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Investment in electricity networks with transmission switching

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  • Villumsen, J.C.
  • Philpott, A.B.

Abstract

We consider the application of Dantzig-Wolfe decomposition to stochastic integer programming problems arising in the capacity planning of electricity transmission networks that have some switchable transmission elements. The decomposition enables a column-generation algorithm to be applied, which allows the solution of large problem instances. The methodology is illustrated by its application to a problem of determining the optimal investment in switching equipment and transmission capacity for an existing network. Computational tests on IEEE test networks with 73 nodes and 118 nodes confirm the efficiency of the approach.

Suggested Citation

  • Villumsen, J.C. & Philpott, A.B., 2012. "Investment in electricity networks with transmission switching," European Journal of Operational Research, Elsevier, vol. 222(2), pages 377-385.
    • Handle: RePEc:eee:ejores:v:222:y:2012:i:2:p:377-385
    DOI: 10.1016/j.ejor.2012.05.002
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    References listed on IDEAS

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    1. Ryan, D. M. & Falkner, J. C., 1988. "On the integer properties of scheduling set partitioning models," European Journal of Operational Research, Elsevier, vol. 35(3), pages 442-456, June.
    2. Kavinesh J. Singh & Andy B. Philpott & R. Kevin Wood, 2009. "Dantzig-Wolfe Decomposition for Solving Multistage Stochastic Capacity-Planning Problems," Operations Research, INFORMS, vol. 57(5), pages 1271-1286, October.
    3. Roger E. Bohn & Michael C. Caramanis & Fred C. Schweppe, 1984. "Optimal Pricing in Electrical Networks over Space and Time," RAND Journal of Economics, The RAND Corporation, vol. 15(3), pages 360-376, Autumn.
    4. George B. Dantzig & Philip Wolfe, 1960. "Decomposition Principle for Linear Programs," Operations Research, INFORMS, vol. 8(1), pages 101-111, February.
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    Cited by:

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    3. Burak Kocuk & Hyemin Jeon & Santanu S. Dey & Jeff Linderoth & James Luedtke & Xu Andy Sun, 2016. "A Cycle-Based Formulation and Valid Inequalities for DC Power Transmission Problems with Switching," Operations Research, INFORMS, vol. 64(4), pages 922-938, August.
    4. Dominic White & Niven Winchester, 2018. "Energy- and multi-sector modelling of climate change mitigation in New Zealand: current practice and future needs," Working Papers 18_15, Motu Economic and Public Policy Research.
    5. Jabarnejad, Masood & Valenzuela, Jorge, 2016. "Optimal investment plan for dynamic thermal rating using benders decomposition," European Journal of Operational Research, Elsevier, vol. 248(3), pages 917-929.
    6. Pichler, Alois & Tomasgard, Asgeir, 2016. "Nonlinear stochastic programming–With a case study in continuous switching," European Journal of Operational Research, Elsevier, vol. 252(2), pages 487-501.
    7. Märkle-Huß, Joscha & Feuerriegel, Stefan & Neumann, Dirk, 2020. "Cost minimization of large-scale infrastructure for electricity generation and transmission," Omega, Elsevier, vol. 96(C).
    8. Moreira, Alexandre & Pozo, David & Street, Alexandre & Sauma, Enzo & Strbac, Goran, 2021. "Climate‐aware generation and transmission expansion planning: A three‐stage robust optimization approach," European Journal of Operational Research, Elsevier, vol. 295(3), pages 1099-1118.
    9. Ruiz, C. & Conejo, A.J., 2015. "Robust transmission expansion planning," European Journal of Operational Research, Elsevier, vol. 242(2), pages 390-401.
    10. Jonas Christoffer Villumsen & Joe Naoum‐Sawaya, 2016. "Column generation for stochastic green telecommunication network planning with switchable base stations," Naval Research Logistics (NRL), John Wiley & Sons, vol. 63(5), pages 351-366, August.

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