Abstract: A computer-implemented method, system, and computer program product are provided for anomaly detection in a power system. The method includes receiving, by a processor-device, a plurality of measurements from a plurality of meters throughout the power system. The method also includes generating, by the processor-device, temporal causal networks based on pair-wise relationships between the plurality of measurements from the plurality of meters over time. The method additionally includes determining, by the processor-device, invariant relationships for the plurality of meters between the temporal causal networks. The method further includes predicting, by the processor-device, an anomaly from the invariant relationships for the plurality of meters with a residual anomaly threshold. The method also includes disabling one of the plurality of meters that originated the anomaly.

Abstract: Systems and methods for photovoltaic (PV) output forecasting are provided. The methods include determining whether a weather condition that indicates a first forecasting model to have a greater accuracy than a deep learning-based forecasting model is detected in weather data for a predetermined time span. The method also includes forecasting PV output, by a processing device, using the first forecasting model in response to a determination that the weather condition is detected in the weather data for the predetermined time span. The method further includes predicting PV output using the deep learning-based forecasting model in response to a determination that the weather condition is not detected in the weather data for the predetermined time span.

Abstract: A computer-implemented method, system, and computer program product are provided for anomaly detection in a power system. The method includes receiving, by a processor-device, a plurality of measurements from a plurality of meters throughout the power system. The method also includes generating, by the processor-device, temporal causal networks based on pair-wise relationships between the plurality of measurements from the plurality of meters over time. The method additionally includes determining, by the processor-device, invariant relationships for the plurality of meters between the temporal causal networks. The method further includes predicting, by the processor-device, an anomaly from the invariant relationships for the plurality of meters with a residual anomaly threshold. The method also includes disabling one of the plurality of meters that originated the anomaly.

Abstract: A computer-implemented method executed on a processor for outputting a smoothed photovoltaic (PV) power output from a battery of a power control system communicating with one or more microgrids is presented. The method includes curtailing an input signal received from a plurality of sensors, smoothing the input signal by employing a fuzzy logic based low pass filter having an adaptive window to generate a power reference command, applying a hard ramp rate limit to the power reference command, adjusting battery power output of the battery to satisfy battery constraints and a no-power-from-grid constraint, and distributing energy from the battery based on the adjusted battery power output.

Abstract: A system and method are provided for an energy distribution system having at least one energy storage system and at least one renewable energy resource. The method includes determining distribution optimal power flow optimization models of components of the distribution system. The components at least include the at least one energy storage system and the at least one renewable energy resource. The method further includes generating a composite model of the distribution system by integrating therein the distribution optimal power flow optimization models. The method also includes optimally scheduling, using a processor-based scheduling optimizer, an operation of resources in the distribution system using at least one of a fixed-window iterative optimization technique and a rolling stochastic optimization technique applied to the composite model.