4.7 Article

Optimal Resource Allocation to Enhance Power Grid Resilience Against Hurricanes

Journal

IEEE TRANSACTIONS ON POWER SYSTEMS
Volume 38, Issue 3, Pages 2621-2629

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TPWRS.2022.3193133

Keywords

Resilience; Hurricanes; Resource management; Optimization; Risk management; Wind speed; Minimization; Disaster response; interdependencies; optimal resource allocation; resilience; system restoration

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This paper presents a two-step optimization strategy to maximize the resilience of the power distribution network against hurricanes. The strategy integrates a pre-disaster preparedness plan and a post-disaster resource re-allocation procedure. The resource allocation optimization problem is formulated as a Mixed-Integer Nonlinear Programming (MINP) problem. The proposed method is tested on the IEEE 70-node system and it shows improved performance in reducing failure probability and enhancing system recovery ability.
Optimal resource allocation is critical when maximizing the resilience of the electrical power distribution network against natural disasters. This paper presents a two-step optimization strategy that integrates a pre-disaster preparedness plan and a post-disaster resource re-allocation procedure to optimize the resilience of the power distribution network against hurricanes. Emergency resources are operationally interdependent, and it is these interdependencies that determine how the resources should be distributed to the critical loads in the network. This work uses the concept of the Human Readable Table (HRT) to relate the interdependencies among these resources. The resource allocation optimization is then formulated into a Mixed-Integer Nonlinear Programming (MINP) problem. The proposed method is tested on the IEEE 70-node system. The results show that this two-step procedure decreases the probability of failure for the critical nodes during the pre-hurricane stage and increases the system's ability to recover during the post-hurricane stage.

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