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Title: A Hybrid Data-Driven and Model-Based Anomaly Detection Scheme for DER Operation

Conference ·

This paper proposes a hybrid data and model-based anomaly detection scheme to secure the operation of distributed energy resources (DERs) in distribution grids. Data-driven autoencoders are set up at the edge device level and they use local DER operational data as inputs. The abnormal statuses are detected by analyzing reconstruction errors. In parallel, modelbased state estimation (SE) is set up at the central level and it uses system-wide models and measurements as data inputs. The anomalies are identified by analyzing measurement residuals. The hybrid scheme preserves the benefits of both data-driven and model-based analyses and thus improves the robustness and the accuracy of anomaly detection. Numerical tests based on the model of a real distribution feeder in Southern California highlight the proposed scheme's effectiveness and benefits.

Research Organization:
National Renewable Energy Lab. (NREL), Golden, CO (United States)
Sponsoring Organization:
USDOE Grid Modernization Laboratory Consortium
DOE Contract Number:
Report Number(s):
NREL/CP-5D00-83787; MainId:84560; UUID:021f4c8e-c3df-4996-b521-4d41950aa273; MainAdminID:65157
Resource Relation:
Conference: Presented at the 2022 IEEE Power & Energy Society Innovative Smart Grid Technologies Conference (ISGT), 24-28 April 2022, New Orleans, Louisiana; Related Information: 80628
Country of Publication:
United States

References (7)

Performance Evaluation of Distributed Energy Resource Management via Advanced Hardware-in-the-Loop Simulation conference February 2020
Distribution System State Estimation: A Semidefinite Programming Approach journal July 2019
Power system disturbance identification from recorded dynamic data at the Northfield substation journal December 2003
Comprehensive Clustering of Disturbance Events Recorded by Phasor Measurement Units journal June 2014
30 years of adaptive neural networks: perceptron, Madaline, and backpropagation journal January 1990
Reducing the Dimensionality of Data with Neural Networks journal July 2006
Fault Detection and Isolation Filters for Three-Phase AC-DC Power Electronics Systems journal April 2013