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Robust Day-Ahead Scheduling of Electricity and Natural Gas Systems via a Risk-Averse Adjustable Uncertainty Set Approach

Author

Listed:
  • Li Yao

    (School of Electrical Engineering, Xi’an Jiaotong University, Xi’an 710049, China)

  • Xiuli Wang

    (School of Electrical Engineering, Xi’an Jiaotong University, Xi’an 710049, China)

  • Tao Qian

    (School of Electrical Engineering, Xi’an Jiaotong University, Xi’an 710049, China)

  • Shixiong Qi

    (School of Electrical Engineering, Xi’an Jiaotong University, Xi’an 710049, China)

  • Chengzhi Zhu

    (State Grid Zhejiang Electric Power Co., LTD., Hang Zhou 310007, China)

Abstract

The requirement for energy sustainability drives the development of renewable energy technologies and gas-fired power generation. The increasing installation of gas-fired units significantly intensifies the interdependency between the electricity system and natural gas system. The joint scheduling of electricity and natural gas systems has become an attractive option for improving energy efficiency. This paper proposes a robust day-ahead scheduling model for electricity and natural gas system, which minimizes the total cost including fuel cost, spinning reserve cost and cost of operational risk while ensuring the feasibility for all scenarios within the uncertainty set. Different from the conventional robust optimization with predefined uncertainty set, a new approach with risk-averse adjustable uncertainty set is proposed in this paper to mitigate the conservatism. Furthermore, the Wasserstein–Moment metric is applied to construct ambiguity sets for computing operational risk. The proposed scheduling model is solved by the column-and-constraint generation method. The effectiveness of the proposed approach is tested on a 6-bus test system and a 118-bus system.

Suggested Citation

  • Li Yao & Xiuli Wang & Tao Qian & Shixiong Qi & Chengzhi Zhu, 2018. "Robust Day-Ahead Scheduling of Electricity and Natural Gas Systems via a Risk-Averse Adjustable Uncertainty Set Approach," Sustainability, MDPI, vol. 10(11), pages 1-16, October.
    • Handle: RePEc:gam:jsusta:v:10:y:2018:i:11:p:3848-:d:177862
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    References listed on IDEAS

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    Cited by:

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    2. Biyun Chen & Yanni Chen & Bin Li & Yun Zhu & Chi Zhang, 2022. "An Optimal Dispatching Model for Integrated Energy Microgrid Considering the Reliability Principal–Agent Contract," Sustainability, MDPI, vol. 14(13), pages 1-16, June.
    3. Riepin, Iegor & Schmidt, Matthew & Baringo, Luis & Müsgens, Felix, 2022. "Adaptive robust optimization for European strategic gas infrastructure planning," Applied Energy, Elsevier, vol. 324(C).
    4. Zhengping Liu & Wang Zhang & Hongxian Liu & Guohe Huang & Jiliang Zhen & Xin Qi, 2019. "Characterization of Renewable Energy Utilization Mode for Air-Environmental Quality Improvement through an Inexact Factorial Optimization Approach," Sustainability, MDPI, vol. 11(8), pages 1-19, April.

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