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• W2914271106 abstract "The proposed distributed dynamic clustering algorithm enables to group agents based on their pre-selected feature states. The clusters are determined by comparing the distance of the agents' current feature states with average estimates of the states in all clusters. The algorithm also provides average estimates of pre-selected auxiliary states that can be utilized for control purposes. Two example applications of the algorithm are introduced. In the first application, the algorithm is applied to a microgrid with distributed batteries that are controlled to achieve a common state of charge within a group. However, a random selection of the batteries' groups results in additional power losses during operation. The algorithm reduces the power losses by clustering the batteries based on the selected feature states: local loads and battery capacities, while the state of charges and output voltages are selected as auxiliary states for control purposes. In the second application, the algorithm is used to form a virtual energy storage from batteries distributed in a microgrid." @default.
• W2914271106 created "2019-02-21" @default.
• W2914271106 creator A5056736908 @default.
• W2914271106 creator A5061288483 @default.
• W2914271106 date "2019-01-28" @default.
• W2914271106 modified "2023-09-27" @default.
• W2914271106 title "A Novel Dynamic Peer-to-Peer Clustering Algorithm and Its Application to Aggregate Energy Storage Systems" @default.
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• W2914271106 doi "https://doi.org/10.48550/arxiv.1901.10029" @default.
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