Abstract: A system for real-time optimization of power resources on an electrical system is disclosed. The system includes a data acquisition component, an analytics server, a control element and a client terminal. The data acquisition component is communicatively connected to a sensor configured to acquire real-time data output from the electrical system. The analytics server is communicatively connected to the data acquisition component and is comprised of a virtual system modeling engine, an analytics engine and a power flow optimization engine. The virtual system modeling engine is configured to generate predicted data output for the electrical system utilizing a virtual system model of the electrical system. The control element is interfaced with an electrical system component and communicatively connected to the analytics server. The client terminal is communicatively connected to the analytics server.

Abstract: A system for conducting performing real-time harmonics analysis of an electrical power distribution and transmission system is disclosed. The system includes a data acquisition component, a power analytics server and a client terminal. The data acquisition component is communicatively connected to a sensor configured to acquire real-time data output from the electrical system. The power analytics server is communicatively connected to the data acquisition component and is comprised of a virtual system modeling engine, an analytics engine and a machine learning engine. The machine learning engine is configured to store and process patterns observed from the real-time data output and the predicted data output, forecasting harmonic distortions in the electrical system subjected to a simulated contingency event.

Abstract: Systems and method for providing a microgrid power analytics portal for mission critical power systems are provided. The techniques disclosed herein provides for real-time modeling, evaluation, and commodity market pricing and optimization for an electrical network that includes microgrids using data collected from virtually any digital data source. The portal is platform independent and can be configured to collect and aggregate real-time data from sensors interfaced with components of the electrical network regardless of proprietary architectures or vendor-specific limitations imposed by the sensors or data collection software.

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: A system for providing real-time modeling of protective device in an electrical system under management is disclosed. The system includes a data acquisition component, a virtual system modeling engine, and an analytics engine. The data acquisition component is communicatively connected to a sensor configured to provide real-time measurements of data output from protective devices within the system under management. The virtual system modeling engine is configured to update a virtual mode of the system based on the status of the protective devices and to generate predicted data for the system using the updated virtual model. The analytics engine is communicatively connected to the data acquisition system and the virtual system modeling engine and is configured to monitor and analyze a difference between the real-time data output and the predicted data output. The analytics engine is also configured to determine the bracing capabilities for the protective devices.

Abstract: A system for real-time modeling of uninterruptible power supply (UPS) control elements protecting an electrical system is disclosed. The system includes a data acquisition component, a power analytics server and a client terminal. The data acquisition component acquires real-time data output from the electrical system. The power analytics server is comprised of a virtual system modeling engine, an analytics engine and a UPS transient stability simulation engine. The virtual system modeling engine generates predicted data output for the electrical system. The analytics engine monitors real-time data output and predicted data output of the electrical system. The UPS transient stability simulation engine stores and processes patterns observed from the real-time data output and utilizes a user-defined UPS control logic model to forecast an aspect of the interaction between UPS control elements and the electrical system subjected to a simulated contingency event.

Abstract: A system for performing real-time failure mode analysis of a monitored system is disclosed. The system includes a data acquisition component, an analytics server and a client terminal. The data acquisition component is communicatively connected to a sensor configured to acquire real-time data output from the monitored system. The analytics server is communicatively connected to the data acquisition component and is comprised of a virtual system modeling engine, an analytics engine and a machine learning engine.

Abstract: A system for making real-time predictions about an arc flash event on an electrical system is disclosed. The system includes a data acquisition component, an analytics server and a client terminal. The data acquisition component is communicatively connected to a sensor configured to acquire real-time data output from the electrical system. The analytics server is communicatively connected to the data acquisition component and is comprised of a virtual system modeling engine, an analytics engine and an arc flash simulation engine.

Abstract: A system for providing real-time modeling of an electrical system under management is disclosed. The system includes a data acquisition component, a virtual system modeling engine, and an analytics engine. The data acquisition component is communicatively connected to a sensor configured to provide real-time measurements of data output from an element of the system. The virtual system modeling engine is configured to generate a predicted data output for the element. The analytics engine is communicatively connected to the data acquisition system and the virtual system modeling engine and is configured to monitor and analyze a difference between the real-time data output and the predicted data output.

Abstract: A system for making real-time predictions about an arc flash event on an electrical system is disclosed. The system includes a data acquisition component, an analytics server and a client terminal. The data acquisition component is communicatively connected to a sensor configured to acquire real-time data output from the electrical system. The analytics server is communicatively connected to the data acquisition component and is comprised of a virtual system modeling engine, an analytics engine and an arc flash simulation engine. The arc flash simulation engine is configured to utilize the virtual system model to forecast an aspect of the arc flash event.

Abstract: A system for providing real-time modeling of an electrical system under management is disclosed. The system includes a data acquisition component, a virtual system modeling engine, and an analytics engine. The data acquisition component is communicatively connected to a sensor configured to provide real-time measurements of data output from an element of the system. The virtual system modeling engine is configured to generate a predicted data output for the element. The analytics engine is communicatively connected to the data acquisition system and the virtual system modeling engine and is configured to monitor and analyze a difference between the real-time data output and the predicted data output.

Abstract: A system for filtering and interpreting real-time sensory data from an electrical system is disclosed. The system includes a data acquisition component, a power analytics server and a client terminal. The data acquisition component acquires real-time data output from the electrical system. The power analytics server is comprised of a virtual system modeling engine, an analytics engine, and a decision engine. The virtual system modeling engine generates predicted data output for the electrical system. The analytics engine monitors real-time data output and predicted data output of the electrical system. The decision engine compares the real-time data output against the predicted data output to filter out and interpret indicia of electrical system health and performance. The client terminal is communicatively connected to the power analytics server and configured to display the filtered and interpreted indicia.

Abstract: A system for making real-time predictions about an arc flash event on an electrical system is disclosed. The system includes a data acquisition component, an analytics server and a client terminal. The data acquisition component is communicatively connected to a sensor configured to acquire real-time data output from the electrical system. The analytics server is communicatively connected to the data acquisition component and is comprised of a virtual system modeling engine, an analytics engine and an arc flash simulation engine. The arc flash simulation engine is configured to utilize the virtual system model to forecast an aspect of the arc flash event.

Abstract: A system for filtering and interpreting real-time sensory data from an electrical system is disclosed. The system includes a data acquisition component, a power analytics server and a client terminal. The data acquisition component acquires real-time data output from the electrical system. The power analytics sewer is comprised of a virtual system modeling engine, an analytics engine, and a decision engine. The virtual system modeling engine generates predicted data output for the electrical system. The analytics engine monitors real-lime data output and predicted data output of the electrical system. The decision engine compares the real-time data output against the predicted data output to filter out and interpret indicia of electrical system health and performance. The client terminal is communicatively connected to the power analytics server and configured to display the filtered and interpreted indicia.

Abstract: A system for making real-time predictions about an arc flash event on an electrical system comprises a data acquisition component communicatively connected to a sensor configured to acquire real-time data output from the electrical system; an analytics server communicatively connected to the data acquisition component and comprising a virtual system modeling engine configured to generate predicted data output for the electrical system using a virtual system model of the electrical system, an analytics engine configured to monitor the real-time data output and the predicted data output of the electrical system, and an arc flash simulation engine configured to use the virtual system model updated based in the real-time data to forecast an aspect of the arc flash event.

Abstract: A system for real-time verification of protective device system configuration settings on a monitored system, is disclosed. The system includes a data acquisition component, a virtual system model database, a protective device system verification engine. The data acquisition component is communicatively connected to a sensor configured to real-time protective device configuration data output from a protective device that is part of the monitored system. The virtual system model database is configured to update a virtual mode of the system based on the status of the protective devices and to store a virtual system model of the monitored system, including preset protective device configuration settings for the protective device.

Abstract: A system for utilizing a neural network to make real-time predictions about the health, reliability, and performance of a monitored system are disclosed. The system includes a data acquisition component, a power analytics server and a client terminal. The data acquisition component acquires real-time data output from the electrical system. The power analytics server is comprised of a virtual system modeling engine, an analytics engine, an adaptive prediction engine. The virtual system modeling engine generates predicted data output for the electrical system. The analytics engine monitors real-time data output and predicted data output of the electrical system. The adaptive prediction engine can be configured to forecast an aspect of the monitored system using a neural network algorithm.

Abstract: A method for simulating an arc flash event on an electrical power system is disclosed. The virtual system model of the electrical system is modified to introduce a short circuiting feature. The standard to supply equations used in the arc flash event calculations is chosen. The arc flash event is simulated using the modified virtual system model in accordance with the chosen standard. The quantity of arc energy released by the arc flash event is calculated using results from the simulation. The report that forecasts an aspect of the arc flash event is communicated.

Abstract: A computer system for converting a computer aided design drawing file of an electrical power system into one or more component objects for power analytic analysis and simulation, is disclosed. The computer system can include a processor, a memory, a display device, and an input device. The memory device can be coupled to the processor and configured to maintain a component classification database, an import engine, computer aided design drawing parser, and a symbol classification engine. The display device can be coupled to the processor and configured for displaying the computer aided design drawing file of the electrical power system.

Abstract: A system for modeling a topology of an electrical power system is disclosed. The system can include a processor, a memory, a display device, and an input device. The memory device can be coupled to the processor and configured to maintain a component database, a component control engine, and a power system topology modeling engine. The display device can be coupled to the processor and configured for displaying the topology of the electrical power system. The input device can be coupled to the processor and can be operative to select one of the plurality of power system components stored in the component database as a selected component, position the selected component within a framework, and interface the selected component with other selected components within the framework.