Visible to the public Real-Time Resiliency Assessment of Control Systems in Microgrids Using the Complexity Metric

TitleReal-Time Resiliency Assessment of Control Systems in Microgrids Using the Complexity Metric
Publication TypeConference Paper
Year of Publication2019
AuthorsFerdowsi, Farzad, Barati, Masoud, Edrington, Chris S.
Conference Name2019 IEEE Green Technologies Conference(GreenTech)
ISBN Number978-1-7281-1457-6
KeywordsComplexity Metric, complexity quantification metric, Complexity theory, control systems, control theory, Control Theory and Resiliency, Cyber physical system, cyber physical systems, distributed power generation, Fault tolerance, high speed winds, high-impact low-frequency weather-related events, HILF, Human Behavior, interconnected systems, Measurement, microgrid, Microsoft Windows, nonlinear control systems, nonlinear interconnected system, Operational Resilience, operational resilience quantification, power electronic-based components, power electronics, power generation control, power system stability, power transformers, pubcrawl, Real-time Resiliency, real-time resiliency assessment, resilience, Resiliency, Scalability, solid-state transformer, SST, weather-related disturbances
Abstract

This paper presents a novel technique to quantify the operational resilience for power electronic-based components affected by High-Impact Low-Frequency (HILF) weather-related events such as high speed winds. In this study, the resilience quantification is utilized to investigate how prompt the system goes back to the pre-disturbance or another stable operational state. A complexity quantification metric is used to assess the system resilience. The test system is a Solid-State Transformer (SST) representing a complex, nonlinear interconnected system. Results show the effectiveness of the proposed technique for quantifying the operational resilience in systems affected by weather-related disturbances.

URLhttps://ieeexplore.ieee.org/document/8767158
DOI10.1109/GreenTech.2019.8767158
Citation Keyferdowsi_real-time_2019