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Open-Source Software for Power Industry Research, Teaching, and Training: A DC Optimal Power Flow Illustration


  • Sun, Junjie
  • Tesfatsion, Leigh S.


Software currently available for power industry studies is largely proprietary. Lack of open-source access prevents users from gaining a complete and accurate understanding of what has been implemented, restricts the ability of users to experiment with new software features, and hinders users from tailoring software to specific training scenarios. This study reports on the development of a stand-alone open-source Java solver for DC optimal power flow (DC-OPF) problems suitable for research, teaching, and training purposes. The DC-OPF solver is shown to match or exceed the accuracy of BPMPD, a proprietary third-party QP solver highly recommended by MatPower, when tested on a public repository of small to medium-sized QP problems. The capabilities of the DC-OPF solver are illustrated for a 5-node DC-OPF test case commonly used for training purposes. Related work can be accessed at:

Suggested Citation

  • Sun, Junjie & Tesfatsion, Leigh S., 2007. "Open-Source Software for Power Industry Research, Teaching, and Training: A DC Optimal Power Flow Illustration," Staff General Research Papers Archive 12775, Iowa State University, Department of Economics.
  • Handle: RePEc:isu:genres:12775

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    Cited by:

    1. Junjie Sun & Leigh Tesfatsion, 2007. "Dynamic Testing of Wholesale Power Market Designs: An Open-Source Agent-Based Framework," Computational Economics, Springer;Society for Computational Economics, vol. 30(3), pages 291-327, October.

    More about this item


    DC optimal power flow; QuadProgJ; AMES; software; open-source; Java; DCOPFJ;

    JEL classification:

    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • L94 - Industrial Organization - - Industry Studies: Transportation and Utilities - - - Electric Utilities
    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy

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