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Coordinated scheduling of generators and tie lines in multi-area power systems under wind energy uncertainty

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  • Zhang, Heng
  • Hu, Xiao
  • Cheng, Haozhong
  • Zhang, Shenxi
  • Hong, Shaoyun
  • Gu, Qingfa

Abstract

A novel stochastic multi-area unit commitment (MAUC) framework is proposed to coordinate scheduling of generators and tie lines. In consideration of the randomness and volatility characteristics of wind energy, a worst-case based scenario selection method (SSM) based on the peak and valley shaving of the system, the ramping-up/down rates of net load, and the dispersion of uncertainty factors is presented to reduce the number of scenarios and improve the robustness of unit commitment (UC) schemes. Regarding the balance of efficiency and flexibility of tie-line scheduling, tie-line operation modes are established on the basis of the tie-line load rate (TLLR). Besides, the number of reversals of tie-line power flow directions during the entire scheduling period is also modeled. By linearizing the tie-line operation modes’ equations, the MAUC can be converted into a mixed-integer linear programming (MILP) formulation. Case studies show that more wind energy can be consumed by connecting power systems through tie lines and coordinating scheduling of generators and tie lines. Expected energy not supplied (EENS) of scenario reduction techniques based on the clustering method, i.e. k-means, Gaussian mixture model (GMM) and Fuzzy C-means (FCM), are 147%, 38%, and 130% higher than that of the SSM.

Suggested Citation

  • Zhang, Heng & Hu, Xiao & Cheng, Haozhong & Zhang, Shenxi & Hong, Shaoyun & Gu, Qingfa, 2021. "Coordinated scheduling of generators and tie lines in multi-area power systems under wind energy uncertainty," Energy, Elsevier, vol. 222(C).
    • Handle: RePEc:eee:energy:v:222:y:2021:i:c:s036054422100178x
    DOI: 10.1016/j.energy.2021.119929
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    References listed on IDEAS

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    5. Kraft, Emil & Russo, Marianna & Keles, Dogan & Bertsch, Valentin, 2023. "Stochastic optimization of trading strategies in sequential electricity markets," European Journal of Operational Research, Elsevier, vol. 308(1), pages 400-421.
    6. Russo, Marianna & Kraft, Emil & Bertsch, Valentin & Keles, Dogan, 2022. "Short-term risk management of electricity retailers under rising shares of decentralized solar generation," Energy Economics, Elsevier, vol. 109(C).
    7. Han, Fengwu & Zeng, Jianfeng & Lin, Junjie & Zhao, Yunlong & Gao, Chong, 2023. "A stochastic hierarchical optimization and revenue allocation approach for multi-regional integrated energy systems based on cooperative games," Applied Energy, Elsevier, vol. 350(C).
    8. Ye, Lin & Jin, Yifei & Wang, Kaifeng & Chen, Wei & Wang, Fei & Dai, Binhua, 2023. "A multi-area intra-day dispatch strategy for power systems under high share of renewable energy with power support capacity assessment," Applied Energy, Elsevier, vol. 351(C).

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