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Data-adaptive robust unit commitment in the hybrid AC/DC power system

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  • Zhou, Bo
  • Ai, Xiaomeng
  • Fang, Jiakun
  • Yao, Wei
  • Zuo, Wenping
  • Chen, Zhe
  • Wen, Jinyu

Abstract

This paper proposes the data-adaptive robust optimization for the optimal unit commitment in the hybrid AC/DC power system. With the convexified branch flow model interconnecting the AC and DC power grid, the unit commitment problem in the hybrid AC/DC power system is formulated as a mixed-integer second-order cone programming. Considering the temporal and spatial correlations of multiple wind farms, the data-adaptive uncertainty set and the extreme scenarios are introduced to reformulate the robust optimization. The column-and-constraints generation algorithm is adopted to solve the multi-scenario problem. Case studies in the modified IEEE 14-bus system and the Henan provincial power system demonstrate the applicability of the proposed model. Comparative results with the pure AC power system show the improvement of the flexibility by DC interconnections. Both the operational cost and the times of generator startup/shutdown are reduced. The regulation capability of the DC lines can be fully utilized to cope with the uncertainties introduced by wind power.

Suggested Citation

  • Zhou, Bo & Ai, Xiaomeng & Fang, Jiakun & Yao, Wei & Zuo, Wenping & Chen, Zhe & Wen, Jinyu, 2019. "Data-adaptive robust unit commitment in the hybrid AC/DC power system," Applied Energy, Elsevier, vol. 254(C).
    • Handle: RePEc:eee:appene:v:254:y:2019:i:c:s0306261919314710
    DOI: 10.1016/j.apenergy.2019.113784
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