Assessment of the Center of Inertia and Regional Inertia with Load Contribution via a Fully Data-Driven Method
Lucas Lugnani, Mario Paternina, Daniel Dotta

TL;DR
This paper introduces a fully data-driven method to estimate the center of inertia and regional inertia in power systems, accounting for load contributions and disturbances, using TDA and ARMAX techniques.
Contribution
It presents a novel approach combining typicality-based data analysis and ARMAX modeling to accurately estimate regional inertia and the COI displacement due to load effects.
Findings
Method accurately estimates regional inertia in benchmark systems.
Effective in capturing COI displacement during disturbances.
Validated on IEEE 68-bus system with load aggregation.
Abstract
This paper proposes a new comprehensive and fully data-driven methodology to estimate the center of inertia (COI) and the regional inertia, considering the displacement of the COI due to disturbances and load inertial contributions. The strategy uses the typicality-based data analysis (TDA) technique to detect the right pilot-bus that represents the COI. In the TDA, a compound of correlation and cosine similarities is implemented to approximate the actual distribution of the data and find the point (bus) closest to the mean which is elected as the pilot-bus. Then, the frequency response at the pilot-bus and the active power deviations are embedded into an autoregressive moving average exogenous input (ARMAX)-based approach to determine the regional inertia represented by an equivalent machine, whose inertia constant corresponds to the inertial contribution in the Region. % the This is…
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Taxonomy
TopicsStructural Health Monitoring Techniques · Energy Load and Power Forecasting · Machine Fault Diagnosis Techniques
MethodsTest
