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

Napoleon Costilla-Enriquez, Yang Weng, Baosen Zhang

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish (US)
Article number9216079
Pages (from-to)514-517
Number of pages4
JournalIEEE Transactions on Power Systems
Volume36
Issue number1
DOIs
StatePublished - Jan 2021

Keywords

  • iterative methods
  • Power flow
  • stochastic gradient descent

ASJC Scopus subject areas

  • Energy Engineering and Power Technology
  • Electrical and Electronic Engineering

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