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: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Institute of Advanced Engineering and Science
2024
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| Online Access: | http://eprints.utem.edu.my/id/eprint/28143/2/01753240920242131161164.pdf http://eprints.utem.edu.my/id/eprint/28143/ https://beei.org/index.php/EEI/article/view/7808 https://doi.org/10.11591/eei.v13i6.7808 |
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| Summary: | 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. |
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