Flood-aware Optimal Power Flow for Proactive Day-ahead Transmission Substation Hardening

TL;DR

This paper introduces a flood-aware optimal power flow model that proactively schedules substation protection measures like tiger dams to enhance grid resilience against flooding, demonstrated on a small test system.

Contribution

It presents a novel stochastic mixed-integer programming approach for proactive substation protection scheduling before floods, improving power grid resilience.

Findings

Model effectively identifies critical substations for protection

Proactive scheduling reduces potential damage costs

Promising results on a 6-bus test system

Abstract

Power system components, particularly electrical substations, may be severely damaged due to flooding, resulting in prolonged power outages and resilience degradation. This problem is more severe in low-elevated regions such as Louisiana. Protective operational actions such as placing tiger dams around substations before flooding can reduce substation vulnerability, damage costs, and energy not supplied cost, thus enhancing power grid resilience. This paper proposes a stochastic mixed-integer programming model for protecting transmission substations one day before flood events using tiger dams. A flood-aware optimal power flow problem is formulated for transmission system operators with respect to the protected/unprotected status of substations. The formulated model aims to identify critical substations whose protection maximizes grid resilience. The output of the proposed model is a day-ahead crew team schedule for installing tiger dams on transmission substations. The effectiveness of the proposed model is evaluated on a 6-bus system, and promising results are obtained.