Self-Organizing System of Sensors for Monitoring and Diagnostics of a Modern Microgrid

Michael Gouzman; Serge Luryi; Claran Martis; Yacov A. Shamash; Alex Shevchenko

doi:10.1002/9781119890881.ch29

Self-Organizing System of Sensors for Monitoring and Diagnostics of a Modern Microgrid

Michael Gouzman
, Serge Luryi
, Claran Martis
, Yacov A. Shamash
, Alex Shevchenko

Electrical Engineering

Stony Brook University

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

Abstract

Modern microgrids that are dynamic in nature need to be monitored in real time to be able to identify and diagnose issues that may occur in the grid. The direction of power flow in the power lines may change frequently in response to events or due to optimizations in the grid. Therefore, identifying the current topology of the microgrid is important. A Network Topology Identification Algorithm that uses data from an Energy Flow Sensor is discussed in detail.

Original language	English
Title of host publication	Microgrids
Subtitle of host publication	Theory and Practice
Publisher	wiley
Pages	713-727
Number of pages	15
ISBN (Electronic)	9781119890881
ISBN (Print)	9781119890850
DOIs	https://doi.org/10.1002/9781119890881.ch29
State	Published - Jan 1 2024

Keywords

dynamic microgrids
energy flow sensor
monitoring system
topology identification

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10.1002/9781119890881.ch29

Cite this

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abstract = "Modern microgrids that are dynamic in nature need to be monitored in real time to be able to identify and diagnose issues that may occur in the grid. The direction of power flow in the power lines may change frequently in response to events or due to optimizations in the grid. Therefore, identifying the current topology of the microgrid is important. A Network Topology Identification Algorithm that uses data from an Energy Flow Sensor is discussed in detail.",

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AU - Shevchenko, Alex

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KW - energy flow sensor

KW - monitoring system

KW - topology identification

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ER -

Self-Organizing System of Sensors for Monitoring and Diagnostics of a Modern Microgrid

Abstract

Keywords

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