具有指数收敛速度的电力系统全分布式潮流算法

为了满足互联电力系统潮流计算对数据隐私的需求，提出了一种全分布式潮流算法。该方法由内环迭代与外环迭代组成，外环迭代基于牛顿-拉夫逊法计算雅可比矩阵，内环迭代采用全分布式算法在互联电网各分区分别求解各自的潮流修正方程。该方法不需要协调层对分布式计算进行分解协调，各分区仅需要与邻居分区交换潮流方程修正量的信息，外环迭代收敛特性与全局潮流相同，内环迭代保证收敛且具有指数收敛速度。通过IEEE39节点和118节点算例的测试表明，该方法具有较高的收敛性，适合于没有协调层的分布式潮流计算。

A Fully Distributed Power Flow Algorithm with Exponentially Fast Convergence

In order to meet the data privacy requirements for interconnected power system power flow calculations, a fully distributed power flow algorithm is proposed. The method is composed of outer iteration and inner iteration. The outer iteration calculates the Jacobian matrix based on Newton-Raphson method, while the inner iteration uses the distributed algorithm to solve power flow correction equation for each partitioned area of interconnected power system. The proposed algorithm does not need any coordination layer to decompose and coordinate the distributed calculation, and each partitioned area in the power system only needs to exchange correction information of power flow equation with neighbor areas. The outer iteration has the same convergence behavior as global power flow, while the inner iteration can guarantee convergence with exponential rate. The numerical tests on IEEE 39- and 118-bus systems show that the proposed method has good convergence behavior and is suitable for power flow calculation without coordination layer.