Abstract: Systems and methods for performing power analytics on a microgrid. In an embodiment, predicted data is generated for the microgrid utilizing a virtual system model of the microgrid, which comprises a virtual representation of a topology of the microgrid. Real-time data is received via a portal from at least one external data source. If the difference between the real-time data and the predicted data exceeds a threshold, a calibration and synchronization operation is initiated to update the virtual system model in real-time. Power analytics may be performed on the virtual system model to generate analytical data, which can be returned via the portal.

Abstract: Systems and methods for performing power analytics on a microgrid. In an embodiment, predicted data is generated for the microgrid utilizing a virtual system model of the microgrid, which comprises a virtual representation of a topology of the microgrid. Real-time data is received via a portal from at least one external data source. If the difference between the real-time data and the predicted data exceeds a threshold, a calibration and synchronization operation is initiated to update the virtual system model in real-time. Power analytics may be performed on the virtual system model to generate analytical data, which can be returned via the portal.

Abstract: Systems and methods for market-based electric power system optimization are disclosed. Real-time data is acquired from a microgrid. Predicted data is generated by a virtual system model of the microgrid. A virtual system model is updated in real time when a difference between the real-time data and the predicted data exceeds a threshold. A multiplicity of market-based scenarios is presented to the virtual system model to create a multiplicity of altered virtual system models. The multiplicity of market-based scenarios is based on demand data, pricing data and availability data. Simulations for the multiplicity of market-based scenarios are performed based on the multiplicity of altered virtual system models. Simulation results are compared for optimization of microgrid availability and reliability.

Abstract: Systems and methods for performing power analytics on a microgrid. In an embodiment, predicted data is generated for the microgrid utilizing a virtual system model of the microgrid, which comprises a virtual representation of a topology of the microgrid. Real-time data is received via a portal from at least one external data source. If the difference between the real-time data and the predicted data exceeds a threshold, a calibration and synchronization operation is initiated to update the virtual system model in real-time. Power analytics may be performed on the virtual system model to generate analytical data, which can be returned via the portal.

Abstract: Systems and methods for real-time modeling of a microgrid. In an embodiment, real-time data is acquired from a microgrid. Predicted data for the microgrid is generated using a first virtual system model of the microgrid, which comprises a virtual representation of energy sources within the microgrid. The real-time data and the predicted data are monitored, and a calibration and synchronization operation is initiated to update the first virtual system model in real-time when a difference between the real-time data and the predicted data exceeds a threshold. Parameters of the first virtual system model can be modified to create a second virtual system model, and aspects can be forecasted for the microgrid operating under the modified parameters of the second virtual system model. In a further embodiment, market price information can be received, and optimization solutions can be generated based on the market price information.

Abstract: Systems and methods for performing power analytics on a microgrid. In an embodiment, predicted data is generated for the microgrid utilizing a virtual system model of the microgrid, which comprises a virtual representation of a topology of the microgrid. Real-time data is received via a portal from at least one external data source. If the difference between the real-time data and the predicted data exceeds a threshold, a calibration and synchronization operation is initiated to update the virtual system model in real-time. Power analytics may be performed on the virtual system model to generate analytical data, which can be returned via the portal.

Abstract: Systems and methods for model-based real-time solar power management. In an embodiment, real-time data is received from sensor(s) of an electrical system comprising a photo-voltaic power generator. Predicted data is generated based on a virtual model of the electrical system that replicates operation of the sensor(s). The virtual model is continuously and automatically synchronized with the electrical system based on a difference between the real-time data and the predicted data. Solar irradiance forecast data may also be received and used in conjunction with the virtual model to forecast a power output of the photo-voltaic power generator.

Abstract: A system and method for providing real-time modeling of an electrical power system for demand response. In an embodiment, real-time data is acquired from an electrical power system. Predicted data is generated for the electrical power system utilizing a virtual system model of the electrical power system. If a difference between the real-time data and predicted data exceeds a threshold, a calibration and synchronization operation is initiated to update the virtual system model to provide predicted data that is consistent with the real-time data. In addition, patterns observed from the real-time data and predicted data may be processed, and an aspect of the electrical power system can be forecasted. The forecasted aspect may then be provided to a demand response market system.

Abstract: A system and method for real-time modeling of a microgrid. In an embodiment, the system includes a data acquisition component, a virtual system modeling engine, and an analytics engine. The data acquisition component acquires real-time data from a microgrid. The virtual system modeling engine generates predicted data for the microgrid. The analytics engine analyzes a difference between the real-time data and the predicted data. If the difference exceeds a threshold, the virtual system model is updated to provide predicted data that is consistent with the real-time data. In addition, a simulation module may process patterns observed from the real-time data and predicted data, and forecast an aspect of the microgrid. This forecasted aspect may then be provided to a microgrid operator, as well as a macrogrid operator.

Abstract: Systems and methods for performing power analytics on a microgrid. In an embodiment, predicted data is generated for the microgrid utilizing a virtual system model of the microgrid, which comprises a virtual representation of a topology of the microgrid. Real-time data is received via a portal from at least one external data source. If the difference between the real-time data and the predicted data exceeds a threshold, a calibration and synchronization operation is initiated to update the virtual system model in real-time. Power analytics may be performed on the virtual system model to generate analytical data, which can be returned via the portal.

Abstract: Systems and methods for real-time modeling of a microgrid. In an embodiment, real-time data is acquired from a microgrid. Predicted data for the microgrid is generated using a first virtual system model of the microgrid, which comprises a virtual representation of energy sources within the microgrid. The real-time data and the predicted data are monitored, and a calibration and synchronization operation is initiated to update the first virtual system model in real-time when a difference between the real-time data and the predicted data exceeds a threshold. Parameters of the first virtual system model can be modified to create a second virtual system model, and aspects can be forecasted for the microgrid operating under the modified parameters of the second virtual system model. In a further embodiment, market price information can be received, and optimization solutions can be generated based on the market price information.