Dynamic contingency avoidance and mitigation system
First Claim
1. A dynamic contingency avoidance and mitigation system for determining and allocating the distribution, consumption, and supply of a resource within an infrastructure including a plurality of facilities, comprising:
- one or more processors, each having respective communication interfaces to receive infrastructure network data descriptive of said resource from said plurality of facilities, said infrastructure network data comprising information corresponding to the consumption and supply of said resource at the plurality of facilities;
wherein said one or more processors are further configured to perform sequential Monte Carlo analysis using a topological model of the infrastructure on determined mean time between failure (MTBF) and mean time to repair (MTTR) to provide reliability statistics of the infrastructure in real time and predicted future time periods;
one or more software applications, operatively coupled to and at least partially controlling said one or more processors, said one or more software applications comprising;
a characterizer for generating characterized infrastructure network data based on at least a portion of said infrastructure network data anda predictor for;
generating predictive infrastructure network data based on at least a portion of said infrastructure network data anddetermining one or more proposed enhancements in said infrastructure to provide improved infrastructure performance based at least in part on cost information corresponding to said one or more proposed enhancements;
wherein the one or more software applications include a machine learning engine;
a display, coupled to said one or more processors, for visually presenting a depiction of at least a portion of said infrastructure and said one or more proposed enhancements, based on at least one of;
said characterized infrastructure network data and said predictive infrastructure network data; and
one or more distribution controllers in communication with the one or more processors, to distribute the resource to or from the plurality of facilities based on at least one of;
said characterized infrastructure network data and said predictive infrastructure network data.
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Accused Products
Abstract
The disclosed subject matter provides systems and methods for allocating resources within an infrastructure, such as an electrical grid, in response to changes to inputs and output demands on the infrastructure, such as energy sources and sinks. A disclosed system includes one or more processors, each having respective communication interfaces to receive data from the infrastructure, the data including infrastructure network data, one or more software applications, operatively coupled to and at least partially controlling the one or more processors, to process and characterize the infrastructure network data; and a display, coupled to the one or more processors, for visually presenting a depiction of at least a portion of the infrastructure including any changes in condition thereof, and one or more controllers in communication with the one or more processors, to manage processing of the resource, wherein the resource is obtained and/or distributed based on the characterization of the real time infrastructure data.
156 Citations
33 Claims
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1. A dynamic contingency avoidance and mitigation system for determining and allocating the distribution, consumption, and supply of a resource within an infrastructure including a plurality of facilities, comprising:
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one or more processors, each having respective communication interfaces to receive infrastructure network data descriptive of said resource from said plurality of facilities, said infrastructure network data comprising information corresponding to the consumption and supply of said resource at the plurality of facilities; wherein said one or more processors are further configured to perform sequential Monte Carlo analysis using a topological model of the infrastructure on determined mean time between failure (MTBF) and mean time to repair (MTTR) to provide reliability statistics of the infrastructure in real time and predicted future time periods; one or more software applications, operatively coupled to and at least partially controlling said one or more processors, said one or more software applications comprising; a characterizer for generating characterized infrastructure network data based on at least a portion of said infrastructure network data and a predictor for; generating predictive infrastructure network data based on at least a portion of said infrastructure network data and determining one or more proposed enhancements in said infrastructure to provide improved infrastructure performance based at least in part on cost information corresponding to said one or more proposed enhancements; wherein the one or more software applications include a machine learning engine; a display, coupled to said one or more processors, for visually presenting a depiction of at least a portion of said infrastructure and said one or more proposed enhancements, based on at least one of;
said characterized infrastructure network data and said predictive infrastructure network data; andone or more distribution controllers in communication with the one or more processors, to distribute the resource to or from the plurality of facilities based on at least one of;
said characterized infrastructure network data and said predictive infrastructure network data. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25)
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26. A method for determining and allocating the distribution, consumption, and supply of a resource within an infrastructure including a plurality of facilities, comprising:
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providing one or more processors, each having respective communication interfaces to receive data from said plurality of facilities, said data comprising infrastructure network data including information corresponding to the consumption and supply of said resource at the plurality of facilities; wherein said one or more processors are further configured to perform sequential Monte Carlo analysis using a topological model of the infrastructure on determined mean time between failure (MTBF) and mean time to repair (MTTR) to provide reliability statistics of the infrastructure in real time and predicted future time periods; providing one or more software applications, operatively coupled to and at least partially controlling said one or more processors, to perform a method to process and characterize said infrastructure network data, by at least; generating predictive infrastructure network data based on at least a portion of said infrastructure network data and determining one or more proposed enhancements in said infrastructure to provide improved infrastructure performance based at least in part on cost information corresponding to said one or more proposed enhancements; wherein the one or more software applications include a machine learning engine; providing a display, coupled to said one or more processors, for visually presenting a depiction of at least a portion of said infrastructure and said one or more proposed enhancements; and providing one or more controllers in communication with the one or more processors, to obtain said resource and distribute said resource based on the characterization of said infrastructure network data. - View Dependent Claims (27, 28, 29, 30, 31, 32)
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33. The method of 29, wherein predicting future events occurs based on predicted storm damage.
Specification