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

專利號(hào)
US10867087B2
公開(kāi)日期
2020-12-15
申請(qǐng)人
WaveTech Global Inc.（US NJ Hoboken）
發(fā)明人
Kevin Meagher; Brian Radibratovic; Adib Nasle
IPC分類
G06F17/50; G06F30/20; H02J13/00; H04L29/08; G06F30/00; G05F1/66; H02J3/00; G06F30/367; G06F119/06
技術(shù)領(lǐng)域
system,analytics,power,in,data,electrical,real,virtual,can,be
地域： NJ NJ Hoboken

摘要

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.

說(shuō)明書(shū)

FIG. 23 is an example process for alarm filtering and management of real-time sensory data from a monitored electrical system, in accordance with one embodiment. The complexity of electrical power systems coupled with the many operational conditions that the systems can be asked to operate under pose significant challenges to owners, operators and managers of critical electrical networks. It is vital for owners and operators alike to have a precise and well understood perspective of the overall health and performance of the electrical network.

The ability to intelligently filter, interpret and analyze dense real-time sensory data streams generated by sensor clusters distributed throughout the monitored electrical facility greatly enhances the ability of facility administrators/technical staff (e.g., operators, owners, managers, technicians, etc.) to quickly understand the health and predicted performance of their power network. This allows them to quickly determine the significance of any deviations detected in the sensory data and take or recommend reconfiguration options in order to prevent potential power disruptions.

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