Influence of Raw Data Temporal Resolution by Using Clustering Approach on Electricity Load Profile
Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2017, Vol 5, Issue 2
Abstract
The interest is increasing in contemplative conduct of electricity users in both the housing and retail zon with the approach of high solution time-sequence capacity requrement data through best metering, drilling this data could be valuable from the computational aspect. One of the trendy facility is clustering, but build upon on the algorithm the solution of the data can have an relevant control on the resulting clusters. This paper shows how suited solution of power capacity portrait affects the quality of the gather process, the texture of cluster participation (profiles exhibiting similar behavior), and the ability of the clustering process. This work uses both raw data from ordinary expenditure data and counterfeit profiles. The rationale for this work is to growth the clustering of electricity load profiles to help categorize user types for charge pattern and switching, fault and fraud find requirement-side manage and power ability measures. The vital for benchmark drilling very large data agree is how small information needs to be used to get a stable conclusion while manage solitude and preservation.
Authors and Affiliations
Miss Atole Neha Ravindra, Miss. Itape Aparna Balaso, Miss Palange Poonam Bharat, Miss. Shid Prachi Prakash
Keywords
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- EP ID EP23144
- DOI http://doi.org/10.22214/ijraset.2017.2055
- Views 295
- Downloads 5
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