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Ιδρυματικό Αποθετήριο [SANDBOX]
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| URI | http://purl.tuc.gr/dl/dias/C741C6B5-DBB6-43B8-9A82-F7077D8FD63C | - |
| Αναγνωριστικό | https://doi.org/10.3390/en13123110 | - |
| Αναγνωριστικό | https://www.mdpi.com/1996-1073/13/12/3110/htm | - |
| Γλώσσα | en | - |
| Μέγεθος | 13 pages | el |
| Μέγεθος | 4,14 megabytes | en |
| Τίτλος | Effective electricity theft detection in power distribution grids using an adaptive neuro fuzzy inference system | en |
| Δημιουργός | Blazakis Konstantinos | en |
| Δημιουργός | Μπλαζακης Κωνσταντινος | el |
| Δημιουργός | Kapetanakis Theodoros N. | en |
| Δημιουργός | Stavrakakis Georgios | en |
| Δημιουργός | Σταυρακακης Γεωργιος | el |
| Εκδότης | MDPI | en |
| Περίληψη | Electric power grids are a crucial infrastructure for the proper operation of any country and must be preserved from various threats. Detection of illegal electricity power consumption is a crucial issue for distribution system operators (DSOs). Minimizing non-technical losses is a challenging task for the smooth operation of electrical power system in order to increase electricity provider’s and nation’s revenue and to enhance the reliability of electrical power grid. The widespread popularity of smart meters enables a large volume of electricity consumption data to be collected and new artificial intelligence technologies could be applied to take advantage of these data to solve the problem of power theft more efficiently. In this study, a robust artificial intelligence algorithm adaptive neuro fuzzy inference system (ANFIS)—with many applications in many various areas—is presented in brief and applied to achieve more effective detection of electric power theft. To the best of our knowledge, there are no studies yet that involve the application of ANFIS for the detection of power theft. The proposed technique is shown that if applied properly it could achieve very high success rates in various cases of fraudulent activities originating from unauthorized energy usage. | en |
| Τύπος | Peer-Reviewed Journal Publication | en |
| Τύπος | Δημοσίευση σε Περιοδικό με Κριτές | el |
| Άδεια Χρήσης | http://creativecommons.org/licenses/by/4.0/ | en |
| Ημερομηνία | 2022-03-02 | - |
| Ημερομηνία Δημοσίευσης | 2020 | - |
| Θεματική Κατηγορία | Data mining | en |
| Θεματική Κατηγορία | Adaptive neuro fuzzy inference system (ANFIS) | en |
| Θεματική Κατηγορία | Non-technical losses (NTLs) | en |
| Θεματική Κατηγορία | Power theft detection | en |
| Θεματική Κατηγορία | Smart grid | en |
| Θεματική Κατηγορία | Smart electricity metering | en |
| Θεματική Κατηγορία | Power distribution grids | en |
| Βιβλιογραφική Αναφορά | K. V. Blazakis, T. N. Kapetanakis, and G. S. Stavrakakis, “Effective electricity theft detection in power distribution grids using an adaptive neuro fuzzy inference system,” Energies, vol. 13, no. 12, June 2020, doi: 10.3390/en13123110 | en |
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