Chronological categorization and decomposition of customer loads
Nourbakhsh, Ghavameddin, Eden, Gary, McVeigh, Dylan, & Ghosh, Arindam (2012) Chronological categorization and decomposition of customer loads. IEEE Transactions on Power Delivery, 27(4), pp. 2270-2277.
The majority of distribution utilities do not have accurate information on the constituents of their loads. This information is very useful in managing and planning the network, adequately and economically. Customer loads are normally categorized in three main sectors: 1) residential; 2) industrial; and 3) commercial. In this paper, penalized least-squares regression and Euclidean distance methods are developed for this application to identify and quantify the makeup of a feeder load with unknown sectors/subsectors. This process is done on a monthly basis to account for seasonal and other load changes. The error between the actual and estimated load profiles are used as a benchmark of accuracy. This approach has shown to be accurate in identifying customer types in unknown load profiles, and is used in cross-validation of the results and initial assumptions.
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|Item Type:||Journal Article|
|Keywords:||Load modeling, load distribution, customer loads decomposition, Classification, K-means, clustering, decomposition, load profiling|
|ISSN:||1937-4208 (online) 0885-8977 (print)|
|Subjects:||Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > ELECTRICAL AND ELECTRONIC ENGINEERING (090600) > Power and Energy Systems Engineering (excl. Renewable Power) (090607)
Australian and New Zealand Standard Research Classification > ENGINEERING (090000) > ELECTRICAL AND ELECTRONIC ENGINEERING (090600) > Electrical and Electronic Engineering not elsewhere classified (090699)
|Divisions:||Current > Schools > School of Electrical Engineering & Computer Science
Current > QUT Faculties and Divisions > Science & Engineering Faculty
|Copyright Owner:||Copyright 2012 IEEE|
|Deposited On:||10 Feb 2013 23:22|
|Last Modified:||16 Feb 2013 07:29|
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