基于双层前推回代的孤岛微电网仿射潮流算法

An Affine Power Flow Algorithm for Islanded Microgrid Based on Double-layer Forward-backward Substitution

  • 摘要: 传统前推回代算法因具有迭代逻辑清晰、收敛性较好等优点,常被应用于配电网潮流计算。然而,该算法在计算过程中依赖于平衡节点的存在,因此无法有效解决在下垂控制策略下、无平衡节点的孤岛微电网潮流问题。对此,提出一种基于双层前推回代的孤岛微电网仿射潮流算法。首先,建立下垂控制型分布式电源、负荷的仿射潮流模型。其次,采用双层迭代的前推回代算法计算仿射潮流:外层迭代修正系统频率和根节点电压;内层采用前推回代法计算其余节点的电压复仿射值。最后,根据系统频率和根节点电压所处迭代位置的不同,总结3种不同迭代方式下的仿射潮流算法,并对其收敛性进行对比分析。算例结果表明,该方法在确保计算保守性与完备性的同时,能够显著提高计算效率,且当系统频率与根节点电压均设置于外层时,收敛性能最优。

     

    Abstract: The traditional algorithm is widely utilized in power flow calculations of distribution network due to its clear iterative logic and favorable convergence. However, its calculation depends on the balanced nodes, which makes it unable to address the issue of the islanded microgrid without balanced nodes under droop control. In this paper, we propose an affine power flow algorithm for islanded microgrid based on double-layer forward-backward substitution. First, an affine power flow model of distributed power supply and load under droop control is established. Secondly, a double-layer iterative forward-backward substitution algorithm is employed to calculate the affine power flow. In this algorithm, the outer layer iteratively corrects the system frequency and the root node voltage, while the inner layer uses the forward-backward substitution method to calculate the complex affine voltage values of the remaining nodes. Finally, according to the system frequency and the different iterative states of the root node voltage, the affine power flow algorithms under three different iterative methods are summarized in detail, and their convergence performance is compared and analyzed. The results of the example demonstrate that the double-layer affine algorithm proposed in this paper can significantly enhance computational efficiency while maintaining the conservation and completeness of the calculation. The system frequency and the root node voltage are set in the outer layer simultaneously, leading to optimal convergence performance during iteration.

     

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