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Regular Paper | Open Access

Resilience-oriented Transmission Expansion Planning with Optimal Transmission Switching Under Typhoon Weather

Yang Yuan1Heng Zhang1( )Haozhong Cheng1Zheng Wang2
Key Laboratory of Control of Power Transmission and Conversion, Ministry of Education, Electrical Engineering Department, Shanghai Jiao Tong University, Shanghai, China
State Grid East China Branch, Shanghai, China
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Abstract

This paper presents resilience-oriented transmission expansion planning (RTEP) with optimal transmission switching (OTS) model under typhoon weather. The proposed model carefully considers the uncertainty of component vulnerability by constructing a typhoon-related box uncertainty set where component failure rate varies within a range closely related with typhoon intensity. Accordingly, a min-max-min model is developed to enhance transmission network resilience, where the upper level minimizes transmission lines investment, the middle level searches for the probability distribution of failure status leading to max worst-case expected load-shedding (WCEL) under typhoon, and the lower level optimizes WCEL by economic dispatch (ED) and OTS. A nested decomposition algorithm based on benders decomposition is developed to solve the model. Case studies of modified IEEE 30-bus and 261-bus system of a Chinese region illustrate that: a) the proposed RTEP method can enhance resilience of transmission network with less investment than widely used RTEP method based on attacker and defender (DAD) model, b) the influence of OTS on RTEP is closely related with contingency severity and system scale and c) the RTEP model can be efficiently solved even in a large-scale system.

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CSEE Journal of Power and Energy Systems
Pages 129-138
Cite this article:
Yuan Y, Zhang H, Cheng H, et al. Resilience-oriented Transmission Expansion Planning with Optimal Transmission Switching Under Typhoon Weather. CSEE Journal of Power and Energy Systems, 2024, 10(1): 129-138. https://doi.org/10.17775/CSEEJPES.2021.07840

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Received: 20 October 2021
Revised: 04 February 2022
Accepted: 21 February 2022
Published: 12 October 2022
© 2021 CSEE.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).

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