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 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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Publication Details

Journal
Bulletin of Electrical Engineering and Informatics
Published
2024-09-20
DOI
https://doi.org/10.11591/eei.v13i6.7808
Primary Topic
Optimal Power Flow Distribution
Type
article
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article

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

Nur Diana Izzani Masdzarif, Chin Kim Gan, Khairul Anwar Ibrahim, Mau Teng Au
Bulletin of Electrical Engineering and Informatics
Optimal Power Flow Distribution
article

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

Nur Diana Izzani Masdzarif, Chin Kim Gan, Khairul Anwar Ibrahim, Mau Teng Au
article en

Abstract

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.

Bulletin of Electrical Engineering and InformaticsVol. 13(6)
Affordable and clean energy
Openalex Percentile: Top 87%
Optimal Power Flow Distribution
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Power loss estimation utilizing the flexibility of peak power loss regression equations based on 11 kV base case feeder — Nur Diana Izzani Masdzarif, Chin Kim Gan, et al. · Bulletin of Electrical Engineering and Informatics (2024) | TGRS Research Map | TGRS