Abstract—Power system has a highly interconnected network that requires intense computational effort and resources for centralised control. Distributed computing is a solution to this and needs the systems to be partitioned optimally into clusters. The network partitioning is an optimization problem whose objective is to minimise the number of nodes in a cluster and the tie lines between the clusters. Evolutionary Algorithms like Discrete Particle Swarm Optimization (DPSO) and Harmony Search (HS) Algorithm is proposed to solve this combinatorial optimization problem. Connectivity of the partitioned networks is done using the conventional graph traversing techniques. Simulation is done on IEEE Standard Test Systems and IEEE 118 bus system case study is presented in this paper. The algorithms are found to be very efficeint in partitioning the system hierarchically and obtain a near optimal sub networks without having any isolated nodes.
Index Terms—Discrete Particle Swarm Optimization, Harmony Search Algorithm, Network Decomposition, Optimal Partitioning.
G. Angeline Ezhilarasi is with Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai, 600036 INDIA (phone: +91-98407 28451; fax: +91 44 2257 4402; e-mail: angel.ezhil@gmail.com). Dr. K. S. Swarup is with Department of Electrical Engineering, Indian Institute of Technology Madras, Chennai, 600036 INDIA
Cite: G. Angeline Ezhilarasi and K Shanti Swarup, "Network Decomposition using Evolutionary Algorithms in Power Systems," International Journal of Machine Learning and Computing vol. 1, no. 1, pp. 93-99, 2011.