US 12,423,624 B2
Ensemble forecast storm damage response system for critical infrastructure
Paul R. Hynes, Jupiter, FL (US); Matthew R. Moxley, Palm City, FL (US); Jason S. Price, Palm Beach Gardens, FL (US); Thomas W. Gwaltney, Palm Coast, FL (US); Iliana M. Rentz, West Palm Beach, FL (US); and Jose Luis Medina, Jupiter, FL (US)
Assigned to FLORIDA POWER & LIGHT COMPANY, Juno Beach, FL (US)
Filed by Florida Power & Light Company, Juno Beach, FL (US)
Filed on Jun. 3, 2022, as Appl. No. 17/831,752.
Application 17/831,752 is a continuation in part of application No. 15/948,489, filed on Apr. 9, 2018, granted, now 11,361,236.
Prior Publication US 2022/0292408 A1, Sep. 15, 2022
This patent is subject to a terminal disclaimer.
Int. Cl. G06N 20/20 (2019.01); G01W 1/10 (2006.01); G06F 16/25 (2019.01); G06N 7/01 (2023.01)
CPC G06N 20/20 (2019.01) [G01W 1/10 (2013.01); G06F 16/25 (2019.01); G06N 7/01 (2023.01)] 22 Claims
OG exemplary drawing
 
1. A storm damage response system comprising:
a storm ensemble database configured to store a plurality of ensemble forecast models associated with respective potential storm paths of a given storm across a geographic area, as provided from and updated by a weather forecasting service;
an inventory database configured to store inventory data associated with location and characteristics associated with power-providing equipment in the geographic area; and
a storm damage model control system configured to implement a storm damage model algorithm to generate a predictive storm response plan comprising estimated resources for providing recovery from storm damage impact with respect to the power-providing equipment, the storm damage model algorithm being configured to generate a probabilistic model associated with operational failure of the power-providing equipment relative to at least one of time, cost, resource availability, and storm severity constraints for each of the plurality of ensemble forecast models based on the inventory data and to calculate a statistical impact value indicative of a cost-based resource allocation estimate associated with the probabilistic model based on an aggregate of a plurality of iterative probabilistic simulations for the probabilistic model associated with the respective one of the plurality of ensemble forecast models, the storm damage model control system being configured to generate the predictive storm response plan based on a relative statistical impact value of the probabilistic model of each of the plurality of ensemble forecast models.