基于拉普拉斯变换技术的配电网概率潮流算法

由于分布式光伏电源接入地区配电网后,其随机性和相关性使得潮流变化具有一定的不确定性,因此针对光伏电源及波动负荷的不确定性,提出了一种基于拉普拉斯变换技术的半不变量法配电网概率潮流计算.通过拉普拉斯变换特性利用半不变量有效估计随机变量的概率密度函数或累积分布函数,进而描述含分布式光伏电源接入配电网的随机变化情况.为了验证组合半不变量和拉普拉斯变换技术,将仿真结果与蒙特卡洛模拟和基于最大熵原理的半不变量方法进行比较.IEEE-33节点算例表明所提方法具有较高的计算精度和较快的计算速度,与基于最大熵原理的半不变量法相比计算负担更低.

Probabilistic load flow calculation of power distributive network based on Laplace transformation technique

After connecting distributive photovoltaic power supply into regional power distribution network, the change of load flow is made to have a certain uncertainty due to the randomness and correlation of the photovoltaic power supply.Therefore, aimed at the uncertainty of the photovoltaic power supply and fluctuating load, a probabilistic load flow calculation method is proposed for the power distribution network based on the semi-invariable method of Laplace transformation technique. By means of the Laplacian transformation feature and semi-invariable, the probabilistic density function or cumulative distribution function of the random variable is estimated effectively and the random variation condition of power distribution network which includes the connected distributive photovoltaic power supply into itself. In order to verify the combination effect of semi-invariable with Laplace transformation technique, the simulation result is compared with the results of Monte Carlo simulation method and maxi-entropy principle-based semi-invariable method. It is shown by a computational example of power distribution network with IEEE-33 node that the proposed method will have a higher computational accuracy, faster calculation speed, and a lower computational burden than the maxi-entropy principle-based semi-invariable method.