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Active robust optimization for wind integrated power system economic dispatch considering hourly demand response

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  • Wang, Xu
  • Jiang, Chuanwen
  • Li, Bosong

Abstract

Due to dramatically increased uncertainties caused by wind power (WP) integration and price responsive demand, economic dispatch (ED) in a day-ahead market faces new challenges. With the involvement of price responsive demand response (DR), independent system operator (ISO) has to adapt to the changes of both nodal prices and loads under different WP conditions. Moreover, here the changeable nodal prices are determined by both power generation and load not using a simple deterministic mathematical function. The robustness of dispatch strategies can be enhanced through proper demand side management. Motivated by these, we propose a novel active robust optimization dispatch (AROD) model in this paper. The proposed model amalgamates robust optimization (RO) with dynamic optimization (DO) to reveal the effects of price responsive DR, while considering all possible WP conditions. We present extensive numerical case studies on the modified IEEE 30-bus system and IEEE 118-bus system. Computational results demonstrate the effectiveness of the proposed AROD model for the secure and economic operation of the power system under various uncertainties in a day-ahead market.

Suggested Citation

  • Wang, Xu & Jiang, Chuanwen & Li, Bosong, 2016. "Active robust optimization for wind integrated power system economic dispatch considering hourly demand response," Renewable Energy, Elsevier, vol. 97(C), pages 798-808.
    • Handle: RePEc:eee:renene:v:97:y:2016:i:c:p:798-808
    DOI: 10.1016/j.renene.2016.06.035
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    References listed on IDEAS

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    1. Dimitris Bertsimas & Melvyn Sim, 2004. "The Price of Robustness," Operations Research, INFORMS, vol. 52(1), pages 35-53, February.
    2. George B. Dantzig, 2004. "Linear Programming Under Uncertainty," Management Science, INFORMS, vol. 50(12_supple), pages 1764-1769, December.
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    Cited by:

    1. Zhang, Jingrui & Zhu, Xiaoqing & Chen, Tengpeng & Yu, Yanlin & Xue, Wendong, 2020. "Improved MOEA/D approach to many-objective day-ahead scheduling with consideration of adjustable outputs of renewable units and load reduction in active distribution networks," Energy, Elsevier, vol. 210(C).
    2. Wang, Zhimin & Gu, Chenghong & Li, Furong, 2018. "Flexible operation of shared energy storage at households to facilitate PV penetration," Renewable Energy, Elsevier, vol. 116(PA), pages 438-446.
    3. Kotur, Dimitrije & Đurišić, Željko, 2017. "Optimal spatial and temporal demand side management in a power system comprising renewable energy sources," Renewable Energy, Elsevier, vol. 108(C), pages 533-547.
    4. Jiang, Yibo & Xu, Jian & Sun, Yuanzhang & Wei, Congying & Wang, Jing & Ke, Deping & Li, Xiong & Yang, Jun & Peng, Xiaotao & Tang, Bowen, 2017. "Day-ahead stochastic economic dispatch of wind integrated power system considering demand response of residential hybrid energy system," Applied Energy, Elsevier, vol. 190(C), pages 1126-1137.

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