Justification of ice melting capacity on 6-10kV OPL distributing power networks based on fuzzy modeling

• Autorzy: Savchenko Oleksandr A. , Miroshnyk Oleksandr O. , Dubko Stanislav V. , Shchur Taras G. , Komada Paweł , Mussabekov Kanat

Identyfikatory

DOI

10.15199/48.2019.05.26

Warianty tytułu

PL

Uzasadnienie zdolności do topienia lodu w napowietrznej sieci rozdzielczej 6-10 kV w oparciu o modelowanie rozmyte

• Języki publikacji: EN

Abstrakty

EN

We developed a fuzzy technical and economic model for optimization the parameters of the ice melting schemes at 6-10 kV OPL of distribution power networks based on which we justified the value of ice melting deposits fusion power, taking into account the uncertainty of initial data.

PL

Opracowano rozmyty model techniczny i ekonomiczny do optymalizacji parametrów schematów topienia lodu w napowietrznych sieciach dystrybucyjnych o napięciu 6-10 kV. Na podstawie tych modeli uzasadniono wartość mocy potrzebnej do stopnienia osadzonego lodu, biorąc pod uwagę niepewność danych początkowych.

Słowa kluczowe

EN

melting of ice; fuzzy set; electric network

PL

topnienie lodu; zbiór rozmyty; sieć elektryczna

• Wydawca: Wydawnictwo SIGMA-NOT
• Czasopismo: Przegląd Elektrotechniczny
• Rocznik: 2019
• Tom: R. 95, nr 5
• Strony: 106--109
• Opis fizyczny: Bibliogr. 16 poz., rys., tab.

Twórcy

autor

Savchenko Oleksandr A.

• Kharkiv Petro Vasylenko National Technical University of Agriculture, Alchevskh, 44, Kharkiv, 61002 Ukraine

autor

Miroshnyk Oleksandr O.

• Kharkiv Petro Vasylenko National Technical University of Agriculture, Alchevskh, 44, Kharkiv, 61002 Ukraine

autor

Dubko Stanislav V.

• Kharkiv Petro Vasylenko National Technical University of Agriculture, Alchevskh, 44, Kharkiv, 61002 Ukraine

autor

Shchur Taras G.

• Lviv National Agricultural University, St. Vladimir the Great, 1, Dublyany, Ukraine

autor

Komada Paweł

• Lublin University of Technology, Institute of Electronics and Information Technology, Nadbystrzycka 38A, 20618 Lublin, Poland

autor

Mussabekov Kanat

• Kazakh Academy of Transport & Communication

Bibliografia

• 1. Farzaneh M., Volat C., Leblond A., Anti-icing and De-icing Techniques for Overhead Lines, Atmospheric Icing of Power Networks Springer, (2008), 229–268
• 2. Scientific and technical report on the topic "Choice of methods and development of suitable schemes for ice melting on the HVL of various voltage classes in the Moldovan energy system" – Chisinau: STC "TehnikaInenergo", 2001.
• 3. Rudakova R., Vavilova I., Golubkov I., Fighting against ice-cold in power grid enterprises: Handbook for organizing the fight against ice / R. Rudakova, I. Vavilova, I. Golubkov – Ufa: OAO Bashkirenergo, Ufa. State Techn. Univ, 1995.
• 4. Toliupa S., Kravchenko Y., Trush A., Organization of implementation of ubiquitous sensor networks, Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska - IAPGOS, 8(2018), no. 1., 36-39.
• 5. Bilash I., Savchenko O., Optimization of the ice melting power on the OPL 6-10 kV distribution electrical networks, Problems of power supply and energy saving in the agroindustrial complex of Ukraine, 101(2010), 31–38.
• 6. Mauris G., Lassere V., Foulley L., A fuzzy approach for the expression of uncertainty in measurement, Measurement, (2001), no. 29., 109–121.
• 7. Wojcik W, Bieganski T., Kotyra A., et al., Application of algorithms of forecasting in the optical fibre coal dust burner monitoring system, Proc. SPIE, 3189 (1997), 100-109.
• 8. Tymchuk S., Miroshnyk O., Svergun Y., Avramenko A., Fuzzy assessment of asymmetric modes of rural networks 0,38 / 0,22 kV, Problems of energy supplying and energy saving in the agroindustrial complex of Ukraine 142(2013), 42–44.
• 9. Kłosowski G., Rymarczyk T., Using neural networks and deep learning algorithms in electrical impedance tomography, Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska - IAPGOS, 7(2017), no. 3., 99-102.
• 10. Hsiao-Fan W., Ruey-Chyn T., Insight of a fuzzy regression model, Fuzzy Sets and Systems, 112 (2000), no. 3, 355–369.
• 11. Asai K., Wadada D., Iwai S. et al., Applied fuzzy systems, Moscow: Mir, (1993)
• 12. Savchenko O., Investigation of the ice melting on a group of interconnected 6–10 kV OPL on the basis of simulation modeling, Problems of power supply and energy conservation in the AIC of Ukraine, 101(2010), 53–55.
• 13. Miroshnyk O. Tymchuk S., Determination of electric power losses depending on its quality in fuzzy form in rural distribution networks, Eastern-European Journal of Enterprise Technologies, 73(2015), no. 1/8, 4-10.
• 14. Diligensky N., Dymova L., Sevastyanov P., Fuzzy modeling and multicriteria optimization of production systems under uncertainty: technology, economics, ecology, Mechanical Engineering, (2004), 397.
• 15. Buckley J.J., Buckley T.F., Linear and non-linear fuzzy regression: Evolutionary algorithm solutions, Fuzzy Sets and Systems, 112(2000) – no. 3, 381–394.
• 16. Mauris G., Berrah L., Foulloy L., Haurat A., Fuzzy handling of measurement errors in instrumentation, IEEE Transaction and measurement, 49(2000), no.1, 43–58

Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).