Factors of Correlation for Dynamic Links of Rotor Systems of Wind Electric Installation
DOI:
https://doi.org/10.22213/2410-9304-2021-4-61-68Keywords:
correlation factor, spectral density, correlation function, vibration, wind turbine, rotor systemAbstract
The substantiation of definition of correlation factors for dynamic links of rotor systems of wind electric installations, as one of subtasks of the mathematical algorithms of dynamic behavior of system claimed for the further working out for the purpose of automated control updating fot the wind-electric installation which provides reduction of vibrations of all elements of rotor systems in conditions of loading a drive at different modes of operation of the energy-unit that promotes improvement of indicators of reliability for components of the modern wind installations is made. The problem of determining the parameters of the analytical model of the correlation function for the purpose of definition of correlation dependences between the measured values of meteorological and electro-power process taking into account the requirement of a minimum of the sum of squares of discrepancies (approximation errors) for the actual and approximating lines is solved. The average square deviation of an error of approximation, meteorological and electro-power process on the basis of a discrete estimation of ordinates of the analytical model of the correlation function does not exceed 1%. Mathematical formulas for definition of the spectral density of input and target casual processes, and also mutual spectral density of input and target casual processes of dynamic links of rotor systems on the basis of the block diagram of transfer functions of the system behavior for the purpose of revealing the degree of correlation of transfer functions are made. The analysis is made for processes of input and target signals of transfer functions with regard to their coherent state on the basis of calculation of factors of correlation for dynamic links of rotor systems for the purpose of the description of the transfer function within the limits of the analysis of vibrating fields of the unit as a whole since vibrations are causednot only by blades but also by all elements with rotor systems.References
Шнеерсон Р. М. Разработка гибридного ветроэнергетического комплекса для электроснабжения удаленных потребителей Мурманской области // Вестник науки Сибири. 2015. № 15. С. 55-58.
Пионкевич В. А. Математическое моделирование ветротурбины для ветроэнергетической установки с асинхронным генератором методом частотных скоростных характеристик // Вестник ИрГТУ. 2016. № 3. С. 83-88.
Степанов С. Ф., Павленко И. М., Ербаев Е. Т. Обеспечение эффективной работы мультимодульной ветроэлектростанции при изменении скорости ветра и нагрузки // Современные проблемы науки и образования. 2013. № 6. С. 93-94.
Суяков С. А. Проблемы интеграции ветроустановок в единую энергетическую систему России // Инженерный вестник Дона. 2014. № 3. С. 10-23.
Emadifar R., Tohidi D., Eldoromi M. Controlling Variable Speed Wind Turbines Which Have Doubly Fed Induction Generator by Using of Internal Model Control Method // International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering. 2016. No. 5. Pp. 3464-3471.
Balamurugan N., Selvaperumal S. Intelligent controller for speed control of three phase induction motor using indirect vector control method in marine applications // Indian journal of Geo Marine Sciences. 2018. No. 47. Pp.1068-1074.
Vijayalaxmi B., Bheema K. Individual Pitch Control of Variable Speed Wind Turbines Using Fuzzy Logic with DFIG // International Journal of research in advanced engineering technologies. 2016. No. 5. Pp. 45-52.
Subbaian V., Sasidhar S. Maximum energy capture of variable speed variable pitch wind turbine by using RBF neural network and fuzzy logic control // International Research Journal of Engineering and Technology. 2015. No. 2. Pp. 493-500.
Haiying D., Lixia Y., Guohan Y., Hongwei L. Wind Turbine Active Power Control Based on Multi-Model Adaptive Control // International Journal of Control and Automation. 2015. No. 8. Pp. 273-284.
Бендат Дж., Персол А. Приложения корреляционного и спектрального анализа. М. : Мир, 1983. 312 с.
Отнес Р., Эноксон Л. Прикладной анализ временных рядов исследования случайных функций / Р. Отнес, Л. Эноксон. М. : Энергия, 1979. 320 с.
Доценко С.В. Случайные процессы в гидрофизических измерениях. Л. : Гидрометиздат, 1983. 239 с.
Буяльский В. И. Комбинированный метод управления ветротурбиной // Энергетик. 2016. № 4. С. 18-20.
Буяльский В. И. Комбинированный метод управления ветротурбиной // Энергетик. 2016. № 4. С. 18-20.
Буяльский В. И. Методика для устранения запаздывания включения устройства разворота лопастей ветротурбины // Энергетик. 2014. № 5. С. 33-35.
