4.7 Article

Enhancing the Transmission Grid Resilience in Ice Storms by Optimal Coordination of Power System Schedule With Pre-Positioning and Routing of Mobile DC De-Icing Devices

Journal

IEEE TRANSACTIONS ON POWER SYSTEMS
Volume 34, Issue 4, Pages 2663-2674

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TPWRS.2019.2899496

Keywords

Transmission grid resilience; mobile DC de-icing device routing; power system scheduling; mixed-integer second-order cone programming; nested column-and-constraint algorithm

Funding

  1. National Natural Science Foundation of China [51707070]
  2. China Postdoctoral Science Foundation [2016M590693]

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This paper proposes a resilience enhancement strategy for power transmission system against ice storms by the optimal coordination of power system schedule with the pre-positioning and routing of mobile dc de-icing devices (MDIDs). A two-stage robust optimization model is established to accommodate the variable ice thickness on transmission lines. The first stage coordinates the pre-positioned MDIDs and unit commitment in day-ahead. These decisions, which are based on a robust approach, can accommodate the variable ice thickness in which the coordinated real-time schedule would always he feasible with respect to day-ahead decisions. At the second stage, the real-time operation, which integrates the power system dispatch, de-icing schedule, and MDID routing, is scheduled according to the real-time ice thickness. Auxiliary variables are adopted to convert the proposed nonconvex nonlinear model to a mixed-integer second-order cone programming (MISOCP) problem. The nested column-and-constraint generation algorithm is utilized to solve the two-stage robust MISOCP problem. Several computational enhancement strategies including Lagrangian relaxation are proposed to improve the performance of the proposed resilience enhancement strategy. Numerical results for an integrated 6-bus 6-node electricity-road network and a real-world example employed in China show the effectiveness of the proposed model and solution technique for enhancing the transmission grid resilience.

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