Estimation of Working Error of Electricity Meter Using Artificial Neural Network (ANN)
Together with the rapidly growing world population and increasing usage of electrical equipment, the demand for electrical energy has continuously increased the demand for electrical energy. For this reason, especially considering the increasing inflation rates around the world, using an electricity...
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MDPI AG
2025-03-01
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| Series: | Energies |
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| Online Access: | https://www.mdpi.com/1996-1073/18/5/1265 |
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| author | Murat Tasci Hidir Duzkaya |
| author_facet | Murat Tasci Hidir Duzkaya |
| author_sort | Murat Tasci |
| collection | DOAJ |
| description | Together with the rapidly growing world population and increasing usage of electrical equipment, the demand for electrical energy has continuously increased the demand for electrical energy. For this reason, especially considering the increasing inflation rates around the world, using an electricity energy meter, which works with the least operating error, has great economic importance. In this study, an artificial neural network (ANN)-based prediction methodology is presented to estimate an active electricity meter’s combined maximum error rate by using variable factors such as current, voltage, temperature, and power factor that affect the maximum permissible error. The estimation results obtained with the developed ANN model are evaluated statistically, and then the suitability and accuracy of the presented approach are tested. At the end of this research, it is understood that the obtained results can be used by high accuracy rate to estimate the combined maximum working error of an active electricity energy meter with the help of a suitable ANN model based on the internal variable factors. |
| format | Article |
| id | doaj-art-bfbc6d6abaf34aea8fb061412220badd |
| institution | DOAJ |
| issn | 1996-1073 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Energies |
| spelling | doaj-art-bfbc6d6abaf34aea8fb061412220badd2025-08-20T02:59:14ZengMDPI AGEnergies1996-10732025-03-01185126510.3390/en18051265Estimation of Working Error of Electricity Meter Using Artificial Neural Network (ANN)Murat Tasci0Hidir Duzkaya1The Ministry of Industry and Technology, Directorate of General for Metrology and Industrial Product Safety, 06530 Ankara, TürkiyeDepartment of Electrical-Electronics Engineering, Faculty of Engineering, Gazi University, 06570 Ankara, TürkiyeTogether with the rapidly growing world population and increasing usage of electrical equipment, the demand for electrical energy has continuously increased the demand for electrical energy. For this reason, especially considering the increasing inflation rates around the world, using an electricity energy meter, which works with the least operating error, has great economic importance. In this study, an artificial neural network (ANN)-based prediction methodology is presented to estimate an active electricity meter’s combined maximum error rate by using variable factors such as current, voltage, temperature, and power factor that affect the maximum permissible error. The estimation results obtained with the developed ANN model are evaluated statistically, and then the suitability and accuracy of the presented approach are tested. At the end of this research, it is understood that the obtained results can be used by high accuracy rate to estimate the combined maximum working error of an active electricity energy meter with the help of a suitable ANN model based on the internal variable factors.https://www.mdpi.com/1996-1073/18/5/1265artificial neural networkcombined maximum working errorelectricity metermetrology |
| spellingShingle | Murat Tasci Hidir Duzkaya Estimation of Working Error of Electricity Meter Using Artificial Neural Network (ANN) Energies artificial neural network combined maximum working error electricity meter metrology |
| title | Estimation of Working Error of Electricity Meter Using Artificial Neural Network (ANN) |
| title_full | Estimation of Working Error of Electricity Meter Using Artificial Neural Network (ANN) |
| title_fullStr | Estimation of Working Error of Electricity Meter Using Artificial Neural Network (ANN) |
| title_full_unstemmed | Estimation of Working Error of Electricity Meter Using Artificial Neural Network (ANN) |
| title_short | Estimation of Working Error of Electricity Meter Using Artificial Neural Network (ANN) |
| title_sort | estimation of working error of electricity meter using artificial neural network ann |
| topic | artificial neural network combined maximum working error electricity meter metrology |
| url | https://www.mdpi.com/1996-1073/18/5/1265 |
| work_keys_str_mv | AT murattasci estimationofworkingerrorofelectricitymeterusingartificialneuralnetworkann AT hidirduzkaya estimationofworkingerrorofelectricitymeterusingartificialneuralnetworkann |