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Hierarchical duality-based planning of transmission networks coordinating active distribution network operation

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  • Liu, Jia
  • Zeng, Peter Pingliang
  • Xing, Hao
  • Li, Yalou
  • Wu, Qiuwei

Abstract

The active distribution network becomes more stochastic due to high penetration of renewable energy sources, and it can transfer surplus power for transmission needs. If the distribution optimization problem collaborates with the conventional transmission expansion formulation, the coordination can also postpone the investment decisions for the transmission network, not only optimize the operation of the entire power system. In view of these, this paper presents a bi-level hierarchy transmission expansion formulation coordinating distribution networks. The upper level of the hierarchical decision-making framework corresponds to the objective and constraints of the transmission network, whereas the lower level relates to the distribution perspective. An approximation technique is used to make the constraints of the distribution network linear, which guarantees that the proposed bi-level program can be solved using the duality-based approach. Numerical tests carried out on two transmission-distribution integration networks demonstrate the effectiveness and high performance of the proposed hierarchical duality-based model to accommodate renewable energy. In addition, sensitivities of the transmission investment decisions are analysed in terms of externalities in transmission and distribution networks. Compared with conventional isolated optimization, results show that the total costs of T24D9 and T38D3 by the proposed hierarchical coordinated optimization can respectively reduce by 34.38 M$ and 382.23 M$. So the economic benefits are remarkable, and the proposed optimization is reasonable and valuable.

Suggested Citation

  • Liu, Jia & Zeng, Peter Pingliang & Xing, Hao & Li, Yalou & Wu, Qiuwei, 2020. "Hierarchical duality-based planning of transmission networks coordinating active distribution network operation," Energy, Elsevier, vol. 213(C).
    • Handle: RePEc:eee:energy:v:213:y:2020:i:c:s0360544220315966
    DOI: 10.1016/j.energy.2020.118488
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    Cited by:

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    2. Yin, Linfei & Luo, Shikui & Ma, Chenxiao, 2021. "Expandable depth and width adaptive dynamic programming for economic smart generation control of smart grids," Energy, Elsevier, vol. 232(C).
    3. Zhang, Jingrui & Li, Zhuoyun & Wang, Beibei, 2021. "Within-day rolling optimal scheduling problem for active distribution networks by multi-objective evolutionary algorithm based on decomposition integrating with thought of simulated annealing," Energy, Elsevier, vol. 223(C).

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