Integrated Transmission Network Planning by Considering Wind Power’s Uncertainty and Disasters

Yishan Shi (), Ruipeng Guo, Yuchen Tang, Yi Lin and Zhanxin Yang
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Yishan Shi: College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China
Ruipeng Guo: College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China
Yuchen Tang: State Grid Fujian Economic Research Institute, Fuzhou 350011, China
Yi Lin: State Grid Fujian Economic Research Institute, Fuzhou 350011, China
Zhanxin Yang: College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China

Energies, 2023, vol. 16, issue 14, 1-25

Abstract: The penetration of wind turbines and other power sources with strong uncertainty into the grid has increased in recent years. It has brought significant technical challenges to power systems’ operation. The volatility and intermittency of wind power increase the risk of insufficient transmission capacity of the lines. Therefore, the traditional deterministic planning methods for transmission grids are no longer fully applicable. On the other hand, the frequent disasters in recent years have posed a great threat to the power system, especially for the transmission grid. This requires the design of transmission lines with high design standards, such as skeleton networks, to withstand disasters. With the aim to address these problems, a bi-level integrated network planning model for the transmission grid is developed by considering wind power’s uncertainty and load guarantee under disasters. Chance constraints are used in the model to characterize wind power’s uncertainty, and a skeleton network is adopted to cope with disasters. Moreover, based on a convex relaxation method, the chance constraints are converted into the probabilistic inequalities to be solved. The proposed method is simulated in the IEEE 118 bus system, and the obtained network planning scheme is further analyzed in the scenario tests. And the result of the tests proves the validity and reasonableness of the proposed method.

Keywords: chance constraint; convex relaxation constraint; bi-level planning model; skeleton network planning; Gaussian mixture model; wind power’s uncertainty (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

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