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Power loss estimation utilizing the flexibility of peak power loss regression equations based on 11 kV base case feeder

Distribution network feeder characteristics can typically be divided into groups based on factors including length, load distribution along the feeder, peak demand, installed capacity, and load profile. By comparing the parameters to those of similar feeders with known losses, it is usually possible...

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Main Authors: Masdzarif N.D.I., Ibrahim K.A., Gan C.K., Au M.T.
Other Authors: 58157291600
Format: Article
Published: Institute of Advanced Engineering and Science 2025
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spelling my.uniten.dspace-360952025-03-03T15:41:22Z Power loss estimation utilizing the flexibility of peak power loss regression equations based on 11 kV base case feeder Masdzarif N.D.I. Ibrahim K.A. Gan C.K. Au M.T. 58157291600 55337003600 35179398400 9742020600 Distribution network feeder characteristics can typically be divided into groups based on factors including length, load distribution along the feeder, peak demand, installed capacity, and load profile. By comparing the parameters to those of similar feeders with known losses, it is usually possible to predict the power losses and technical losses (TL) of the respective feeders pretty accurately. However, it is exceedingly difficult and time-consuming to estimate the losses with various variables and characteristics over such a large area. This paper proposed that through base case feeder modeling and simulation utilizing typical network and load data, feeders? peak power loss (PPL) functions can be established as a simple and effective power loss estimation method. Hence, the least time-consuming way of using a PPL regression equation based on a base case feeder is established in this paper to estimate the losses. The flexibility of PPL is proven through the case study. In the end, the results obtained between PPL and peak power demand (PPD) are demonstrated to be precisely proportional and the method is proven as a simple power loss estimation method due to the flexibility of the PPL regression equation. ? 2024, Institute of Advanced Engineering and Science. All rights reserved. Final 2025-03-03T07:41:22Z 2025-03-03T07:41:22Z 2024 Article 10.11591/eei.v13i6.7808 2-s2.0-85205271971 https://www.scopus.com/inward/record.uri?eid=2-s2.0-85205271971&doi=10.11591%2feei.v13i6.7808&partnerID=40&md5=bda55016c3d1de3e3826774fd4170c8f https://irepository.uniten.edu.my/handle/123456789/36095 13 6 3880 3887 Institute of Advanced Engineering and Science Scopus
institution Universiti Tenaga Nasional
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description Distribution network feeder characteristics can typically be divided into groups based on factors including length, load distribution along the feeder, peak demand, installed capacity, and load profile. By comparing the parameters to those of similar feeders with known losses, it is usually possible to predict the power losses and technical losses (TL) of the respective feeders pretty accurately. However, it is exceedingly difficult and time-consuming to estimate the losses with various variables and characteristics over such a large area. This paper proposed that through base case feeder modeling and simulation utilizing typical network and load data, feeders? peak power loss (PPL) functions can be established as a simple and effective power loss estimation method. Hence, the least time-consuming way of using a PPL regression equation based on a base case feeder is established in this paper to estimate the losses. The flexibility of PPL is proven through the case study. In the end, the results obtained between PPL and peak power demand (PPD) are demonstrated to be precisely proportional and the method is proven as a simple power loss estimation method due to the flexibility of the PPL regression equation. ? 2024, Institute of Advanced Engineering and Science. All rights reserved.
author2 58157291600
author_facet 58157291600
Masdzarif N.D.I.
Ibrahim K.A.
Gan C.K.
Au M.T.
format Article
author Masdzarif N.D.I.
Ibrahim K.A.
Gan C.K.
Au M.T.
spellingShingle Masdzarif N.D.I.
Ibrahim K.A.
Gan C.K.
Au M.T.
Power loss estimation utilizing the flexibility of peak power loss regression equations based on 11 kV base case feeder
author_sort Masdzarif N.D.I.
title Power loss estimation utilizing the flexibility of peak power loss regression equations based on 11 kV base case feeder
title_short Power loss estimation utilizing the flexibility of peak power loss regression equations based on 11 kV base case feeder
title_full Power loss estimation utilizing the flexibility of peak power loss regression equations based on 11 kV base case feeder
title_fullStr Power loss estimation utilizing the flexibility of peak power loss regression equations based on 11 kV base case feeder
title_full_unstemmed Power loss estimation utilizing the flexibility of peak power loss regression equations based on 11 kV base case feeder
title_sort power loss estimation utilizing the flexibility of peak power loss regression equations based on 11 kv base case feeder
publisher Institute of Advanced Engineering and Science
publishDate 2025
_version_ 1825816012269813760
score 13.244413

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