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Security-constrained bi-level economic dispatch model for integrated natural gas and electricity systems considering wind power and power-to-gas process

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  • Li, Guoqing
  • Zhang, Rufeng
  • Jiang, Tao
  • Chen, Houhe
  • Bai, Linquan
  • Li, Xiaojing

Abstract

Worldwide natural gas consumption has increased significantly, especially for power generation in electricity systems with the gas-to-power (G2P) process of natural gas fired units. Supply for both natural gas and electricity systems should be dispatched economically and simultaneously due to their firm interconnection. This paper proposes a security-constrained bi-level economic dispatch (ED) model for integrated natural gas and electricity systems considering wind power and power-to-gas (P2G) process. The upper level is formulated as an ED optimization model for electricity system, while the lower level is an optimal allocation problem for natural gas system. Natural gas system is modeled in detail. In addition, the security constraints and coupling constraints for the integrated energy systems are considered. The objective function is to minimize the total production cost of electricity and natural gas. The lower model is converted and added into the upper model as Karush-Kuhn-Tucher (KKT) optimality conditions, thus the bi-level optimization model is transformed into a mix-integer linear programming (MILP) formulation. Numerical case studies on the PJM-5bus system integrated with a seven-node gas system and IEEE 118-bus system integrated with a modified Belgian high-calorific gas system demonstrate the effectiveness of the proposed bi-level ED model.

Suggested Citation

  • Li, Guoqing & Zhang, Rufeng & Jiang, Tao & Chen, Houhe & Bai, Linquan & Li, Xiaojing, 2017. "Security-constrained bi-level economic dispatch model for integrated natural gas and electricity systems considering wind power and power-to-gas process," Applied Energy, Elsevier, vol. 194(C), pages 696-704.
    • Handle: RePEc:eee:appene:v:194:y:2017:i:c:p:696-704
    DOI: 10.1016/j.apenergy.2016.07.077
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    References listed on IDEAS

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    1. Škugor, Branimir & Deur, Joško, 2016. "A bi-level optimisation framework for electric vehicle fleet charging management," Applied Energy, Elsevier, vol. 184(C), pages 1332-1342.
    2. Qadrdan, Meysam & Chaudry, Modassar & Jenkins, Nick & Baruah, Pranab & Eyre, Nick, 2015. "Impact of transition to a low carbon power system on the GB gas network," Applied Energy, Elsevier, vol. 151(C), pages 1-12.
    3. Jirutitijaroen, Panida & Kim, Sujin & Kittithreerapronchai, Oran & Prina, José, 2013. "An optimization model for natural gas supply portfolios of a power generation company," Applied Energy, Elsevier, vol. 107(C), pages 1-9.
    4. Feijoo, Felipe & Das, Tapas K., 2015. "Emissions control via carbon policies and microgrid generation: A bilevel model and Pareto analysis," Energy, Elsevier, vol. 90(P2), pages 1545-1555.
    5. Chaudry, Modassar & Jenkins, Nick & Qadrdan, Meysam & Wu, Jianzhong, 2014. "Combined gas and electricity network expansion planning," Applied Energy, Elsevier, vol. 113(C), pages 1171-1187.
    6. DE WOLF, Daniel & SMEERS, Yves, 2000. "The gas transmission problem solved by an extension of the simplex algorithm," LIDAM Reprints CORE 1489, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    7. Ju, Liwei & Tan, Zhongfu & Yuan, Jinyun & Tan, Qingkun & Li, Huanhuan & Dong, Fugui, 2016. "A bi-level stochastic scheduling optimization model for a virtual power plant connected to a wind–photovoltaic–energy storage system considering the uncertainty and demand response," Applied Energy, Elsevier, vol. 171(C), pages 184-199.
    8. Bai, Linquan & Li, Fangxing & Cui, Hantao & Jiang, Tao & Sun, Hongbin & Zhu, Jinxiang, 2016. "Interval optimization based operating strategy for gas-electricity integrated energy systems considering demand response and wind uncertainty," Applied Energy, Elsevier, vol. 167(C), pages 270-279.
    9. Cui, Hantao & Li, Fangxing & Hu, Qinran & Bai, Linquan & Fang, Xin, 2016. "Day-ahead coordinated operation of utility-scale electricity and natural gas networks considering demand response based virtual power plants," Applied Energy, Elsevier, vol. 176(C), pages 183-195.
    10. Daniel De Wolf & Yves Smeers, 2000. "The Gas Transmission Problem Solved by an Extension of the Simplex Algorithm," Management Science, INFORMS, vol. 46(11), pages 1454-1465, November.
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