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DC Optimal Power Flow Formulation and Solution Using QuadProgJ

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  • Sun, Junjie
  • Tesfatsion, Leigh

Abstract

Nonlinear AC Optimal Power Flow (OPF) problems are commonly approximated by linearized DC OPF problems to obtain real power solutions for restructured wholesale power markets. We first present a standard DC OPF problem, which has the numerically desirable form of a strictly convex quadratic programming (SCQP) problem when voltage angles are eliminated by substitution. We next augment this standard DC OPF problem in a physically meaningful way, still retaining an SCQP form, so that solution values for voltage angles and locational marginal prices are directly obtained along with real power injections and branch flows. We then show how this augmented DC OPF problem can be solved using QuadProgJ, an open-source Java SCQP solver newly developed by the authors that implements the well-known dual active-set SCQP algorithm by Goldfarb and Idnani (1983). To demonstrate the accuracy of QuadProgJ, comparative results are reported for a well-known suite of numerical QP test cases with up to 1500 decision variables plus constraints. Detailed QuadProgJ results are also reported for 3-node and 5-node DC OPF test cases taken from power systems texts and ISO-NE/MISO/PJM training manuals.

Suggested Citation

  • Sun, Junjie & Tesfatsion, Leigh, 2006. "DC Optimal Power Flow Formulation and Solution Using QuadProgJ," Working Papers 18221, Iowa State University, Department of Economics.
    • Handle: RePEc:ags:genres:18221
    DOI: 10.22004/ag.econ.18221
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    1. Koesrinartoto, D. & Sun, Junjie & Tesfatsion, Leigh, 2005. "An agent-based computational laboratory for testing the economic reliability of wholesale power market designs," ISU General Staff Papers 200501010800001043, Iowa State University, Department of Economics.
    2. Paul L. Joskow, 2006. "Markets for Power in the United States: An Interim Assessment," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 1-36.
    3. Leigh Tesfatsion, 2002. "Agent-Based Computational Economics," Computational Economics 0203001, University Library of Munich, Germany, revised 15 Aug 2002.
    4. Koesrindartoto, Deddy P. & Tesfatsion, Leigh, 2004. "Testing the Reliability of FERC's Wholesale Power Market Platform: An Agent-Based Computational Economics Approach," Staff General Research Papers Archive 12326, Iowa State University, Department of Economics.
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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.
    2. Sensfuß, Frank & Ragwitz, Mario & Genoese, Massimo & Möst, Dominik, 2007. "Agent-based simulation of electricity markets: a literature review," Working Papers "Sustainability and Innovation" S5/2007, Fraunhofer Institute for Systems and Innovation Research (ISI).
    3. A. Farina & A. Graziano & F. Mariani & F. Zirilli, 2008. "Probabilistic Analysis of Failures in Power Transmission Networks and Phase Transitions: Study Case of a High-Voltage Power Transmission Network," Journal of Optimization Theory and Applications, Springer, vol. 139(1), pages 171-199, October.
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    5. Weidlich, Anke & Veit, Daniel, 2008. "A critical survey of agent-based wholesale electricity market models," Energy Economics, Elsevier, vol. 30(4), pages 1728-1759, July.

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    Keywords

    Research Methods/ Statistical Methods;

    JEL classification:

    • B4 - Schools of Economic Thought and Methodology - - Economic Methodology
    • C6 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling
    • C88 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Other Computer Software
    • 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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