Load Profile Analysis of Electricity Customer Using Adaline Based Clustering Algorithm
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2015, Vol 3, Issue 3
Abstract
This paper deals with the classification of electricity customers on the basis of their electrical behavior. Client classification may also be used for an integrated planning system, by considering the load-management alternatives which will be enforced to effectively meet the system demand. Therefore, this project proposes a stability index for selecting the foremost appropriate clustering algorithm and a priority index for determining the priority rank of clusters. ADLALINE based neural network clustering algorithm, an analysis approach is bestowed to demonstrate the utilization of these indices. Within the approach, all load curves of shoppers are first clustered with the clustering algorithms beneath a serial given range of clusters. Each customer class is then represented by its load profile. We tend to use the load profiles to check the margins left to a distribution company for fixing dedicated tariffs to every client category.
Authors and Affiliations
Vijayakumari M, Sundararajan D
Keywords
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- EP ID EP20026
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