Abstract: Systems and methods for failure prediction and maintenance planning are provided. A system for failure prediction and maintenance planning, comprises a statistical modeling module comprising a periodic impact evaluation module capable of identifying periodic effects on the failure risk, a balance equation systems module capable of constructing balance equations with respect to phases of failure times, and an initial phase estimation module capable of estimating an unknown initial phase, wherein one or more of the modules are implemented on a computer system comprising a memory and at least one processor coupled to the memory.

Abstract: Systems and methods for failure prediction and maintenance planning are provided. A system for failure prediction and maintenance planning, comprises a statistical modeling module comprising a periodic impact evaluation module capable of identifying periodic effects on the failure risk, a balance equation systems module capable of constructing balance equations with respect to phases of failure times, and an initial phase estimation module capable of estimating an unknown initial phase, wherein one or more of the modules are implemented on a computer system comprising a memory and at least one processor coupled to the memory.

Abstract: The present disclosure relates generally to computational solution algorithms (and associated systems and methods) applied to a stochastic unit commitment problem. In one example, the computational solution algorithms (and associated systems and methods) may be applied to the energy industry.

Abstract: The present disclosure relates generally to systematic algorithms (and associated systems and methods) that take a forecast model as input and produce a discrete probability distribution as output, using scenario reduction ideas from stochastic programming. In one example, an algorithm (and associated system and method) creates scenarios sequentially for each time period, leading to a scenario tree.

Abstract: A system and method for detecting anomalous energy usage of building or household entities. The method applies a number of successively stringent anomaly detection techniques to isolate households that are highly suspect for having engaged in electricity theft via meter tampering. The system utilizes historical time series data of electricity usage, weather, and household characteristics (e.g., size, age, value) and provides a list of households that are worthy of a formal theft investigation. Generally, raw utility usage data, weather history data, and household characteristics are cleansed, and loaded into an analytics data mart. The data mart feeds four classes of anomaly detection algorithms developed, with each analytic producing a set of households suspected of having engaged in electricity theft. The system allows a user to select households from each list or a set based on the intersection of all individual sets.

Abstract: A method for detecting anomalous energy usage of building or household entities. The method applies a number of successively stringent anomaly detection techniques to isolate households that are highly suspect for having engaged in electricity theft via meter tampering. The system utilizes historical time series data of electricity usage, weather, and household characteristics (e.g., size, age, value) and provides a list of households that are worthy of a formal theft investigation. Generally, raw utility usage data, weather history data, and household characteristics are cleansed, and loaded into an analytics data mart. The data mart feeds four classes of anomaly detection algorithms developed, with each analytic producing a set of households suspected of having engaged in electricity theft. The system allows a user to select households from each list or a set based on the intersection of all individual sets.

Abstract: A system, method and computer program product for improving a manufacturing or production environment. The system receives two or more time series data having values that represent current conditions of the manufacturing or production environment as inputs. The system determines one or more different regimes in the received two or more time series data. The system predicts future or unmeasured values of the received two or more time series data in the determined different regimes. The future or unmeasured values represent future conditions of the manufacturing or production environment.

Abstract: Described herein are methods, systems, apparatuses and products for phase determination in an electricity grid. An aspect provides for determining phase for at least one electric grid device via receiving power consumption measurements derived from electricity grid devices connected in the electricity grid, comparing, over a series of time intervals, a total power consumed; and determining a phase for at least one electricity grid device.

Abstract: An approach for infrastructure asset management is provided. This approach comprises an end-to-end analytics driven maintenance approach that can take data about physical assets and additional external data, and apply advanced analytics to the data to generate business insight, foresight and planning information. Specifically, this approach uses a maintenance analysis tool, which is configured to: receive data about a set of physical assets of an infrastructure, and analyze the data about the set of physical assets to predict maintenance requirements for each of the set of physical assets. The maintenance analysis tool further comprises an output component configured to generate a maintenance plan based on the predicted maintenance requirements for each of the set of physical assets.

Abstract: A system, method and computer program product for maintaining an infrastructure of components. The system receives structured data, unstructured data, and infrastructure data from a database. The system runs at least one statistical and optimization modeler with one or more of: the received structured data, the received unstructured data and the received infrastructure data, in order to calculate a health index of at least one component of the infrastructure. The health index represents a health attribute of the at least one component. The system establishes at least one maintenance plan of the infrastructure, based on the calculated health index. Each established maintenance plan is associated with at least one health index. The system compares health indices of the at least one established maintenance plan. The system selects a plan, among the at least one established maintenance plan, whose health index is a maximum among the compared health indices.

Abstract: A system, a method and a computer program product for determining an amount of an electric power to be generated in an electric power system and determining a total cost for generating the amount of electric power while satisfying at least one contingency constraint and one or more customer request. The system creates an optimization problem for calculating amount of the electric power to be generated and a total cost for generating the calculated amount of the electric power while meeting the at least one contingency constraint. The system runs the optimization problem in real-time. The system outputs, from the optimization problem, an output specifying the calculated amount of the electric power and the total cost to generate the calculated amount of the electric power.

Abstract: Systems and methods for failure prediction and maintenance planning are provided. A system for failure prediction and maintenance planning, comprises a statistical modeling module comprising a periodic impact evaluation module capable of identifying periodic effects on the failure risk, a balance equation systems module capable of constructing balance equations with respect to phases of failure times, and an initial phase estimation module capable of estimating an unknown initial phase, wherein one or more of the modules are implemented on a computer system comprising a memory and at least one processor coupled to the memory.

Abstract: Systems and methods for failure prediction and maintenance planning are provided. A system for failure prediction and maintenance planning, comprises a statistical modeling module comprising a periodic impact evaluation module capable of identifying periodic effects on the failure risk, a balance equation systems module capable of constructing balance equations with respect to phases of failure times, and an initial phase estimation module capable of estimating an unknown initial phase, wherein one or more of the modules are implemented on a computer system comprising a memory and at least one processor coupled to the memory.

Abstract: A method and system for designing a layout of turbines on a grid is provided. The method comprises receiving wind data for each possible location of placement of a turbine on said grid; calculating an energy yield for a given layout of turbines on said grid as a nonlinear objective function, said function constrained by said wind data; implementing a bounding heuristic, said bounding heuristic comparing said calculated energy yield for said given layout of turbines to a current lower bound, and if said calculated energy yield is greater than the current lower bound, replacing the current lower bound with the calculated energy yield; and repeating the above steps for different layouts of turbines on the grid.

Abstract: A method and system for optimizing modules of a steel manufacturing process includes a plurality of manufacturing modules for a manufacturing process. Each of the modules have a plurality of steps. The plurality of modules include at least an upstream module, a casting module, and a downstream module. Each of the plurality of modules have parameters, and include at least one variable event. The variable event is adjustable for optimization of the manufacturing process while the parameters are being maintained for each of the plurality of modules. A communication system is used for exchanging information between the modules while the manufacturing process is occurring to adjust the at least one variable event for optimizing the manufacturing process.

Abstract: System and method of solving, in a single-period, an optimal dispatching problem for a network of energy generators connected via multiple transmission lines, where it is sought to find the lowest operational cost of dispatching of various energy sources to satisfy demand. The model includes traditional thermal resources and renewable energy resources available generation capabilities within the grid. The method considers demand reduction as a virtual generation source that can be dispatched quickly to hedge against the risk of unforeseen shortfall in supply. Demand reduction is dispatched in response to incentive signals sent to consumers. The control options of the optimization model consist of the dispatching order and dispatching amount energy units at generators together with the rebate signals sent to end-users at each node of the network under a demand response policy. Numerical experiments based on an analysis of representative data illustrate the effectiveness of demand response as a hedging option.

Abstract: A system, a method and a computer program product for determining an amount of an electric power to be generated in an electric power system and determining a total cost for generating the amount of electric power while satisfying at least one contingency constraint and one or more customer request. The system creates an optimization problem for calculating amount of the electric power to be generated and a total cost for generating the calculated amount of the electric power while meeting the at least one contingency constraint. The system runs the optimization problem in real-time. The system outputs, from the optimization problem, an output specifying the calculated amount of the electric power and the total cost to generate the calculated amount of the electric power.

Abstract: A method and system for designing a layout of turbines on a grid is provided. The method comprises receiving wind data for each possible location of placement of a turbine on said grid; calculating an energy yield for a given layout of turbines on said grid as a nonlinear objective function, said function constrained by said wind data; implementing a bounding heuristic, said bounding heuristic comparing said calculated energy yield for said given layout of turbines to a current lower bound, and if said calculated energy yield is greater than the current lower bound, replacing the current lower bound with the calculated energy yield; and repeating the above steps for different layouts of turbines on the grid.

Abstract: The present disclosure relates generally to computational solution algorithms (and associated systems and methods) applied to a stochastic unit commitment problem. In one example, the computational solution algorithms (and associated systems and methods) may be applied to the energy industry.

Abstract: The present disclosure relates generally to systematic algorithms (and associated systems and methods) that take a forecast model as input and produce a discrete probability distribution as output, using scenario reduction ideas from stochastic programming. In one example, an algorithm (and associated system and method) creates scenarios sequentially for each time period, leading to a scenario tree.