Coherency Approach by Hybrid PSO, K-Means Clustering Method in Power System
This paper presents a new method for recognition the identical behaviors of synchronous generators for particular fault location on power system. In this method, a hybrid algorithm combining particle swarm optimization (PSO) algorithm with k-means algorithm, also referred to PSO-KM algorithm is proposed to find the specified number of clusters in electric network. Each cluster represents a number of generators such that these generators named coherent generators. Clustering process is based on similarity of time domain data in transient stability studies. The new algorithm is evaluated on 39-Bus New England test system. Results show that the proposed algorithm has much potential in finding coherent generators.
M. Davodi et al., "Coherency Approach by Hybrid PSO, K-Means Clustering Method in Power System," Proceedinds of the 2008 IEEE 2nd International Power and Energy Conference (2008, Johor Bahru, Malaysia), pp. 1203-1207, Institute of Electrical and Electronics Engineers (IEEE), Dec 2008.
The definitive version is available at https://doi.org/10.1109/PECON.2008.4762659
2008 IEEE 2nd International Power and Energy Conference PECon 2008 (2008: Dec. 1-3, Johor Bahru, Malaysia)
Electrical and Computer Engineering
Keywords and Phrases
Clustering Algorithms; Electric Power Transmission Networks; Power Transmission; Synchronous Generators; Clustering; Clustering Process; Coherency; Coherent Generators; Electric Networks; Fault Locations; Hybrid Algorithms; Hybrid Pso; K-Means; K-Means Algorithms; K-Means Clustering Methods; New England Test Systems; Number of Clusters; Particle Swarm Optimization Algorithms; Power Systems; Time-Domain Datum; Transient Stabilities; Particle Swarm Optimization (PSO)
International Standard Book Number (ISBN)
Article - Conference proceedings
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