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

專利號
US10867087B2
公開日期
2020-12-15
申請人
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.

說明書

Thus, the above methods provide a mean to determine the withstand capability of various protective devices, under various conditions and using various standards, using an aged, up to date virtual model of the system being monitored.

The influx of massive sensory data, e.g., provided via sensors 104, 106, and 108, intelligent filtration of this dense stream of data into manageable and easily understandable knowledge. For example, as mentioned, it is important to be able to assess the real-time ability of the power system to provide sufficient generation to satisfy the system load requirements and to move the generated energy through the system to the load points. Conventional systems do not make use of an on-line, real-time system snap shot captured by a real-time data acquisition platform to perform real time system availability evaluation.

FIG. 15 is a flow chart illustrating an example process for analyzing the reliability of an electrical power distribution and transmission system in accordance with one embodiment. First, in step 1502, reliability data can be calculated and/or determined. The inputs used in step 1502 can comprise power flow data, e.g., network connectivity, loads, generations, cables/transformer impedances, etc., which can be obtained from the predicted values generated in step 1008, reliability data associated with each power system component, lists of contingencies to be considered, which can vary by implementation including by region, site, etc., customer damage (load interruptions) costs, which can also vary by implementation, and load duration curve information. Other inputs can include failure rates, repair rates, and required availability of the system and of the various components.

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