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Tytuł artykułu

Approximation and Prediction of the Wind Speed Change Function

Autorzy
Treść / Zawartość
Identyfikatory
Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
In the article the features of energy summation from two wind generators, located at a certain distance from each other, are considered. The method of calculating the correlation function between the wind flow speed change functions in the direction of wind distribution is presented. The formulas for describing the fluctuation components of energy at the output of the wind generator are given for two cases: when the phases of the fluctuations of the wind flow on two wind generators are the same and when the fluctuations of the wind flow are in the antiphases. It is shown that to increase the energy level that can be taken from the wind power plant it is necessary to control the phase shift between the energy fluctuations at the output of the wind generators and use the energy of the storages; and to use linear approximations to approximate the wind speed change function. Under the condition of a linear change of the internal resistance of the wind generator in time, it is advisable to introduce the wind speed change function with linear approximations. The system of orthonormal linear functions based on Walsh functions is given. A table with formulas and graphs describing the first 8 functions, which are arranged in order of increasing the number of their sign alternating on the interval of functions definition, is presented. The result of the approximation of the wind speed change function with a system of 8 linear functions based on Walsh functions is shown. Decomposition coefficients, mean-square and average relative approximation errors for such approximation are calculated. In order to find the parameters of multiple linear regression the method of least squares is applied. The regression equation in matrix form is given. An example of application of linear regression prediction method to simple functions is shown. The restoration result for wind speed change function is shown. Decomposition coefficients, mean-square and average relative approximation errors for restoration of wind speed change function with linear regression method are calculated.
Rocznik
Tom
Strony
35--46
Opis fizyczny
Bibliogr. 13 poz., tab., rys.
Twórcy
autor
  • National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Peremohy Ave. 37, 03056 Kyiv, Ukraine
autor
  • National Technical University of Ukraine "Igor Sikorsky Kyiv Polytechnic Institute", Peremohy Ave. 37, 03056 Kyiv, Ukraine
Bibliografia
  • [1] SUHODOLYA L., Current state, problems and prospects of hydropower development in Ukraine, National Institute for Strategic Studies, Analytical report, 2014.
  • [2] Ostap Semerak: Ukraine pledged to increase its share of renewable energy up to 11% by 2035 [electronic resource] – Access to the resource: https://www.kmu.gov.ua/ua/news/ostap-semerak-ukrayinazobovyazalasya-do-11-zbilshiti-chastku-vidnovlyuvanoyi-energetiki-do-2035-roku
  • [3] PRAHOVNYK A., Harmony of Ukraine’s energy and energy efficiency paths to world trends, Knowledge, Kyiv 2003, p. 100.
  • [4] OSYPENKO K., ZHUIKOV V., Heisenberg’s uncertainty principle in evaluating the renewable sources power level, Technical Electrodynamics, 2017, Vol. 1, pp. 10–16.
  • [5] ZHUIKOV V., OSYPENKO K., Compensator currents form determination considering wind generator aerodynamic resistance, 2014 IEEE International Conference on Intelligent Energy and Power Systems (IEPS), 2014, pp. 168–170.
  • [6] BUTCHER J. C., Numerical Methods for Ordinary Differential Equations, John Wiley & Sons, New York 2003.
  • [7] KORN G., KORN T., Mathematical handbook for scientists and engineers, Science, Moscow, USSR, 1974.
  • [8] OSYPENKO K., ZHUIKOV V., The linearization of primary energy flow parameters change function Franklin discrete functions, Electronics and Communication, 2016, Vol. 4, pp. 33–37.
  • [9] TRAHTMAN A., TRAHTMAN V., The fundamentals of the theory of discrete signals on finite intervals, Soviet radio, Moscow, USSR, 1975.
  • [10] DAGMAN E., Fast discrete orthogonal transformations, Science, Novosibirsk 1983.
  • [11] The weather at the airports [electronic resource] – Access to the resource: http://pogoda.by/avia/ ?icao=UKBB
  • [12] Multiple linear regression. Improving the regression model [electronic resource] – Access to the resource: https://function-x.ru/statistics_regression2.html
  • [13] BRILLOUIN L., Science and the information theory, State publishing house of physical and mathematical literature, Moscow, USSR, 1960.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-9857cd0a-07e2-4344-be10-b3f0b0cdcf53
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