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Deterministic electric power infrastructure planning: Mixed-integer programming model and nested decomposition algorithm

Author

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  • Lara, Cristiana L.
  • Mallapragada, Dharik S.
  • Papageorgiou, Dimitri J.
  • Venkatesh, Aranya
  • Grossmann, Ignacio E.

Abstract

This paper addresses the long-term planning of electric power infrastructures considering high renewable penetration. To capture the intermittency of these sources, we propose a deterministic multi-scale Mixed-Integer Linear Programming (MILP) formulation that simultaneously considers annual generation investment decisions and hourly operational decisions. We adopt judicious approximations and aggregations to improve its tractability. Moreover, to overcome the computational challenges of treating hourly operational decisions within a monolithic multi-year planning horizon, we propose a decomposition algorithm based on Nested Benders Decomposition for multi-period MILP problems to allow the solution of larger instances. Our decomposition adapts previous nested Benders methods by handling integer and continuous state variables, although at the expense of losing its finite convergence property due to potential duality gap. We apply the proposed modeling framework to a case study in the Electric Reliability Council of Texas (ERCOT) region, and demonstrate massive computational savings from our decomposition.

Suggested Citation

  • Lara, Cristiana L. & Mallapragada, Dharik S. & Papageorgiou, Dimitri J. & Venkatesh, Aranya & Grossmann, Ignacio E., 2018. "Deterministic electric power infrastructure planning: Mixed-integer programming model and nested decomposition algorithm," European Journal of Operational Research, Elsevier, vol. 271(3), pages 1037-1054.
    • Handle: RePEc:eee:ejores:v:271:y:2018:i:3:p:1037-1054
    DOI: 10.1016/j.ejor.2018.05.039
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    1. LE CADRE, Hélène & PAPAVASILIOU, Anthony & SMEERS, Yves, 2015. "Wind farm portfolio optimization under network capacity constraints," LIDAM Reprints CORE 2689, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    2. Alexander E. MacDonald & Christopher T. M. Clack & Anneliese Alexander & Adam Dunbar & James Wilczak & Yuanfu Xie, 2016. "Future cost-competitive electricity systems and their impact on US CO2 emissions," Nature Climate Change, Nature, vol. 6(5), pages 526-531, May.
    3. Santiago Cerisola & Álvaro Baíllo & José M. Fernández-López & Andrés Ramos & Ralf Gollmer, 2009. "Stochastic Power Generation Unit Commitment in Electricity Markets: A Novel Formulation and a Comparison of Solution Methods," Operations Research, INFORMS, vol. 57(1), pages 32-46, February.
    4. Marshall L. Fisher, 2004. "The Lagrangian Relaxation Method for Solving Integer Programming Problems," Management Science, INFORMS, vol. 50(12_supple), pages 1861-1871, December.
    5. Nahmmacher, Paul & Schmid, Eva & Hirth, Lion & Knopf, Brigitte, 2016. "Carpe diem: A novel approach to select representative days for long-term power system modeling," Energy, Elsevier, vol. 112(C), pages 430-442.
    6. Steeger, Gregory & Rebennack, Steffen, 2017. "Dynamic convexification within nested Benders decomposition using Lagrangian relaxation: An application to the strategic bidding problem," European Journal of Operational Research, Elsevier, vol. 257(2), pages 669-686.
    7. Pina, André & Silva, Carlos & Ferrão, Paulo, 2011. "Modeling hourly electricity dynamics for policy making in long-term scenarios," Energy Policy, Elsevier, vol. 39(9), pages 4692-4702, September.
    8. Pina, André & Silva, Carlos A. & Ferrão, Paulo, 2013. "High-resolution modeling framework for planning electricity systems with high penetration of renewables," Applied Energy, Elsevier, vol. 112(C), pages 215-223.
    9. Francisco Munoz & Enzo Sauma & Benjamin Hobbs, 2013. "Approximations in power transmission planning: implications for the cost and performance of renewable portfolio standards," Journal of Regulatory Economics, Springer, vol. 43(3), pages 305-338, June.
    10. O. Schmidt & A. Hawkes & A. Gambhir & I. Staffell, 2017. "The future cost of electrical energy storage based on experience rates," Nature Energy, Nature, vol. 2(8), pages 1-8, August.
    11. Koltsaklis, Nikolaos E. & Georgiadis, Michael C., 2015. "A multi-period, multi-regional generation expansion planning model incorporating unit commitment constraints," Applied Energy, Elsevier, vol. 158(C), pages 310-331.
    12. Antonio Frangioni, 2005. "About Lagrangian Methods in Integer Optimization," Annals of Operations Research, Springer, vol. 139(1), pages 163-193, October.
    13. Hélène Le Cadre & Anthony Papavasiliou & Yves Smeers, 2015. "Wind Farm Portfolio Optimization under Network Capacity Constraints," Post-Print hal-01007992, HAL.
    14. Kai Huang & Shabbir Ahmed, 2009. "The Value of Multistage Stochastic Programming in Capacity Planning Under Uncertainty," Operations Research, INFORMS, vol. 57(4), pages 893-904, August.
    15. Marshall L. Fisher, 2004. "Comments on ÜThe Lagrangian Relaxation Method for Solving Integer Programming ProblemsÝ," Management Science, INFORMS, vol. 50(12_supple), pages 1872-1874, December.
    16. John R. Birge, 1985. "Decomposition and Partitioning Methods for Multistage Stochastic Linear Programs," Operations Research, INFORMS, vol. 33(5), pages 989-1007, October.
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