Determining The Contributing Factors and Their Impact on Technical Losses of a Secondary Distribution Network

Purpose: The need to investigate how much each factor contributes to the total distribution of technical losses is evident. This work seeks to find the extent of each possible factor's contribution. Design/Methodology/ Approach: The research is designed as an experimental-quantitative. 40 randomly selected LV networks in urban, rural and metropolitan areas were modelled on the OpenDSS platform, and steady-state load flow studies were carried out. 14 no. predictors were then extracted as input to a regression analysis to formulate a regression equation that could be used to develop a loss reduction strategy for each network. Findings: It has been identified that seven predictors are responsible for high technical losses. Based on the statistical significance of the predictors, they could be categorised into three categories: Average Phase Current and Average Load Power Factor, which fall within the first category. Average line Resistance (Ohms/km) and % Voltage Imbalance fall within the second category. The third category's predictions are the Equivalent Load Distance (km), Average Bus Voltage (V) and Line Average Percentage loading. Research Limitation: This work has limitations, such as the customer load profile not being available and losses related to transformers not being considered. Some equipment's electric characteristics were unavailable, so similar ones were used. However, these limitations do not distort the results of this research. Practical Implication: Therefore, a more appropriate strategy for loss reduction could be formulated by determining the characteristics of individual networks. Social Implication: Reducing these losses lessens the overall demand for power generation, leading to lower greenhouse gas emissions and reduced environmental impact. This supports broader sustainable development goals and helps meet national and global climate targets. Originality/Value: Every network has peculiar characteristics; therefore, a generalised loss reduction strategy will not yield the needed results for all circuits. A regression expression has been made to serve as a guide in determining the primary causes of high technical losses of any LV network.

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Publication Details

Journal
African Journal Of Applied Research
Published
2025-04-13
DOI
https://doi.org/10.26437/ajar.v11i2.995
Primary Topic
Power System Reliability and Maintenance
Type
article
Field-Weighted Citation Impact
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article

Determining The Contributing Factors and Their Impact on Technical Losses of a Secondary Distribution Network

Philip Amoah, J. E. Essilfie
African Journal Of Applied Research
Power System Reliability and Maintenance
article

Determining The Contributing Factors and Their Impact on Technical Losses of a Secondary Distribution Network

Philip Amoah, J. E. Essilfie
article en

Abstract

Purpose: The need to investigate how much each factor contributes to the total distribution of technical losses is evident. This work seeks to find the extent of each possible factor's contribution. Design/Methodology/ Approach: The research is designed as an experimental-quantitative. 40 randomly selected LV networks in urban, rural and metropolitan areas were modelled on the OpenDSS platform, and steady-state load flow studies were carried out. 14 no. predictors were then extracted as input to a regression analysis to formulate a regression equation that could be used to develop a loss reduction strategy for each network. Findings: It has been identified that seven predictors are responsible for high technical losses. Based on the statistical significance of the predictors, they could be categorised into three categories: Average Phase Current and Average Load Power Factor, which fall within the first category. Average line Resistance (Ohms/km) and % Voltage Imbalance fall within the second category. The third category's predictions are the Equivalent Load Distance (km), Average Bus Voltage (V) and Line Average Percentage loading. Research Limitation: This work has limitations, such as the customer load profile not being available and losses related to transformers not being considered. Some equipment's electric characteristics were unavailable, so similar ones were used. However, these limitations do not distort the results of this research. Practical Implication: Therefore, a more appropriate strategy for loss reduction could be formulated by determining the characteristics of individual networks. Social Implication: Reducing these losses lessens the overall demand for power generation, leading to lower greenhouse gas emissions and reduced environmental impact. This supports broader sustainable development goals and helps meet national and global climate targets. Originality/Value: Every network has peculiar characteristics; therefore, a generalised loss reduction strategy will not yield the needed results for all circuits. A regression expression has been made to serve as a guide in determining the primary causes of high technical losses of any LV network.

African Journal Of Applied ResearchVol. 11(2)
Pentecost University College (GH)
Openalex Percentile: Top 92%
Power System Reliability and Maintenance
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