Abstract: A method includes determining whether transformer phases should be permuted. The method includes, responsive to a determination that the transformer phases should be permuted, permuting the transformer phases, based on historical aging information of transformer input phases, to cause transformer input phases with higher ages to be connected to transformer output phases with lower output loads and transformer input phases with lower ages to be connected to transformer output phases with higher output loads. Multiple apparatus and program products are also disclosed.

Abstract: A method includes capturing multivariate time-series data comprising two or more data sets from a system captured over a past time period and a present time period, applying at least two sliding time windows to the multivariate time-series data in determining respective data matrices, computing an orthonormal matrix for each of the data matrices, wherein the orthonormal matrix is a signature of fluctuation patterns of a respective data matrix, computing a difference between at least two of the data sets in the past and the present time periods through the orthonormal matrices, and detecting a fault in at least one of the systems by comparing the difference to a threshold.

Abstract: A method for solving a two-stage non-linear stochastic formulation for the economic dispatch problem under renewable-generation uncertainty. Certain generation decisions are made only in the first stage and fixed for the subsequent (second) stage, where the actual renewable generation is realized. The uncertainty in renewable output is captured by a finite number of scenarios. Any resulting supply-demand mis-match must then be alleviated using high marginal-cost power sources that can be tapped in short time frames. The solution implements two outer approximation algorithms to solve this nonconvex optimization problem to optimality including the application of a decomposition approach derived from the Alternating Direction Method of Multipliers (ADMM) algorithm.

Abstract: A method includes determining whether transformer phases should be permuted. The method includes, responsive to a determination that the transformer phases should be permuted, permuting the transformer phases, based on historical aging information of transformer input phases, to cause transformer input phases with higher ages to be connected to transformer output phases with lower output loads and transformer input phases with lower ages to be connected to transformer output phases with higher output loads. Multiple apparatus and program products are also disclosed.

Abstract: A method for solving a two-stage non-linear stochastic formulation for the economic dispatch problem under renewable-generation uncertainty. Certain generation decisions are made only in the first stage and fixed for the subsequent (second) stage, where the actual renewable generation is realized. The uncertainty in renewable output is captured by a finite number of scenarios. Any resulting supply-demand mis-match must then be alleviated using high marginal-cost power sources that can be tapped in short time frames. The solution implements two outer approximation algorithms to solve this nonconvex optimization problem to optimality. Under certain conditions the sequence of optimal solutions obtained under both alternatives has a limit point that is a globally-optimal solution to the original two-stage nonconvex program. A further decomposition approach derived from the Alternating Direction Method of Multipliers algorithm is implemented.

Abstract: A system and computer program product for solving a two-stage non-linear stochastic formulation for the economic dispatch problem under renewable-generation uncertainty. Certain generation decisions are made only in the first stage and fixed for the subsequent (second) stage, where the actual renewable generation is realized. The uncertainty in renewable output is captured by a finite number of scenarios. Any resulting supply-demand mis-match must then be alleviated using high marginal-cost power sources that can be tapped in short time frames. The solution implements two outer approximation algorithms to solve this nonconvex optimization problem to optimality. Under certain conditions the sequence of optimal solutions obtained under both alternatives has a limit point that is a globally-optimal solution to the original two-stage nonconvex program. A further decomposition approach derived from the Alternating Direction Method of Multipliers algorithm is implemented.

Abstract: An optimization framework to find the periodic inspection interval over an infinite time horizon for geo-distributed infrastructure systems subject to hidden failures. The unit's failure can only be rectified at periodic inspection, at which point a failed unit will be considered as being “perfectly” repaired. For geo-distributed infrastructure systems, for example, fire hydrants in a city, water and power supply networks in urban areas, firstly, the units of a system are clustered into groups. Then, the optimal inspection interval is calculated for each group based on the expected cost per cycle. Finally, the best schedule for inspection is determined. This schedule: (i) minimizes the global system inspection and maintenance cost; and (ii) meets the applicable labor and budget resource constraints. An integer nonlinear programming formulation together with a heuristics deals with the inspection schedule.

Abstract: A method for solving a two-stage non-linear stochastic formulation for the economic dispatch problem under renewable-generation uncertainty. Certain generation decisions are made only in the first stage and fixed for the subsequent (second) stage, where the actual renewable generation is realized. The uncertainty in renewable output is captured by a finite number of scenarios. Any resulting supply-demand mis-match must then be alleviated using high marginal-cost power sources that can be tapped in short time frames. The solution implements two outer approximation algorithms to solve this nonconvex optimization problem to optimality. Under certain conditions the sequence of optimal solutions obtained under both alternatives has a limit point that is a globally-optimal solution to the original two-stage nonconvex program. A further decomposition approach derived from the Alternating Direction Method of Multipliers algorithm is implemented.