Transmission expansion planning with optimal transmission switching considering uncertain n-k contingency and renewables

This paper presents a novel model for transmission expansion planning (TEP) with optimal transmission switching (OTS) considering uncertain N-k contingency, renewables and loads. In the proposed approach, ambiguity set and budget uncertainty set are utilized to simultaneously characterize three types of uncertainties in power system: (1) wind power output; (2) load demands; (3) the status and probability distribution of generation and transmission N-k contingency. Accordingly, the optimal expansion plan and OTS can be obtained through a three-level model to guarantee the safety and economy of power system in the worst-case of wind power, load demand and N-k contingency. A decomposition algorithm based on benders decomposition is developed to efficiently solve the model. Cases studies on the revised IEEE 30-bus test system demonstrate that (1) the optimal expansion plan can be greatly affected by the proposed uncertainty sets, (2) the total costs can be effectively reduced by considering optimal transmission switching and (3) the decomposition method can efficiently solve the proposed TEP model. (c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer-review under responsibility of the scientific committee of the 2021 The 2nd International Conference on Power Engineering, ICPE, 2021.

Automated summary

This paper presents a novel model for transmission expansion planning with optimal transmission switching considering uncertain N-k contingency, renewables, and loads. The proposed approach utilizes ambiguity set and budget uncertainty set to simultaneously characterize the uncertainties in wind power output, load demands, and the status of generation and transmission N-k contingency. Through a three-level model, the optimal expansion plan and transmission switching can be obtained to ensure the safety and economy of the power system in worst-case scenarios. A decomposition algorithm based on benders decomposition is developed to efficiently solve the model. Case studies on the revised IEEE 30-bus test system demonstrate the effectiveness of the proposed approach in determining the optimal expansion plan and reducing total costs.