Ensemble machine learning models for the detection of energy theft
Sign Up to like & getrecommendations! Published in 2020 at "Electric Power Systems Research"
DOI: 10.1016/j.epsr.2020.106904
Abstract: Abstract Advanced metering infrastructure allows the two-way sharing of information between smart meters and utilities. However, it makes smart grids more vulnerable to cyber-security threats such as energy theft. This study suggests ensemble machine learning… read more here.
Keywords: machine learning; learning models; energy; energy theft ... See more keywords
Unbalanced Data Handling Techniques for Classifying Energy Theft and Defective Meters in the Provincial Electricity Authority of Thailand
Sign Up to like & getrecommendations! Published in 2023 at "IEEE Access"
DOI: 10.1109/access.2023.3274543
Abstract: Energy theft and defective meters not only lead to non-technical losses (NTLs) that are extremely detrimental to energy distributors and power infrastructure, but NTLs are also a major cause of damages to electricity and massive… read more here.
Keywords: provincial electricity; energy; theft defective; unbalanced data ... See more keywords