Power Analytics Corporation

Wavetech Global Inc.

Edsa Micro Corporation

Kevin Meagher

Adib Nasle

Branislav Radibratovic

Ali Nasle

Brian Radibratovic

Barry Needle

David Loiselle

Rodger Koopman

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.

Microgrid model based automated real time simulation for market based electric power system optimization

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.

Systems and methods for real-time DC microgrid power analytics for mission-critical power systems

Systems and methods for making real-time predictions about an arc flash event on an electrical system are disclosed. An analytics server is communicatively connected to a data acquisition component. The analytics server comprises a virtual system modeling engine configured to create a virtual system model reflecting current network topology of the electrical system; an analytics engine configured to monitor predicted output data from the virtual system model and real-time output data from the electrical system acquired by the data acquisition component and update the virtual system model when a difference between the real-time output data and the predicted output data exceeds a threshold; and an arc flash simulation engine configured to forecast at least one aspect of and arc flash event based on the virtual system model.

Method for predicting symmetric, automated, real-time ARC flash energy within a real-time monitoring system

A system for automatically generating a schematic user interface of 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, a machine learning engine and a schematic user interface creator 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 machine learning engine stores and processes patterns observed from the real-time data output and the predicted data output to forecast an aspect of the electrical system. The schematic user interface creator engine is configured to create a schematic user interface that is representative of the virtual system model and link the schematic user interface to the data acquisition component.

Systems and methods for creation of a schematic user interface for monitoring and predicting the real-time health, reliability and performance of an electrical power system

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.

Method for predicting symmetric, automated, real-time Arc Flash energy within a real-time monitoring system

A system for making real-time predictions about power usage efficiency (PUE) and/or data center infrastructure efficiency (DCiE) of 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 a PUE/DCiE simulation engine configured to use the virtual system model updated based in the real-time data to forecast the PUE/DCiE.

Method for predicting power usage effectiveness and data center infrastructure efficiency within a real-time monitoring system

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.

Real time microgrid power analytics portal for mission critical power systems

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.

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Raleigh, NC, United States of America

Kevin Meagher