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Pregled bibliografske jedinice broj: 805952

An Adaptive Neuro-Fuzzy Inference System in Assessment of Technical Losses in Distribution Networks


Mlakić, Dragan; Nikolovski, Srete; Knežević, Goran
An Adaptive Neuro-Fuzzy Inference System in Assessment of Technical Losses in Distribution Networks // International Journal of Electrical and Computer Engineering (Yogyakarta), 6 (2016), 3; 1294-1304 doi:10.11591/ijece.v6i3 (međunarodna recenzija, članak, znanstveni)


CROSBI ID: 805952 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
An Adaptive Neuro-Fuzzy Inference System in Assessment of Technical Losses in Distribution Networks

Autori
Mlakić, Dragan ; Nikolovski, Srete ; Knežević, Goran

Izvornik
International Journal of Electrical and Computer Engineering (Yogyakarta) (2088-8708) 6 (2016), 3; 1294-1304

Vrsta, podvrsta i kategorija rada
Radovi u časopisima, članak, znanstveni

Ključne riječi
Artificial intelligence ; Adaptive neuro-fuzzy inference system ; Technical losses ; Remote meter reading ; LV distribution network

Sažetak
The losses in distribution networks have always been key elements in predicting investment, planning work, evaluating the efficiency and effectiveness of a network. This paper elaborates on the use of fuzzy logic systems in analyzing the data from a particular substation area predicting losses in the low voltage network. The data collected from the field were obtained from the Automatic Meter Reading (AMR) and Automatic Meter Management (AMM) systems. The AMR system is fully implemented in EPHZHB and integrated within the network infrastructure at secondary level substations 35/10kV and 10(20)/0.4 kV. The AMM system is partially implemented in the areas of electrical energy consumers ; precisely, in accounting meters. Daily information gathered from these systems is of great value for the calculation of technical and non-technical losses. Fuzzy logic in combination with the Artificial Neural Networks implemented via the Adaptive Neuro-Fuzzy Inference System (ANFIS) is used. Finally, FIS Sugeno, FIS Mamdani and ANFIS are compared with the measured data from smart meters and presented with their errors and graphs.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika



POVEZANOST RADA


Ustanove:
Fakultet elektrotehnike, računarstva i informacijskih tehnologija Osijek

Profili:

Avatar Url Goran Knežević (autor)

Avatar Url Srete Nikolovski (autor)

Poveznice na cjeloviti tekst rada:

doi iaesjournal.com iaesjournal.com

Citiraj ovu publikaciju:

Mlakić, Dragan; Nikolovski, Srete; Knežević, Goran
An Adaptive Neuro-Fuzzy Inference System in Assessment of Technical Losses in Distribution Networks // International Journal of Electrical and Computer Engineering (Yogyakarta), 6 (2016), 3; 1294-1304 doi:10.11591/ijece.v6i3 (međunarodna recenzija, članak, znanstveni)
Mlakić, D., Nikolovski, S. & Knežević, G. (2016) An Adaptive Neuro-Fuzzy Inference System in Assessment of Technical Losses in Distribution Networks. International Journal of Electrical and Computer Engineering (Yogyakarta), 6 (3), 1294-1304 doi:10.11591/ijece.v6i3.
@article{article, author = {Mlaki\'{c}, Dragan and Nikolovski, Srete and Kne\v{z}evi\'{c}, Goran}, year = {2016}, pages = {1294-1304}, DOI = {10.11591/ijece.v6i3}, keywords = {Artificial intelligence, Adaptive neuro-fuzzy inference system, Technical losses, Remote meter reading, LV distribution network}, journal = {International Journal of Electrical and Computer Engineering (Yogyakarta)}, doi = {10.11591/ijece.v6i3}, volume = {6}, number = {3}, issn = {2088-8708}, title = {An Adaptive Neuro-Fuzzy Inference System in Assessment of Technical Losses in Distribution Networks}, keyword = {Artificial intelligence, Adaptive neuro-fuzzy inference system, Technical losses, Remote meter reading, LV distribution network} }
@article{article, author = {Mlaki\'{c}, Dragan and Nikolovski, Srete and Kne\v{z}evi\'{c}, Goran}, year = {2016}, pages = {1294-1304}, DOI = {10.11591/ijece.v6i3}, keywords = {Artificial intelligence, Adaptive neuro-fuzzy inference system, Technical losses, Remote meter reading, LV distribution network}, journal = {International Journal of Electrical and Computer Engineering (Yogyakarta)}, doi = {10.11591/ijece.v6i3}, volume = {6}, number = {3}, issn = {2088-8708}, title = {An Adaptive Neuro-Fuzzy Inference System in Assessment of Technical Losses in Distribution Networks}, keyword = {Artificial intelligence, Adaptive neuro-fuzzy inference system, Technical losses, Remote meter reading, LV distribution network} }

Časopis indeksira:


  • Scopus


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