IDEAS home Printed from https://ideas.repec.org/p/ags/genres/18221.html
   My bibliography  Save this paper

DC Optimal Power Flow Formulation and Solution Using QuadProgJ

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://ageconsearch.umn.edu/record/18221/files/wp060014.pdf
    Download Restriction: no
    File URL: https://libkey.io/10.22004/ag.econ.18221?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    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, , vol. 27(1), pages 1-36, January.
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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. Martin Meinel & Michael Ulbrich & Sebastian Albrecht, 2014. "A class of distributed optimization methods with event-triggered communication," Computational Optimization and Applications, Springer, vol. 57(3), pages 517-553, April.
    4. 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.
    5. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    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. Paul L. Borrill & Leigh Tesfatsion, 2011. "Agent-based Modeling: The Right Mathematics for the Social Sciences?," Chapters, in: John B. Davis & D. Wade Hands (ed.), The Elgar Companion to Recent Economic Methodology, chapter 11, Edward Elgar Publishing.
    3. 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).
    4. Giorgio Fagiolo & Paul Windrum & Alessio Moneta, 2006. "Empirical Validation of Agent Based Models: A Critical Survey," LEM Papers Series 2006/14, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    5. Deddy Koesrindartoto & Junjie Sun, 2005. "An Agent-Based Computational Laboratory for Testing the Economic Reliability of Wholesale Power Market Designs," Computing in Economics and Finance 2005 50, Society for Computational Economics.
    6. 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.
    7. Moore, J. & Woo, C.K. & Horii, B. & Price, S. & Olson, A., 2010. "Estimating the option value of a non-firm electricity tariff," Energy, Elsevier, vol. 35(4), pages 1609-1614.
    8. Agustin J. Ros, 2017. "An Econometric Assessment of Electricity Demand in the United States Using Utility-specific Panel Data and the Impact of Retail Competition on Prices," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4).
    9. Peter Cramton & Steven Stoft, 2006. "The Convergence of Market Designs for Adequate Generating Capacity," Papers of Peter Cramton 06mdfra, University of Maryland, Department of Economics - Peter Cramton, revised 2006.
    10. Matteo Richiardi, 2003. "The Promises and Perils of Agent-Based Computational Economics," LABORatorio R. Revelli Working Papers Series 29, LABORatorio R. Revelli, Centre for Employment Studies.
    11. Westerhoff Frank H., 2008. "The Use of Agent-Based Financial Market Models to Test the Effectiveness of Regulatory Policies," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 228(2-3), pages 195-227, April.
    12. Pollitt, Michael G., 2012. "The role of policy in energy transitions: Lessons from the energy liberalisation era," Energy Policy, Elsevier, vol. 50(C), pages 128-137.
    13. Donald N. Dewees, 2008. "Pollution and the Price of Power," The Energy Journal, International Association for Energy Economics, vol. 0(Number 2), pages 81-100.
    14. Tesfatsion, Leigh, 2007. "Agents come to bits: Towards a constructive comprehensive taxonomy of economic entities," Journal of Economic Behavior & Organization, Elsevier, vol. 63(2), pages 333-346, June.
    15. Hokky Situngkir, 2004. "Money-Scape: A Generic Agent-Based Model of Corruption," Computational Economics 0405008, University Library of Munich, Germany.
    16. Silvia Concettini & Anna Creti, 2013. "Liberalization of electricity retailing in Europe: coming back or going forth?," Working Papers hal-00915924, HAL.
    17. John Duffy & M. Utku Unver, 2003. "Asset Price Bubbles and Crashes with Near-Zero-Intelligence Traders: Towards an Understanding of Laboratory Findings," Computational Economics 0307001, University Library of Munich, Germany, revised 17 Mar 2004.
    18. Juan Manuel Larrosa, 2016. "Agentes computacionales y análisis económico," Revista de Economía Institucional, Universidad Externado de Colombia - Facultad de Economía, vol. 18(34), pages 87-113, January-J.
    19. Richard O’Neill & Emily Fisher & Benjamin Hobbs & Ross Baldick, 2008. "Towards a complete real-time electricity market design," Journal of Regulatory Economics, Springer, vol. 34(3), pages 220-250, December.
    20. Kaller, Alexander & Bielen, Samantha & Marneffe, Wim, 2018. "The impact of regulatory quality and corruption on residential electricity prices in the context of electricity market reforms," Energy Policy, Elsevier, vol. 123(C), pages 514-524.

    More about this item

    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

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:ags:genres:18221. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: AgEcon Search (email available below). General contact details of provider: https://edirc.repec.org/data/deiasus.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.