基于随机降阶与随机响应面法的电网概率潮流计算

马玉涛; 刘青; 李龙威; 刘运锋

doi:10.16513/j.2096-2185.DE.(2025)010-02-0090-08

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分布式能源 ›› 2025, Vol. 10 ›› Issue (2) : 90-97. DOI: 10.16513/j.2096-2185.DE.(2025)010-02-0090-08

应用技术

基于随机降阶与随机响应面法的电网概率潮流计算

马玉涛 ¹ ,
刘青 ¹ ,
李龙威 ¹ ,
刘运锋 ²

作者信息 +

Probabilistic Power Flow Calculation Based on Stochastic Reduced Order Method and Stochastic Response Surface Method

Author information +

文章历史 +

摘要

源荷不确定性是新型电力系统的典型特点之一，因此有必要对考虑源荷变化的电网概率潮流进行计算。针对随机响应面法（stochastic response surface method，SRSM）在构建多项式混沌展开式时通过随机抽样生成样本的盲目性，采用随机降阶法（stochastic reduced order method，SROM）选取重要样本以提高计算结果的准确性。将光照强度、风速参数和负荷作为随机输入变量，建立源荷概率模型并对其进行相关性处理，采用SROM选取三维输入变量的重要样本生成概率潮流的多项式混沌展开式；提出基于SROM-SRSM的电力系统概率潮流计算方法并给出详细计算流程；以改进的IEEE 33节点系统为算例，比较了不同多项式阶数下的模拟时间和精度，采用3阶多项式混沌展开式作为概率潮流计算的基础，比较了不同计算方法下的概率潮流计算结果，得到了潮流状态变量的概率分布。结果表明：相对于传统的蒙特卡罗方法，所提的SROM-SRSM方法减少了计算耗时，采用随机降阶法优选样本提高了概率潮流计算结果的准确性。

Abstract

Source-load uncertainty is one of the typical characteristics of new power systems， so it is necessary to calculate the probabilistic tidal currents of power grids considering source-load variations. Aiming at the blindness of stochastic response surface method （SRSM） in constructing polynomial chaotic expansion by random sampling to generate samples， this paper adopts stochastic reduced order method （SROM） to select important samples in order to improve the accuracy of calculation results. The light intensity， wind speed parameter and load are taken as random input variables， the source-load probability model is established and its correlation is processed， and the polynomial chaotic expansion of probabilistic tidal current is generated by using SROM to select the important samples of the three-dimensional input variables； the probabilistic tidal current computation method of the electric power system based on SROM-SRSM is proposed and the detailed computation process is given； the improved IEEE 33-node system is used as an example to the simulation time and accuracy under different polynomial orders are compared； the 3rd order polynomial chaotic expansion is used as the basis of probabilistic tidal current calculation； the results of probabilistic tidal current calculation under different calculation methods are compared and the probability distribution of tidal current state variables is obtained. The results show that compared with the traditional Monte Carlo method， the SROM-SRSM proposed in this paper reduces the computation time， and the accuracy of the probabilistic tidal current calculation results is improved by adopting the stochastic descending order method to optimize the samples.

导出引用

马玉涛, 刘青, 李龙威, 等. 基于随机降阶与随机响应面法的电网概率潮流计算[J]. 分布式能源. 2025, 10(2): 90-97 https://doi.org/10.16513/j.2096-2185.DE.(2025)010-02-0090-08

Yutao MA, Qing LIU, Longwei LI, et al. Probabilistic Power Flow Calculation Based on Stochastic Reduced Order Method and Stochastic Response Surface Method[J]. Distributed Energy Resources. 2025, 10(2): 90-97 https://doi.org/10.16513/j.2096-2185.DE.(2025)010-02-0090-08

中图分类号： TK01

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