Electricity Losses in Focus: Detection and Reduction Strategies—State of the Art

In contemporary society, electricity has become one of the most prevalent energy sources, with a global distribution network. The significance of energy efficiency has become a prominent subject of interest across various disciplines, leading to a notable surge in research on electricity over the last decade. The present paper explores the significance of examining power losses in power grids and proposes methods to identify and reduce them. The objective of this study is to methodically and systematically review existing databases to identify relevant studies pertinent to electricity losses in power grids. To this end, this study methodically categorizes energy losses into two primary classifications: technical losses and non-technical losses. To this end, two primary analytical approaches have been devised, providing a foundation for the prioritization of the most effective detection methods for each loss category, as well as the most recent findings in the literature on reducing these losses. The issue of power grid instability, stemming from fluctuations and voltage dips, was addressed, with power losses emerging as the primary source of concern. To this end, a comprehensive analysis of major academic databases, including Scopus, Web of Science, IEEE, and Google Scholar, was conducted to identify relevant research articles. This review introduces several important concepts for the energy field by introducing and analyzing the most relevant methods to identify and reduce power losses. The results of our study outlined the comprehensive analysis of 90 relevant studies on the benefits as well as the barriers encountered in the application of methods to identify and reduce electricity losses and the impact they have in the field under review. In conclusion, this paper emphasizes the importance of the in-depth study of the energy domain to achieve performance and contribute to the improvement of power grids. Future research directions are based on the implementation of artificial intelligence (AI) algorithms to achieve this goal.

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Publication Details

Journal
Applied Sciences
Published
2025-03-23
DOI
https://doi.org/10.3390/app15073517
Citations
3
Primary Topic
Non-Destructive Testing Techniques
Type
article
Field-Weighted Citation Impact
2.14
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article

Electricity Losses in Focus: Detection and Reduction Strategies—State of the Art

Horia G. Beleiu, Ceclan Andrei, Sorin G. Pavel, Daniela Florentina Niste et al.
3 citations
Applied Sciences
Non-Destructive Testing Techniques
2.14
article

Electricity Losses in Focus: Detection and Reduction Strategies—State of the Art

Horia G. Beleiu, Ceclan Andrei, Sorin G. Pavel, Daniela Florentina Niste, Marius Misaroș, Radu Tîrnovan
article en
3 citations

Abstract

In contemporary society, electricity has become one of the most prevalent energy sources, with a global distribution network. The significance of energy efficiency has become a prominent subject of interest across various disciplines, leading to a notable surge in research on electricity over the last decade. The present paper explores the significance of examining power losses in power grids and proposes methods to identify and reduce them. The objective of this study is to methodically and systematically review existing databases to identify relevant studies pertinent to electricity losses in power grids. To this end, this study methodically categorizes energy losses into two primary classifications: technical losses and non-technical losses. To this end, two primary analytical approaches have been devised, providing a foundation for the prioritization of the most effective detection methods for each loss category, as well as the most recent findings in the literature on reducing these losses. The issue of power grid instability, stemming from fluctuations and voltage dips, was addressed, with power losses emerging as the primary source of concern. To this end, a comprehensive analysis of major academic databases, including Scopus, Web of Science, IEEE, and Google Scholar, was conducted to identify relevant research articles. This review introduces several important concepts for the energy field by introducing and analyzing the most relevant methods to identify and reduce power losses. The results of our study outlined the comprehensive analysis of 90 relevant studies on the benefits as well as the barriers encountered in the application of methods to identify and reduce electricity losses and the impact they have in the field under review. In conclusion, this paper emphasizes the importance of the in-depth study of the energy domain to achieve performance and contribute to the improvement of power grids. Future research directions are based on the implementation of artificial intelligence (AI) algorithms to achieve this goal.

Applied SciencesVol. 15(7)
Technical University of Cluj-Napoca (RO)
Openalex Percentile: Top 15%
Non-Destructive Testing Techniques
2.14
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