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Tytuł artykułu

Optimal quality management algorithm for assessing the usage capacity level of mining transformers

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Warianty tytułu
PL
Optymalny algorytm zarządzania jakością do oceny wydajności poziomu transformatorów górniczych
Języki publikacji
EN
Abstrakty
EN
In order to establish if a transformer corresponds to the requirements of the power network, it is mandatory to know the consumption characteristics. Heretofore, the determination of load level of transformers was performed based on technical-economic criteria. However, for the situation in which the real load would be equal to the one resulting from calculations, this fact would be valid only for a short time period, maximum two years, but the calculation based on the total updated expenditure is performed for a twenty years period, in which it is more than certain that the load will undergo variations within certain limits compared to the initial one. The central theme of this paper is represented by the development of an optimal quality management algorithm for assessing the load of transformers, which provides more information related to the economic usage capacity level, the value of power losses, economic transient power, possible over-voltages, the pricing of energy and charging of energy losses. In the end, results have been simulated for three series of mining transformers with different transformation ratios.
PL
W celu ustalenia, czy transformator odpowiada wymaganiom sieci energetycznej, obowiązkowe jest poznanie charakterystyki zużycia. Dotychczas wyznaczanie poziomu obciążenia transformatorów odbywało się w oparciu o kryteria techniczno-ekonomiczne. Jednakże w sytuacji, w której rzeczywiste obciążenie byłoby równe wynikowi wynikającemu z obliczeń, fakt ten byłby ważny tylko przez krótki okres, maksymalnie dwa lata, ale obliczenia oparte na całkowitych zaktualizowanych wydatkach są dokonywane dla dwudziestu, w okresie, w którym jest więcej niż pewne, że obciążenie ulegnie zmianom w pewnych granicach w porównaniu z okresem początkowym. Głównym tematem tego artykułu jest opracowanie optymalnego algorytmu zarządzania jakością do oceny obciążenia transformatorów, który dostarcza więcej informacji dotyczących ekonomicznego poziomu wykorzystania mocy, wartości strat mocy, ekonomicznej przejściowej mocy, możliwych przepięć, wycena energii i pobieranie strat energii. W efekcie symulowano wyniki dla trzech serii transformatorów górniczych o różnych współczynnikach transformacji.
Rocznik
Strony
233--244
Opis fizyczny
Bibliogr. 20 poz., rys., tab.
Twórcy
autor
  • Department of Automation, Computers, Electrical Engineering and Power Engineering, Faculty of Mechanical and Electrical Engineering, University of Petrosani, Romania
autor
  • Czestochowa University of Technology, Management Faculty, Poland
  • Department of Automation, Computers, Electrical Engineering and Power Engineering, Faculty of Mechanical and Electrical Engineering, University of Petrosani, Romania
  • Laboratory for International Projects and Cooperation, National R&D Institute for Mine Safety and Protection to Explosion - INSEMEX, Petrosani, Romania
autor
  • Scientific Research and International Cooperation, University of Petrosani, Romania
Bibliografia
  • 1. Abrham J., 2017, Project management and funding in the Euroregions, “Polish Journal of Management Studies”, 16(1).
  • 2. Goh Y.M., Lover P.E.D., Brown H., Spickett J., 2012, Organizational accidents: a systemic model of production versus protection, “Journal of Management Studies”, 49(1).
  • 3. Jahromi M.G., Mirzaeva G., Mitchell S.D., 2017, Design and control of a high-power low-loss DC-DC converter for mining applications, IEEE Transactions on Industry Applications, 53(5).
  • 4. Janekova J., Fabianova J., Onofrejova D., Puskas E., Busa M., 2017, Implementation of deviation analysis method in the utilisation phase of the investment project: a case study, “Polish Journal of Management Studies”, 15(1).
  • 5. Kalenova S., Onyusheva I., Yerubayeva G., 2017, The contemporary state of eco-economy of Kazakhstan: Problems and solutions, “International Journal of Ecological Economics and Statistics”, 38 (2)
  • 6. Lenka S., 2017, The relationship between company returns and leverage depending on the business sector: empirical evidence from the Czech Republic, “Journal of Competitiveness”, 9(3).
  • 7. Liang Z.L., Parlikad A.K., 2015, A condition-based maintenance model for assets with accelerated deterioration due to fault propagation, IEEE Transactions on Reliability, 64(3).
  • 8. Mikita M., Kolcun M., Spes M., Voktek M., Ivancak M., 2017, Impact of electrical power load time management at sizing and cost of hybrid renewable power system, “Polish Journal of Management Studies”, 15(1).
  • 9. Misak S., Fulnecek J., 2017, The influence of ferroresonance on a temperature of voltage transformers in undeground mines, [In:] Proceedings of the 2017 18th International Scientific Conference on Electric Power Engineering (EPE), May 17-19, Kouty nad Desnou, Czech Republic.
  • 10. Mokhova N., Zinecker M., Meluzin T., 2018, Internal factors influencing the cost of equity capital, Entrepreneurship and Sustainability Issues, 5(4).
  • 11. Niculescu T., Pasculescu D., Pasculescu V.M., Stoica I.O., 2014, Evaluation of electrical parameters of intrinsic safety barriers of the electrical equipment intended to be used in atmospheres with explosion hazard, [In:] Geoconference on informatics, geoinformatics and remote sensing, vol. I, 14th International Multidisciplinary Scientific Geoconference (SGEM), June 17-26, Albena, Bulgaria.
  • 12. Oláh J., Nestler S., Nobel T., Popp J., 2018, International characteristics of the macro-logistics system of freight villages, “Periodica Polytechnica Transportation Engineering”, 46(4).
  • 13. Oommen M.P., Kohler J.L., 1999, Effect of three-winding transformer models on the analysis and protection of mine power systems, IEEE Transactions on Industry Applications, 35(3).
  • 14. Pana L., 2006, Tehnici de optimizare în sistemele electroenergetice miniere, Editura Focus, Petroşani, Romania.
  • 15. Pasculescu V.M., Pricop D.G., Morar M.S., Florea V.A., 2015, Research on the development of an expert system for selecting technical equipment intended to be used in potentially explosive atmospheres, [In:] Informatics, Geoinformatics and Remote Sensing, Vol. I, 15th International Multidisciplinary Scientific Geoconference (SGEM), June 18-24, Albena, Bulgaria.
  • 16. Pasculescu V.M., Vlasin N.I., Suvar M.C., Lupu C., 2017, Decision support system for managing electrical equipment used in hazardous atmospheres, “Environmental Engineering and Management Journal”, 16.
  • 17. Power Engineering Guide, 2009, Edition 7. Available at: https://www.siemens.com/content/dam/internet/siemens-com/global/products-services/energy/high-voltage/transformers/brochures-transformers-en/siemens-transformers-in-the-power-engineering-guide-transformers-product-brochure.pdf
  • 18. Shaefiee M., Animah I., 2017, Life extension decision making of safety critical systems: An overview, “Journal of Loss Prevention in the Process Industries”, 47.
  • 19. Ulewicz R., 2016, Quality Management System Operation in the Woodworking Industry, International Conference on the Path Forward for Wood Products: A Global Perspective, “Proceedings of Scientific Papers”
  • 20. Wang D.M., Tee S.J., Liu Q., Wang Z.D., 2018, Factorial analysis for ageing assessment of in-service transformers, IET Generation Transmission & Distribution, 12(13).
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2018).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-72e161bb-a3c6-44da-aa6b-d9e6f416892b
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