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Security constrained co-planning of transmission expansion and energy storage

Author

Listed:
  • Gan, Wei
  • Ai, Xiaomeng
  • Fang, Jiakun
  • Yan, Mingyu
  • Yao, Wei
  • Zuo, Wenping
  • Wen, Jinyu

Abstract

This paper presents a security-constrained co-planning of transmission line expansion and energy storage with high penetration of wind power. The energy storage can not only improve the accommodation of renewable generation but also help to mitigate the emergency overflow under the post-contingency state. Also, the adjustment capabilities of the wind farms are considered, and the risk of excessive wind curtailment under the post-contingency state is assessed quantitatively. The coordinated multistage corrective control strategy for the battery storage, the pumped storage, thermal generators, and wind farms is studied. The mixed-integer linear programming problem based on the proposed corrective control strategy has been formulated. The Benders decomposition algorithm is introduced to divide the co-planning problem into one master problem and two sub-problems. In the master problem, the system is operating under normal conditions, so the security constraints are not considered. It minimizes the sum of the investment cost of newly built facilities and the operational cost. In the sub-problems, the corrective control during different post-contingency stages is formulated, minimizing the risk costs under fault conditions. The two-step technique is developed to generate the Benders cuts from the mixed-integer linear programming sub-problems, and return to the master problem. The real-world power system in Gansu, China is studied to validate the applicability and scalability of the proposed model and solution technique. The results denote that the co-planning model with security constraints is profitable in the real power system, with savings of 25% for the newly built transmission lines and a 5.5% reduction in total cost.

Suggested Citation

  • Gan, Wei & Ai, Xiaomeng & Fang, Jiakun & Yan, Mingyu & Yao, Wei & Zuo, Wenping & Wen, Jinyu, 2019. "Security constrained co-planning of transmission expansion and energy storage," Applied Energy, Elsevier, vol. 239(C), pages 383-394.
  • Handle: RePEc:eee:appene:v:239:y:2019:i:c:p:383-394
    DOI: 10.1016/j.apenergy.2019.01.192
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    10. Xie, Rui & Wei, Wei & Li, Mingxuan & Dong, ZhaoYang & Mei, Shengwei, 2023. "Sizing capacities of renewable generation, transmission, and energy storage for low-carbon power systems: A distributionally robust optimization approach," Energy, Elsevier, vol. 263(PA).
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    12. Dany H. Huanca & Djalma M. Falcão & Murilo E. C. Bento, 2024. "Transmission Expansion Planning Considering Storage, Flexible AC Transmission System, Losses, and Contingencies to Integrate Wind Power," Energies, MDPI, vol. 17(7), pages 1-23, April.
    13. Panda, Deepak Kumar & Das, Saptarshi, 2021. "Economic operational analytics for energy storage placement at different grid locations and contingency scenarios with stochastic wind profiles," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    14. Gan, Wei & Yan, Mingyu & Yao, Wei & Guo, Jianbo & Ai, Xiaomeng & Fang, Jiakun & Wen, Jinyu, 2021. "Decentralized computation method for robust operation of multi-area joint regional-district integrated energy systems with uncertain wind power," Applied Energy, Elsevier, vol. 298(C).
    15. Wu, Yunyun & Fang, Jiakun & Ai, Xiaomeng & Xue, Xizhen & Cui, Shichang & Chen, Xia & Wen, Jinyu, 2023. "Robust co-planning of AC/DC transmission network and energy storage considering uncertainty of renewable energy," Applied Energy, Elsevier, vol. 339(C).
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    17. Zhao, Bo & Ren, Junzhi & Chen, Jian & Lin, Da & Qin, Ruwen, 2020. "Tri-level robust planning-operation co-optimization of distributed energy storage in distribution networks with high PV penetration," Applied Energy, Elsevier, vol. 279(C).
    18. Liao, Shiwu & Yao, Wei & Han, Xingning & Fang, Jiakun & Ai, Xiaomeng & Wen, Jinyu & He, Haibo, 2019. "An improved two-stage optimization for network and load recovery during power system restoration," Applied Energy, Elsevier, vol. 249(C), pages 265-275.
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    20. 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).
    21. Savelli, Iacopo & De Paola, Antonio & Li, Furong, 2020. "Ex-ante dynamic network tariffs for transmission cost recovery," Applied Energy, Elsevier, vol. 258(C).

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