Distributed algorithms for optimal power flow problem

Yun Sang Albert Lam*, Baosen Zhang, David N. Tse

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

91 Citations (Scopus)


Optimal power flow (OPF) is an important problem for power generation and it is in general non-convex. With the employment of renewable energy, it will be desirable if OPF can be solved very efficiently so that its solution can be used in real time. With some special network structure, e.g. trees, the problem has been shown to have a zero duality gap and the convex dual problem yields the optimal solution. In this paper, we propose a primal and a dual algorithm to coordinate the smaller subproblems decomposed from the convexified OPF. We can arrange the subproblems to be solved sequentially and cumulatively in a central node or solved in parallel in distributed nodes. We test the algorithms on IEEE radial distribution test feeders, some random tree-structured networks, and the IEEE transmission system benchmarks. Simulation results show that the computation time can be improved dramatically with our algorithms over the centralized approach of solving the problem without decomposition, especially in tree-structured problems. The computation time grows linearly with the problem size with the cumulative approach while the distributed one can have size-independent computation time.

Original languageEnglish
Title of host publicationProceedings - 2012 IEEE 51st IEEE Conference on Decision and Control, CDC 2012
Number of pages8
ISBN (Electronic)9781467320665, 9781467320634, 9781467320641
Publication statusPublished - Dec 2012
Event51st IEEE Conference on Decision and Control, CDC 2012 - Maui, HI, United States
Duration: 10 Dec 201213 Dec 2012

Publication series

NameProceedings of the IEEE Conference on Decision and Control
ISSN (Print)0191-2216
ISSN (Electronic)0743-1546


Conference51st IEEE Conference on Decision and Control, CDC 2012
Country/TerritoryUnited States
CityMaui, HI
Internet address

Scopus Subject Areas

  • Control and Systems Engineering
  • Modelling and Simulation
  • Control and Optimization


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