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Processing of data on the intensity of solar radiation for solar power plant management systems

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In the article is elaborated a method for estimating the amount of electricity that can be produced by solar panels for a short period of time (several hours). For estimating are used meteorological observations of different geographic points. This method of estimation can be used for optimization the internal structure of the hybrid power supply system.
Twórcy
  • Lviv Polytechnic National University
  • Department of Telecommunications, University of Computer Sciences and Skills, Poland Lodz
autor
  • Lviv Polytechnic National University
Bibliografia
  • 1. Twiddell J., Wyre A. 1990. Renewable Energy // Energoatomizdat, 392.
  • 2. Pivnyak G. G., Shkrabets F. P. 2013. Alternative energy in Ukraine: monograph. - Dnipropetrovsk: Nats. Mountain Un. D.: NMU, 109 p.
  • 3. Kudrya S. O. 2012. Non-traditional and renewable energy sources: Textbook // National Technical University of Ukraine (KPI), 495 p.
  • 4. Golik O. P., Zhesan R. V. 2009. Analysis of meteorological observations of the intensity of solar radiation in the Kirovograd region for the purpose of creating an automatic control system for autonomous power supply on the basis of solar-wind installations // Collection of scientific works of Kirovograd National Technical University. Engineering in agricultural production, branch engineering, automation, 164-172.
  • 5. Shchur I. Z., Klimko V. I. 2014. Prediction of the efficiency of photoelectric panels in the city of Lviv // Bulletin of the National University "Lviv Polytechnic". Electric power and electromechanical systems, No. 785, 88-94.
  • 6. Stadnik M. I., Rubanenko A. O., Bondarenko S. V. 2016. Analysis of the efficiency of generation of electricity based on solar energy in the Vinnytsia region // Engineering, power engineering, transport of agro-industrial complex. No. 2 (94), 104-114.
  • 7. Eliseev O. K., Khazan P. V. 2016. Economical-statistical analysis of solar energy in the regions of Ukraine // Statistics of Ukraine, No. 4, 51-58.
  • 8. Kozyrskiy V. V., Martynyuk L. V. 2012. The intensity of solar radiation directed to an inclined surface // Scientific Bulletin of the National University of Life and Environmental Sciences of Ukraine. Series: Engineering and Power Engineering of Agroindustrial Complex, Exp. 174 (1), 112-119.
  • 9. Yurchenko A. V., Volgin V. V., Kozlov S. A. 2009. Statistical model of silicon solar cells operating under the influence of natural and hardware factors // Tomsk polytechnic, 142-148.
  • 10. Duffett-Smith P., Zwart J. 2011. Practical astronomy with your calculator or spreadsheet – 4th ed., Cambridge, 240 p.
  • 11. Duffie J. A., Beckman W. A. 2013. Solar Engineering of Thermal Processes – 4th ed., New Jersey, 928 p.
  • 12. Voloshin I. I. 2002. General earth science // Nizhyn Gogol State University, 294.
  • 13. Protsenko G.D. 2007. Meteorology and climatology // National Pedagogical Dragomanov University, 265 p.
  • 14. Weather Underground. Available online at: https://www.wunderground.com/
  • 15. Weather Underground ostrow IGMINAPR3. Available online at: https://www.wunderground.com/personalweatherstation/dashboard?ID=IGMINAPR3#history/s20170916/e20170916/mdailyWeather Underground Forecast for Khlepcha, Kiev. Available online at https//wwwwunderground.com/personalweatherstation/dashboard?ID=IKIEVKHL2#history/s20170601/e20170608/mweek
  • 16. Donchenko V. S., Sidorov M. V. 2015. Probability Theory and Mathematical Statistics for Social Sciences // Publishing center "Kyiv University", 400 p.
Uwagi
Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-9255d775-a36d-4e1b-b876-79bf43dfc80c
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