monte Carlo simulation method of random sampling has been proposed to improve the efficiency of the probabilistic load flow computation. To verify the effectiveness of proposed method (referred to as CMCS-LIS method), on the basis of the IEEE33 bus system and coupled with utilizing MATLAB software to compile the computer program simulation tests were carried out. Simulation results revealed that the proposed method could flexibly deal with the correlation between wind speed and other random variables and boost computational efficiency. Furthermore, it has a good reference value in engineering application.