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Stochastic planning of electricity and gas networks: An asynchronous column generation approach

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  • Saldarriaga-Cortés, Carlos
  • Salazar, Harold
  • Moreno, Rodrigo
  • Jiménez-Estévez, Guillermo

Abstract

Planning networks within a multi-stage stochastic framework is becoming critical for improving the economic performance of investment decisions against the present levels of uncertainty. This problem, however, has been proved extremely challenging to be solved on real networks, especially when considering the interactions among various energy vectors. In this context, this paper proposes the use of Dantzig-Wolfe decomposition and parallel asynchronous column generation to solve a multi-stage stochastic planning of an integrated power and natural gas system, including non-linear effects of gas compressors reformulated in a mixed integer linear programming fashion. We compare the computational performance of the proposed approach against two alternatives: a parallel synchronous column generation approach and the counterfactual, monolithic approach, where the mixed integer linear program (without decomposition) is directly solved by a commercial solver. Our sources of long-term uncertainty are the locations and volumes of (i) new renewable generation (which may depend on policy objectives, regulatory incentives, etc. that are constantly evolving) and (ii) new demands. The model also ensures that the planned energy infrastructure can effectively be operated reliably against a large array of operating conditions originated by high variability of renewable generation outputs, multiple demand levels and hydro inflows. Through various case studies, we discuss and demonstrate the importance of stochastic and integrated planning of electricity and natural gas systems along with the benefits of asynchronous algorithms and decomposition techniques that can be parallelized.

Suggested Citation

  • Saldarriaga-Cortés, Carlos & Salazar, Harold & Moreno, Rodrigo & Jiménez-Estévez, Guillermo, 2019. "Stochastic planning of electricity and gas networks: An asynchronous column generation approach," Applied Energy, Elsevier, vol. 233, pages 1065-1077.
    • Handle: RePEc:eee:appene:v:233-234:y:2019:i::p:1065-1077
    DOI: 10.1016/j.apenergy.2018.09.148
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    References listed on IDEAS

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    1. 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.
    2. Saldarriaga-C., Carlos A. & Salazar, Harold, 2016. "Security of the Colombian energy supply: The need for liquefied natural gas regasification terminals for power and natural gas sectors," Energy, Elsevier, vol. 100(C), pages 349-362.
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    Cited by:

    1. Devine, Mel T. & Russo, Marianna, 2019. "Liquefied natural gas and gas storage valuation: Lessons from the integrated Irish and UK markets," Applied Energy, Elsevier, vol. 238(C), pages 1389-1406.
    2. Ji, Ling & Zhang, Beibei & Huang, Guohe & Wang, Peng, 2020. "A novel multi-stage fuzzy stochastic programming for electricity system structure optimization and planning with energy-water nexus - A case study of Tianjin, China," Energy, Elsevier, vol. 190(C).
    3. Farrokhifar, Meisam & Nie, Yinghui & Pozo, David, 2020. "Energy systems planning: A survey on models for integrated power and natural gas networks coordination," Applied Energy, Elsevier, vol. 262(C).
    4. Wakui, Tetsuya & Hashiguchi, Moe & Yokoyama, Ryohei, 2021. "Structural design of distributed energy networks by a hierarchical combination of variable- and constraint-based decomposition methods," Energy, Elsevier, vol. 224(C).
    5. Dranka, Géremi Gilson & Ferreira, Paula & Vaz, A. Ismael F., 2021. "A review of co-optimization approaches for operational and planning problems in the energy sector," Applied Energy, Elsevier, vol. 304(C).
    6. Wakui, Tetsuya & Hashiguchi, Moe & Yokoyama, Ryohei, 2020. "A near-optimal solution method for coordinated operation planning problem of power- and heat-interchange networks using column generation-based decomposition," Energy, Elsevier, vol. 197(C).
    7. Wei, Congying & Wu, Qiuwei & Xu, Jian & Sun, Yuanzhang & Jin, Xiaolong & Liao, Siyang & Yuan, Zhiyong & Yu, Li, 2020. "Distributed scheduling of smart buildings to smooth power fluctuations considering load rebound," Applied Energy, Elsevier, vol. 276(C).
    8. Masoud Khatibi & Abbas Rabiee & Amir Bagheri, 2023. "Integrated Electricity and Gas Systems Planning: New Opportunities, and a Detailed Assessment of Relevant Issues," Sustainability, MDPI, vol. 15(8), pages 1-32, April.
    9. Chen, Cong & Sun, Hongbin & Shen, Xinwei & Guo, Ye & Guo, Qinglai & Xia, Tian, 2019. "Two-stage robust planning-operation co-optimization of energy hub considering precise energy storage economic model," Applied Energy, Elsevier, vol. 252(C), pages 1-1.
    10. Martínez Sánchez, Ana M. & Saldarriaga Cortés, Carlos A. & Salazar, Harold, 2021. "An optimal coordination of seasonal energy storages: A holistic approach to ensure energy adequacy and cost efficiency," Applied Energy, Elsevier, vol. 290(C).
    11. Fernández, Mauricio & Muñoz, Francisco D. & Moreno, Rodrigo, 2020. "Analysis of imperfect competition in natural gas supply contracts for electric power generation: A closed-loop approach," Energy Economics, Elsevier, vol. 87(C).
    12. Hosseini, Seyed Hamid Reza & Allahham, Adib & Walker, Sara Louise & Taylor, Phil, 2020. "Optimal planning and operation of multi-vector energy networks: A systematic review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).

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