Combining Newton-Raphson and Stochastic Gradient Descent for Power Flow Analysis
Combining Newton-Raphson and Stochastic Gradient Descent for Power Flow Analysis
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DOI：
10.1109/tpwrs.2020.3029449
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发表时间：
2021-01
影响因子：
6.6
通讯作者：
N. Costilla-Enríquez;Yang Weng;Baosen Zhang
中科院分区：
文献类型：
--
作者：
N. Costilla-Enríquez;Yang Weng;Baosen Zhang
潮流问题是解决电网运行和规划问题不可缺少的工具，在过去的半个世纪里一直受到研究。目前，流行的算法需要二阶方法，这可能会导致性能差时，初始化点是穷人或当系统的压力。随着电网中发电和负荷分布的变化，这些情况变得越来越普遍。在本文中，我们提出了一个混合的一阶和二阶方法，有效地逃避局部极小，可能会陷入现有的算法。我们证明了我们的算法在标准IEEE基准的性能。
The power flow problem is an indispensable tool to solve many of the operation and planning problems in the electric grid and has been studied for the last half-century. Currently, popular algorithms require second-order methods, which may lead to poor performance when the initialization points are poor or when the system is stressed. These conditions are becoming more common as both the generation and load profiles changes in the grid. In this paper, we present a hybrid first-order and second-order method that effectively escapes local minima that may trap existing algorithms. We demonstrate the performance of our algorithm on standard IEEE benchmarks.