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Lift-and-project MVEE based convex hull for robust SCED with wind power integration using historical data-driven modeling approach

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Listed:
  • Ding, Tao
  • Lv, Jiajun
  • Bo, Rui
  • Bie, Zhaohong
  • Li, Fangxing

Abstract

This paper presents an adjustable robust security constrained economic dispatch (SCED) model with wind power uncertainties. First, the scenario based adjustable robust SCED model is presented. It considers multiple scenarios from historical data as well as the spatial correlation among wind farms. Then, the proposed SCED model becomes an optimization problem with a large amount of constraints which is skillfully solved using a lift-and-project minimum volume enclosing ellipsoid (MVEE) based convex hull. Furthermore, the proposed model is transformed into a second order cone programming (SOCP) model by the use of participation factors to generate adjustable generation outputs and thus guarantee the energy balance. In order to further reduce the computational complexity, the inactive constraints reduction strategy is proposed to quickly eliminate inactive SOC security constraints before solving the model. Numerical results of IEEE 14-bus and 118-bus test systems as well as the practical Polish power systems with several wind farms show that the proposed model can achieve better economies. Moreover, more than 82% of security constraints are identified as inactive in various cases of the simulation, and the proposed inactive constraints reduction strategy is promising for improving the computational performance.

Suggested Citation

  • Ding, Tao & Lv, Jiajun & Bo, Rui & Bie, Zhaohong & Li, Fangxing, 2016. "Lift-and-project MVEE based convex hull for robust SCED with wind power integration using historical data-driven modeling approach," Renewable Energy, Elsevier, vol. 92(C), pages 415-427.
  • Handle: RePEc:eee:renene:v:92:y:2016:i:c:p:415-427
    DOI: 10.1016/j.renene.2016.01.001
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    References listed on IDEAS

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    1. Tao Ding & Qinglai Guo & Rui Bo & Hongbin Sun & Boming Zhang & Tian-en Huang, 2014. "A Static Voltage Security Region for Centralized Wind Power Integration—Part II: Applications," Energies, MDPI, vol. 7(1), pages 1-18, January.
    2. Tao Ding & Qinglai Guo & Rui Bo & Hongbin Sun & Boming Zhang, 2014. "A Static Voltage Security Region for Centralized Wind Power Integration—Part I: Concept and Method," Energies, MDPI, vol. 7(1), pages 1-24, January.
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    Citations

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    Cited by:

    1. Ji, Ling & Zhang, Bei-Bei & Huang, Guo-He & Xie, Yu-Lei & Niu, Dong-Xiao, 2018. "GHG-mitigation oriented and coal-consumption constrained inexact robust model for regional energy structure adjustment – A case study for Jiangsu Province, China," Renewable Energy, Elsevier, vol. 123(C), pages 549-562.
    2. Li, Yanbin & Zhang, Feng & Li, Yun & Wang, Yuwei, 2021. "An improved two-stage robust optimization model for CCHP-P2G microgrid system considering multi-energy operation under wind power outputs uncertainties," Energy, Elsevier, vol. 223(C).
    3. He, Xinran & Ding, Tao & Zhang, Xiaosheng & Huang, Yuhan & Li, Li & Zhang, Qinglei & Li, Fangxing, 2023. "A robust reliability evaluation model with sequential acceleration method for power systems considering renewable energy temporal-spatial correlation," Applied Energy, Elsevier, vol. 340(C).
    4. 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).
    5. Zhang, Yachao & Liu, Yan & Shu, Shengwen & Zheng, Feng & Huang, Zhanghao, 2021. "A data-driven distributionally robust optimization model for multi-energy coupled system considering the temporal-spatial correlation and distribution uncertainty of renewable energy sources," Energy, Elsevier, vol. 216(C).
    6. Qing, Ke & Du, Yuefang & Huang, Qi & Duan, Chao & Hu, Weihao, 2024. "Energy scheduling for microgrids with renewable energy sources considering an adjustable convex hull based uncertainty set," Renewable Energy, Elsevier, vol. 220(C).

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