Distribution System Intelligent State Estimation through Minimal Meter Placement

L. Ramesh (India), S. Chowdhury, S.P. Chowdhury, and C.T. Gaunt (South Africa)


ANN, distribution state estimation, hybrid particle swarm optimization and meter placement.


Accurate estimation of electrical parameters is very essential for proper operation of distribution automation systems for power distribution networks. This paper deals with identifying meter location, monitoring and estimating the parameters in distribution system. A particle swarm optimization (PSO) algorithm is developed to identify the meter placement positions. The locations determined thus are used to monitor and estimate the parameters through SCADA arrangement. The parameter values are estimated with the help of Hybrid Artificial Neural Network (ANN) based state estimation technique injecting pseudo measurements at un-metered buses. The algorithm and simulation is tested with IEEE 13 node system and a typical distribution system of Tamil Nadu Electrical Board in India.

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