A successive flow direction enforcing algorithm for optimal operation of variable-impedance FACTS devices
A successive flow direction enforcing algorithm for optimal operation of variable-impedance FACTS devices
复制标题
用于变阻抗 FACTS 设备优化运行的连续流向强制算法
DOI：
10.1016/j.epsr.2022.108171
复制
发表时间：
2022
影响因子：
3.9
通讯作者：
Sahraei-Ardakani, Mostafa
中科院分区：
文献类型：
--
作者：
Rui, Xinyang;Sahraei-Ardakani, Mostafa
提出了一种求解含柔性交流输电系统（FACTS）装置的电力系统运行模型的新的连续潮流方向强制（SFDE）算法。FACTS装置的潮流控制能力可以提高现有输电网络的利用率。然而，在电力系统运行模型中对FACTS设备进行建模所增加的计算复杂性是FACTS部署的主要挑战之一。一个突出的组成部分是由可变阻抗FACTS设备的线性直流潮流方程引入的非线性。根据以往的研究，这种非线性可以通过预先分配的潮流方向配备FACTS恢复直流潮流方程的线性。然而，由于次优的流动方向分配，该方法在某些情况下具有收敛到次优解的问题。本文提出的算法可以解决次优问题，同时仍然实现计算效率的提高。采用强制潮流方向迭代求解含FACTS的电力系统运行模型，并根据前一次迭代的结果连续调整预定的潮流方向。仿真研究证实了该方法在几乎所有实际情况下都能在几次迭代内收敛到全局最优解的有效性。
This paper presents a novel successive flow direction enforcing (SFDE) algorithm for solving power system operation models with flexible AC transmission system (FACTS) devices. The power flow control capabilities of FACTS devices can improve the utilization of the existing transmission network. However, the added computational complexity of modeling FACTS devices in power system operation models is one of the primary challenges for FACTS deployment. A prominent component is the nonlinearity introduced by variable-impedance FACTS devices to the linear DC power flow equations. According to previous studies, such nonlinearity can be tackled by preassigning the power flow directions on lines equipped with FACTS to restore the linearity of DC power flow equations. However, this method has the issue of converging to suboptimal solutions in some cases, due to suboptimal flow direction assignment. The algorithm presented in this paper can address the issue of suboptimality, while still achieving computational efficiency improvements. Power system operation models with FACTS are solved iteratively with flow directions enforced, and the predetermined flow directions are adjusted successively based on the results of the previous iteration. Simulation studies confirm the effectiveness of the method in converging to the globally optimal solution within a few iterations in almost all practical cases.