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Network-constrained thermal unit commitment fortexhybrid AC/DC transmission grids under wind power uncertainty

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  • Isuru, Mohasha
  • Hotz, Matthias
  • Gooi, H.B.
  • Utschick, Wolfgang

Abstract

The day-ahead energy and reserve management considering transmission restrictions and voltage security limits is a challenging task for large-scale power systems in the presence of volatile renewable energy sources. In this paper, a two-stage robust optimization model is proposed for the joint scheduling of energy and reserve for hybrid AC/DC transmission grids. The optimal schedule, including the commitment, power dispatch, and reserve allocations is computed subject to the feasibility of nonlinear AC and DC network constraints under a specified set of scenarios. Furthermore, the proposed decomposition approach renders the second stage (network security evaluations) into standard optimal power flow problems, which addresses the scalability issues observed with existing methods. A second-order cone relaxation is applied to nonlinear AC and DC network constraints to improve the computational tractability. In simulations, the proposed robust optimization model is illustrated using a recently proposed hybrid AC/DC transmission grid architecture with a specific topology. The results demonstrate the effective utilization of the grid capacity to accommodate more demand and renewable energy sources. This hybrid AC/DC transmission grid architecture induces exactness of the convex relaxation, supporting the validity of the optimal day-ahead schedule. The efficiency and computational performance of the proposed method is compared to the existing literature and the robustness is verified using an out-of-sample analysis.

Suggested Citation

  • Isuru, Mohasha & Hotz, Matthias & Gooi, H.B. & Utschick, Wolfgang, 2020. "Network-constrained thermal unit commitment fortexhybrid AC/DC transmission grids under wind power uncertainty," Applied Energy, Elsevier, vol. 258(C).
    • Handle: RePEc:eee:appene:v:258:y:2020:i:c:s0306261919317180
    DOI: 10.1016/j.apenergy.2019.114031
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    References listed on IDEAS

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    1. Gan, Wei & Ai, Xiaomeng & Fang, Jiakun & Yan, Mingyu & Yao, Wei & Zuo, Wenping & Wen, Jinyu, 2019. "Security constrained co-planning of transmission expansion and energy storage," Applied Energy, Elsevier, vol. 239(C), pages 383-394.
    2. Aghaei, Jamshid & Nikoobakht, Ahmad & Siano, Pierluigi & Nayeripour, Majid & Heidari, Alireza & Mardaneh, Mohammad, 2016. "Exploring the reliability effects on the short term AC security-constrained unit commitment: A stochastic evaluation," Energy, Elsevier, vol. 114(C), pages 1016-1032.
    3. G. Cobos, Noemi & Arroyo, José M. & Alguacil, Natalia & Street, Alexandre, 2018. "Network-constrained unit commitment under significant wind penetration: A multistage robust approach with non-fixed recourse," Applied Energy, Elsevier, vol. 232(C), pages 489-503.
    4. Morales-España, Germán & Ramírez-Elizondo, Laura & Hobbs, Benjamin F., 2017. "Hidden power system inflexibilities imposed by traditional unit commitment formulations," Applied Energy, Elsevier, vol. 191(C), pages 223-238.
    5. Kabir, M.N. & Mishra, Y. & Bansal, R.C., 2016. "Probabilistic load flow for distribution systems with uncertain PV generation," Applied Energy, Elsevier, vol. 163(C), pages 343-351.
    6. Azizipanah-Abarghooee, Rasoul & Golestaneh, Faranak & Gooi, Hoay Beng & Lin, Jeremy & Bavafa, Farhad & Terzija, Vladimir, 2016. "Corrective economic dispatch and operational cycles for probabilistic unit commitment with demand response and high wind power," Applied Energy, Elsevier, vol. 182(C), pages 634-651.
    7. Arcia-Garibaldi, Guadalupe & Cruz-Romero, Pedro & Gómez-Expósito, Antonio, 2018. "Future power transmission: Visions, technologies and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 94(C), pages 285-301.
    8. Staffell, Iain & Pfenninger, Stefan, 2016. "Using bias-corrected reanalysis to simulate current and future wind power output," Energy, Elsevier, vol. 114(C), pages 1224-1239.
    9. Furukakoi, Masahiro & Adewuyi, Oludamilare Bode & Matayoshi, Hidehito & Howlader, Abdul Motin & Senjyu, Tomonobu, 2018. "Multi objective unit commitment with voltage stability and PV uncertainty," Applied Energy, Elsevier, vol. 228(C), pages 618-623.
    10. Bai, Yang & Zhong, Haiwang & Xia, Qing & Kang, Chongqing & Xie, Le, 2015. "A decomposition method for network-constrained unit commitment with AC power flow constraints," Energy, Elsevier, vol. 88(C), pages 595-603.
    11. Fernández-Blanco, Ricardo & Arroyo, José M. & Alguacil, Natalia, 2014. "Consumer payment minimization under uniform pricing: A mixed-integer linear programming approach," Applied Energy, Elsevier, vol. 114(C), pages 676-686.
    12. Quan, Hao & Srinivasan, Dipti & Khambadkone, Ashwin M. & Khosravi, Abbas, 2015. "A computational framework for uncertainty integration in stochastic unit commitment with intermittent renewable energy sources," Applied Energy, Elsevier, vol. 152(C), pages 71-82.
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