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All Journal International Journal of Applied Power Engineering (IJAPE)
Sushmita Poudel
Pokhara University
Electrical & Electronics Engineering

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Artificial intelligence for energy fraud detection: a review Sushmita Poudel; Udaya Raj Dhungana
International Journal of Applied Power Engineering (IJAPE) Vol 11, No 2: June 2022
Publisher : Institute of Advanced Engineering and Science

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (616.336 KB) | DOI: 10.11591/ijape.v11.i2.pp109-119

Abstract

Energy fraud in the distribution sector of electric utility includes electricity theft, meter tampering, or billing error. This fraud causing non-technical loss has led to an economic loss of the company. In order to detect and minimize fraud, different technologies have been used. From conventional methods to development in the field of artificial intelligence (AI), effective and reliable fraud detection methods have been proposed. This paper first provides an overview of different proposed methods for non-technical loss detection and evaluate the advantage and limitation of using those methods. Furthermore, several supervised and unsupervised machine learning methods for detecting electricity theft are discussed in summary along with their metrics and attributes used. Finally, these methods are classified based on the overall operation and the parameters used. This paper provides comparisons of several fraud detection methods using AI along with their weak and strong points and this information is very useful for the researchers who are working in the field of AI method for detecting fraud.
Co-Authors Udaya Raj Dhungana