Cyber Times International Journal of Technology & Management

This paper shows the classification of load profile of different types of electricity customers. Prediction of electricity demand for future years is an essential step. To classify the huge amount of load profile is difficult. For this purpose different clustering techniques are available. In this paper for clustering the huge amount of data k-means clustering and extended k-means algorithm are used. The results shows that the proposed method is efficient for distributing Load Profile to the consumers and also shows that the energy consumption can be clustered not only based on the hourly based load curve but also on load value. This paper shows the work on extended k-means clustering algorithm which is helpful for improve the execution time of algorithm.