Intelligent approach for efficient operation of electrical distribution automation systems

The distribution systems play a vital role in making efficient service in terms of power quality, reliability, and economy. The distribution network reconfiguration can be used for planning as well as real time control. This paper presents an efficient approach for network reconfiguration approach based on artifical neuran networks. A package "DISTFLOW" is developed adopting the proposed technique. The off-line simulation results and daily load curve data are used for training of the neural network. Further the distribution system operation is optimized by selecting optimum compensation level computed by Genetic Algorithms (G.A). The proposed integrated approach is applied to 140 bus practical system of Surathkal city subdivision, of the power utility Mangalor electricity supply company (MESCOM).