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Dynamic Transmission Expansion Planning Using Adaptive Robust Optimization Under Uncertainties

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Proceedings of the 8th PURPLE MOUNTAIN FORUM on Smart Grid Protection and Control (PMF2023) (PMF 2023)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 1129))

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Abstract

The transmission expansion planning (TEP) problem is one of the perilous issues, which allows electricity transmission planners to design a cost-effective and reliable strategic model for the implementation of optimal transmission reinforcements in existing power grid networks. In this paper, a novel TEP model is proposed considering long- and short- term uncertain factors. The three-stage adaptive robust optimization (ARO) method deals with long-term uncertainties while prudently representing short-term uncertain parameters via scenarios. The formulated strategic scheme is elucidated through a modified decomposition algorithm that applies primal cutting planes and focuses on the subproblem feasible solution. The efficacy of the presented model is demonstrated through realistic case studies based on a 6-bus test system.

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Acknowledgement

This work is supported by the Science and Technology Project of State Grid, Zhejiang Electric Power Company (No. 5100-202119559A-0–5-SF).

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Correspondence to Zhen Wang .

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Rahim, S., Li, F., Wang, Z., Dai, P., Yang, H. (2024). Dynamic Transmission Expansion Planning Using Adaptive Robust Optimization Under Uncertainties. In: Xue, Y., Zheng, Y., Gómez-Expósito, A. (eds) Proceedings of the 8th PURPLE MOUNTAIN FORUM on Smart Grid Protection and Control (PMF2023). PMF 2023. Lecture Notes in Electrical Engineering, vol 1129. Springer, Singapore. https://doi.org/10.1007/978-981-99-9251-5_28

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  • DOI: https://doi.org/10.1007/978-981-99-9251-5_28

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-99-9250-8

  • Online ISBN: 978-981-99-9251-5

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