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IJSTR >> Volume 9 - Issue 6, June 2020 Edition

International Journal of Scientific & Technology Research  
International Journal of Scientific & Technology Research

Website: http://www.ijstr.org

ISSN 2277-8616

Optimization OF Energy Losses IN Oil Industry OF Mangystau Region

[Full Text]



Erzhanov Kaly, Kartbayev Amandyk



power distortion, electricity, neural networks, power quality, reactive power, higher harmonics.



The issue of efficient use of electric power due to a sharp increase in its cost is more pressing than ever. A reason requiring a reduction in electricity losses is the power networks that have exhausted their resource and can not manage the increased loads and need modernization. Optimization of electric power regime will help with reduction of production cost and preservation of competitiveness of enterprises. Currently, the main electricity consumers are non-linear, which cause distortions in the current and voltage curve, increase the level of reactive power, which in turn leads to additional losses of electrical energy and equipment failure. The most obvious solution of the problem is to reduce losses and increase network capacity. Neural networks were used to solve the task of optimizing the division of load of the most powerful electrical receivers by time to reduce peak load.



[1] T.N. Barchenko, R.I. Zakirov, Electrical supply of the industrial enterprises. Tomsk: TPI Publishing House, 1989.
[2] V.S. Medvedev, V.G. Potemkin, Neural Networks. MATLAB 6. Moscow: DIALOG MEPHI, 2002.
[3] P.S. Zhdanov, The Problems of Stability of Electric Systems, Moscow: Energia, 1979.
[4] A. Kartbayev, U. Tukeyev, S. Sheremeteva, A. Kalizhanova, B. Kalybek Uuly, Experimental study of neural network-based Word alignment selection model trained with Fourier descriptors. Journal of Theoretical and Applied Information Technology, vol.96, no.13., 2018, pp.4103-4113.
[5] A. Kartbayev, Refining Kazakh Word Alignment Using Simulation Modeling Methods for Statistical Machine Translation. Lecture Notes in Computer Science. Springer, Vol. 9362, 2015, pp. 421-427.
[6] Benn D.V., Farmer E.D. Sravnitelnye modeli prognozirovaniya elektricheskoy nagruzki. Moscow: Energoatomizdat, 1987.
[7] Y.S. Zhelezko. Loss of electricity. Reactive power. Electric power quality: Manual for practical calculations. Moscow: ENAS, 2009.
[8] T.T. Omorov, B.K. Takyrbashev. To the problem of the asymmetric operation modes optimization of the distribution networks. Devices and systems. Management, control, diagnostics, Issue 9, Moscow: Naukhtekhlitizdat Publishing House. 2016, pp.11-15.
[9] T.A. Sadykbek, R.E. Matov. Methods and Technical Tools of Improving the Electric Power Quality. Bulletin of the Kazakh Academy of Transport and Communications named after M. Tynyshpaev, Issue 6 (91). 2014, pp. 149-154.
[10] D. Srinivasan, Evolving artificial neural networks for short term load forecasting. Neuro Computing, Elsevier, Issue 23, 1998, pp.265–276.