Distributed optimal power flow: An Augmented Lagrangian-Sequential Quadratic Programming approach

Zejiang Hou, Ho Chun Wu, Shing Chow Chan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

3 Citations (Scopus)

Abstract

This paper presents a distributed optimal power flow approach based on Augmented Lagrangian (AL) and Sequential Quadratic Programming (SQP). It is able to separate the OPF into smaller sub-problems, which could be iteratively solved individually using the SQP. This utilizes the SQP for largescale problems with non-linear objective functions and constraints. Simulation and comparison using the IEEE 30 and 118 buses examples show that the proposed distributed approach is able to achieve comparable performance with other benchmark centralized solvers provided by the FMINCON in MATPOWER. This suggests the proposed approach may serve an attractive alternative to other OPF algorithms.

Original languageEnglish
Title of host publicationIEEE International Symposium on Circuits and Systems
Subtitle of host publicationFrom Dreams to Innovation, ISCAS 2017 - Conference Proceedings
ISBN (Electronic)9781467368520
DOIs
Publication statusPublished - 25 Sept 2017
Externally publishedYes
Event50th IEEE International Symposium on Circuits and Systems, ISCAS 2017 - Baltimore, United States
Duration: 28 May 201731 May 2017

Publication series

NameProceedings - IEEE International Symposium on Circuits and Systems
ISSN (Print)0271-4310

Conference

Conference50th IEEE International Symposium on Circuits and Systems, ISCAS 2017
Country/TerritoryUnited States
CityBaltimore
Period28/05/1731/05/17

Keywords

  • Augmented Lagrangian
  • Distributed
  • Optimal Power Flow
  • Sequential Quadratic Programming

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