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Analytical Solutions for Power Flow Equations Based on the Multivariate Quotient-Difference Method

机译:基于多元商差法的潮流方程解析解

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This paper proposes a method of obtaining the approximate analytical solutions for power flow equations based on the multivariate quotient-difference method. The power flow solutions for different operating conditions can be directly obtained by scaling multiple symbolic variables in the analytical solutions, such that the power injections or consumptions of selected buses or groups of buses can be independently adjusted. This method first uses the multi-dimensional holomorphic embedding method to derive the power flow solutions in the form of multivariate power series. Then, the multivariate quotient-difference method is applied to transform multivariate power series (MPS) to multivariate Padé approximants (MPA) to expand the radius of convergence (ROC), so that the accuracy of the derived analytical solutions can be significantly increased. This method can adapt to many online applications, since the analytical solution can be derived offline and evaluated online by only plugging values into the system symbolic variables according to actual operating conditions. This proposed method is validated in detail on the IEEE 39-bus New England power system considering independent load variations in multiple regions.
机译:提出了一种基于多元商差法的潮流方程近似解析解的求取方法。通过缩放解析解决方案中的多个符号变量,可以直接获得针对不同运行条件的潮流解决方案,从而可以独立调整所选母线或母线组的功率注入或功耗。该方法首先使用多维全同嵌入方法以多元幂级数形式导出潮流解决方案。然后,采用多元商差方法将多元幂级数(MPS)转换为多元Padé近似值(MPA),以扩展收敛半径(ROC),从而可以显着提高导出的解析解的准确性。此方法可以适应许多在线应用程序,因为可以根据实际操作条件仅通过将值插入系统符号变量中就可以离线导出分析解决方案并对其进行在线评估。考虑到多个区域中独立的负载变化,该提议的方法已在IEEE 39总线新英格兰电力系统上进行了详细验证。

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