Research into the influence of climatic factors on the losses of electric energy in overhead power transmission lines

Authors

DOI:

https://doi.org/10.15587/1729-4061.2016.80072

Keywords:

neural networks, electric power losses, overhead power transmission lines, climatic factors

Abstract

The problem of improving the accuracy in the calculations of technical energy losses in the overhead transmission lines of voltage 6–35 kV was examined by taking into account climatic factors. The influence of climatic factors on the losses of electricity in the overhead transmission lines of voltage 6–35 kV was explored. We improved the model of thermal processes in the PTL wires through a fuller account of meteofactors. The approaches to calculating the losses of active power in PTL were analyzed and examined. We substantiated expediency of applying the approach in which the losses are calculated taking into account the average monthly air temperature. It was investigated, calculated and proposed to include, in the basic equation of thermal balance for the PTL wires, the heat transfer coefficients that take into account the impact of precipitation (rain, snow). We improved the basic equation of thermal balance for sustained thermal mode for the PTL wires with regard to the proposed approach to the selection of temperature and calculated heat transfer coefficients at atmospheric precipitation on the surface of the wires. The expression is proposed for determining technical energy losses in the overhead PTL of voltage 6–35 kV. We designed a model of neural network for forecasting and calculating technical energy losses in the overhead power transmission lines of voltage 6–35 kV, which has advantages in comparison with traditional models and will make it possible to reduce error when calculating and forecasting load electric power losses in PTL.

Results of the study may be useful for forecasting and calculation of energy losses in the overhead PTL of voltage 6–35 kV in power supply and designing organizations.

Author Biography

Vladimir Bakulevskiy, Odessa National Academy of Food Technologies Kanatna str., 112, Odessa, Ukraine, 65039

Lecturer, Head of cyclic commission

Cycle commission of electrotechnical disciplines

Mechanics and Technology College of 

References

  1. The Cabinet of Ministers of Ukraine (1997). A comprehensive state program of energy saving in Ukraine.
  2. Krasovsky, P. Y. (2006). Factors affecting the dynamics of technical losses in power lines. Proceedings of the Dnipropetrovsk National Mining University, 76.
  3. Miroshnik, A. A. (2010). Refined algorithms for calculating the energy losses in networks 0,38 kV in real time. Regional energy issues, 2 (13), 35–42.
  4. Turbin, S. V. (2006). Improving methods for determining environmental loads on air routes taking into consideration subject topographical features of the area. Energy and Electrification, 3, 33–43.
  5. IEC 60287–2–2: 1995 Electric cables – Calculation of the current rating – Part 2: Thermal resistance – Section 2: A method for calculating reduction factors for groups of cables in free air, protected from solar radiation.
  6. Gupta, P., Yamada, K. (1972). Adaptive Short-Term Forecasting of Hourly Loads Using Weather Information. IEEE Transactions on Power Apparatus and Systems, PAS-91 (5), 2085–2094. doi: 10.1109/tpas.1972.293541
  7. Panuska, V. (1977). Short–term forecasting of electric power system load from a weather dependent model. IFAC Symp. Autom. Contr. and Prot. Electr. Power Syst., 414–418.
  8. Vorotnitsky, V. E., Turkina, O. V. (2008). Estimation of variable energy losses error in overhead lines because of the weather conditions neglect. Energy systems and electrical networks, 10, 42–49.
  9. Levchenko, I. I., Satsuk, E. I. (2008). Сarrying capacity and monitoring of overhead power lines in extreme weather conditions. Electricity, 4, 2–8.
  10. Zhelezko, Y. S. (2004). Loss of electric energy in electric grids, depending on weather conditions. Power station, 11.
  11. Ministry of Energy and Coal Industry of Ukraine (2011). Method for determining the technological power consumption of transshaper and power lines.
  12. Osipov, D. S. (2006). Recording of heating of current–carrying parts in the calculation of the power loss and power at non–sinusoidal modes of electric power systems. Omsk.
  13. Vragov, A. P. (2006). Heat exchange processes and equipment of chemical and petroleum industries. Sumy, 218.
  14. Server "Weather of Russia». Archive of weather data. Available at: http://meteo.infospace.ru
  15. Rutkovska, D., Pilinsky, M., Rutkowski, L. (2006). Neural networks, genetic algorithms and fuzzy systems. I.D.M.: Hotline–Telecom, 452.
  16. Zaigraeva, Y. B. (2008). Neural network models of assessment and loss electricity planning in power systems. Novosibirsk, 215.
  17. Tsaregorodtsev, V. G. (2003). To the definition of informativeness of independent revariables for the neural network. Neyroinformatika i ee prilozheniya, 176–177.
  18. Srinivasan, D. A. (1991). Novel approach to electrical load Forecasting based on a neural network. Singapore, 1172–1177.
  19. Hamid, B. (1992). Automated load forecasting using neural networks. Proc. Amer. Power Conf., 54, 1149–1153.
  20. Tsaregorodtsev, V. G. (2003). A view at the architecture and requirements for the neuroimitator to solve problems of modern industry. Neyroinformatika i ee prilozheniya, 171–175.
  21. Neural networks. STATISTICA Neural Networks (2001). Moscow: Hotline – Telecom, 654.
  22. Bakulevskiy, V. L. (2011). Considering the temperature factor in the calculation of technical losses in electricity transmission overhead lines. Problems of energy saving in electrical systems, 1, 172–173.
  23. Bakulevskiy, V. L. (2013). Improving the accuracy of calculation of load electricity losses in overhead lines with voltage 6–35 kV by taking into account climatic factors. Scientific works of Donetsk National Technical University, 1 (14), 9–14.
  24. Bakulevskiy, V. L. (2015). The use of neural networks for the calculation of technical losses of electricity in overhead power lines voltage 6–35 kV. Journal of Azov Technical University. Engineering, 30.

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Published

2016-10-30

How to Cite

Bakulevskiy, V. (2016). Research into the influence of climatic factors on the losses of electric energy in overhead power transmission lines. Eastern-European Journal of Enterprise Technologies, 5(8 (83), 4–8. https://doi.org/10.15587/1729-4061.2016.80072

Issue

Section

Energy-saving technologies and equipment