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