Slow coherency is one of the most relevant concepts used in power systems dynamics to group generators that exhibit similar response to disturbances. Among the approaches developed for generator grouping based on slow coherency, clustering algorithms play a significant role. This paper reviews the clustering algorithms applied in model-based and data-driven approaches, highlighting the metrics used, the feature selection, the types of algorithms and the comparison among the results obtained considering simulated or measured data.
Review of Clustering Methods for Slow Coherency-Based Generator Grouping / Chicco, Gianfranco. - In: ENERGY SYSTEMS RESEARCH. - ISSN 2618-9992. - ELETTRONICO. - 4:2(2021), pp. 5-20. [10.38028/esr.2021.02.0001]
Review of Clustering Methods for Slow Coherency-Based Generator Grouping
Chicco, Gianfranco
2021
Abstract
Slow coherency is one of the most relevant concepts used in power systems dynamics to group generators that exhibit similar response to disturbances. Among the approaches developed for generator grouping based on slow coherency, clustering algorithms play a significant role. This paper reviews the clustering algorithms applied in model-based and data-driven approaches, highlighting the metrics used, the feature selection, the types of algorithms and the comparison among the results obtained considering simulated or measured data.File | Dimensione | Formato | |
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https://hdl.handle.net/11583/2963088