Abstract: Systems and methods for optimizing energy consumption in multi-energy sources sites are provided. These techniques include developing a real-time model and a virtual model of the electrical system of a multi-energy source site, such as a microgrid. The real-time model represents a current state of the electrical system can be developed by collecting data from sensors interfaced with the various components of the electrical system. The virtual model of the electrical system mirrors the real-time model of the electrical system and can be used to generate predictions regarding the performance, availability, and reliability of cost and reliability of various distributed energy sources and to predict the price of acquiring energy from these sources. The virtual model can be used to test “what if” scenarios, such as routine maintenance, system changes, and unplanned events that impact the utilization and capacity of the microgrid.

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 demand response are disclosed. An analytics server is communicatively connected to a data acquisition component and a virtual system model database. The data acquisition component is operable to acquire and transmit real-time data from a demand response (DR) power network to the analytic server. The virtual system model database is operable to provide a virtual system model of the DR power network. The analytics server is operable to generate predicted data based on the virtual system model of the DR power network and update the virtual system model in real time based on a difference between the predicted data and the real-time data. The analytics server is further operable to optimize DR output of the DR power network to a power grid.