Suboptimality of decentralized methods for OPF

Ilgiz Murzakhanov, Alexander Malakhov, Elena Gryazina

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

2 Citations (Scopus)


We examine the fact that decentralized methods may converge to suboptimal solution. Observed in numerous studies of decentralized optimal power flow problem it has a simple explanation: the curse of non-convexity. We numerically assess the performance of decentralized interior point method (DIPM) and alternating direction method of multipliers (ADMM). The algorithms were tested in two situations: grid decomposition for a few areas associated with independent Transmission System Operators (TSOs) as in super grids and total decomposition till node level that models prosumers behavior. In particular, we demonstrate that the obtained optimal state and convergence rate depends on the starting point. The algorithms were tested on IEEE 9, 14, 118 bus systems. Besides, we discuss the advantages and drawbacks of decentralized optimization approaches.

Original languageEnglish
Title of host publication2019 IEEE Milan PowerTech, PowerTech 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538647226
Publication statusPublished - Jun 2019
Event2019 IEEE Milan PowerTech, PowerTech 2019 - Milan, Italy
Duration: 23 Jun 201927 Jun 2019

Publication series

Name2019 IEEE Milan PowerTech, PowerTech 2019


Conference2019 IEEE Milan PowerTech, PowerTech 2019


  • ADMM
  • Decentralized interior point method
  • Decentralized optimization
  • Optimal power flow


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