Particle swarm optimization based K-means clustering approach for security assessment in power systems

Authors:
S. Kalyani;K. S. Swarup
Affiliations:
Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai 600 036, Tamilnadu, India;Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai 600 036, Tamilnadu, India
Venue:
Expert Systems with Applications: An International Journal
Year:
2011

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Abstract

Security assessment is a major concern in planning and operation studies of a power system. Conventional method of security evaluation performed by simulation involves long computer time and generates voluminous results. This paper presents a K-means clustering approach for classifying power system states as secure/insecure under a given operating condition and contingency. This paper demonstrates how the traditional K-means clustering algorithm can be profitably modified to be used as a classifier algorithm. The proposed algorithm combines particle swarm optimization (PSO) with the traditional K-means algorithm to satisfy the requirements of a classifier. The proposed PSO based K-means clustering technique is implemented in IEEE 30 Bus, 57 Bus, 118 Bus and 300 Bus standard test systems for static security and transient security evaluation. The simulation results of the proposed algorithm are compared with unsupervised K-means clustering, which uses different methods for cluster center initialization.