Calm Energy Inc.

Columbia University

Consolidated Edison Company of New York, Inc.

Consolidated Edison of New York, Inc.

John A Johnson

Roger N Anderson

Albert Boulanger

Mark Mastrocinque

Philip Gross

Hubert Delany

Arthur Kressner

Marta Arias

Hila Becker

David Waltz

Fred Seibel

Bob Blick

Phil Long

Leon Bukhman

Matthew Koenig

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 comprising 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.

Dynamic contingency avoidance and mitigation system

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.

The disclosed subject matter relates to an integrated decision support 'cockpit' or control center for displaying, analyzing, and/or responding to, various events and contingencies that can occur within an electrical grid.

Decision support control centers

One embodiment of the instant invention is a computer-implemented method that includes steps of: receiving load data for a load, where the load is associated with a smart node that controls a flow of electricity, where the load data includes a service type indication; where the service type indication identifies whether the load receive in a non-firm electricity service, a firm electricity service, or both, where the non-firm electricity service is based on a non-firm service supply arrangement associated with the load and a supplier of electricity, where the non-firm service supply arrangement defines electricity usage based on a reliability level of the electrical supply provided by the supplier of electricity without a guaranteed level of uninterrupted electricity supply, and where the reliability level of the electrical supply is based on an ability to instruct to reduce or shut off the electricity supply.

Systems and methods for operating electrical supply

In one embodiment, the instant invention includes a method of executing computer instructions having steps of: a) receiving, by a first computer, an instruction to perform a task b) executing each thread of a process, corresponding to the task, to time stop point when each thread requires data from a second computer system; maintaining a data structure that identifies a state information of each thread at the time stop point, and ii) whenever each thread reaches its own stop point, each thread gives up its execution in favor of an execution of another thread; c) requesting, from the second computer system, the data needed to continue the execution of the process; d) receiving, from the second computer system, the requested data; and e) resuming the execution of the process based on the state information for each thread stored in the data structure at the time stop point.

Computer methods for business process management execution and systems thereof

A machine learning system creates failure-susceptibility rankings for feeder cables in a utility's electrical distribution system. The machine learning system employs martingale boosting algorithms and Support Vector Machine (SVM) algorithms to generate a feeder failure prediction model, which is trained on static and dynamic feeder attribute data. Feeders are dynamically ranked by failure susceptibility and the rankings displayed to utility operators and engineers so that they can proactively service the distribution system to prevent local power outages. The feeder rankings may be used to redirect power flows and to prioritize repairs. A feedback loop is established to evaluate the responses of the electrical distribution system to field actions taken to optimize preventive maintenance programs.

System and method for grading electricity distribution network feeders susceptible to impending failure

Growing community of inventors

Belle Harbor, NY, United States of America

John A Johnson