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Jamal Moshtagh

Jamal Moshtagh

Academic rank: Professor
ORCID:
Education: PhD.
ScopusId: 11338807100
Faculty: Faculty of Engineering
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Research

Title
Load and Harmonic Forecasting for Optimal Transformer Loading and Life Time by Artificial Neural Network
Type
JournalPaper
Keywords
Artificial Neural Network. Transformer Loss and Life; Load Ability; Harmonic Orders
Year
2016
Journal Journal of Advances in Computer Research
DOI
Researchers S.Mohammad Bagher Sadati ، Jamal Moshtagh ، Abdollah rastgou

Abstract

Proper operations of transformer have several issues such as; preventing of unscheduled removal’s, increasing of reliability and continues supply of consumer demand. This result would be obtained that load and harmonic orders of sensitivity transformer at intervals appropriate for next hours and days is predicted to by selecting optimal utilization coefficient, reduction life of transformer is prevented. A possible solution for load and harmonic orders forecasting is implementation of heuristically algorithm and method such as Artificial Neural Network (ANN). In this paper, firstly relationship between transformer loss and life and effect of harmonic on its, is evaluated. Then by ANN method, load and harmonic orders of 400KVA distribution transformer is predicted. Then by using of existing standards and programs written in MATLAB environment, Load ability or optimal utilization coefficient and life of transformer is calculated.