Stochastic Pre-hurricane Restoration Planning for Electric Power Systems Infrastructure

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Daniel Felix Ritchie School of Engineering and Computer Science, Electrical and Computer Engineering


Maintenance engineering, Hurricanes, Stochastic processes, Random variables, Planning, Substations


Proactive preparedness to cope with emergencies, especially those of nature origins, significantly improves the resilience and minimizes the restoration cost of electric power systems. In this paper, a proactive resource allocation model for repair and restoration of potential damages to the power system infrastructure located on the path of an upcoming hurricane is proposed. The objective is to develop an efficient framework for system operators to minimize potential damages to power system components in a cost-effective manner. The problem is modeled as a stochastic integer program with complete recourse. The large-scale mixed-integer equivalence of the original model is solved by the Benders' decomposition method to handle computation burden. The standard IEEE 118-bus system is employed to demonstrate the effectiveness of the proposed model and further discuss its merits.

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