4.7 Article

Combining Newton-Raphson and Stochastic Gradient Descent for Power Flow Analysis

期刊

IEEE TRANSACTIONS ON POWER SYSTEMS
卷 36, 期 1, 页码 514-517

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TPWRS.2020.3029449

关键词

Power flow; stochastic gradient descent; iterative methods

资金

  1. NSF [ECCS-1810537]
  2. Fondo de Sustentabilidad Energetica CONACYT-SENER, Mexico [708642, PESL-00247-2019]

向作者/读者索取更多资源

The paper introduces a hybrid first-order and second-order method that effectively avoids being trapped in local minima and demonstrates good performance on standard IEEE benchmarks.
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.

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