DYNAMIC WIND SPEED MODEL FOR SOLVING WIND POWER PROBLEMS

DYNAMIC WIND SPEED MODEL FOR SOLVING WIND POWER PROBLEMS

Authors

DOI:

https://doi.org/10.31489/2020No1/77-84

Keywords:

wind power, wind model, spectral model, forming filters.

Abstract

This work is devoted to the development of a dynamic model of wind speed designed to solve the problems of wind power. The time model of wind is presented in the form of two components - constant and turbulent. The Kaimal spectral model recommended by IEC 61400-1:2005 is used to describe the turbulent component of wind speed. The initial data for the calculation of turbulence parameters are the class of wind power plant, which is determined by its location, the height of the axis of rotation of the wind wheel and the average wind speed for the specified time interval of simulation. Computer implementation of wind model is carried out on the basis of statistically independent sources of white noise acting on forming filters, output signals of which are summed. The analysis of the obtained results shows that the wind flow model implemented on the basis of the method of forming filters provides adequate modeling of the longitudinal component of wind speed and can be used to solve the problems of wind power engineering.

References

"1 Renewables 2018 Global Status Rep ort. Renewable Energy Policy Network for the 21st Century. 2018. – 325 р. Available at: http://www.ren21.net/ (accessed 20 October 2019).

Cherubini A., Papini A., Vertechy R., Fontana M. Airborne Wind Energy Systems: A review of the technologies. Renewable and Sustainable Energy Reviews, 2015, Vol. 51, pp. 1461–1476.

Goudarzi N., Zhu W.D. A review on the development of wind turbine generators across the world. International Journal of Dynamics and Control, 2013, Vol. 1, No. 2, pp.192–202.

Abdullah M.A., Yatim A.H., Tan C.W., et al. A review of maximum power point tracking algorithms for wind energy systems. Renewable and Sustainable Energy Reviews, 2012, Vol. 16, pp. 3220– 3227.

Guo R, DuJ., J. Wu, Y. Liu, The Pitch Control Algorithm of Wind Turbine Based on Fuzzy Control and PID Control. Energy and Power Engineering, 2013, Vol. 5, pp. 6-10.

Surzhikova O. Power supply of remote and almost inaccessible settlements. IOP Conference Series: Materials Science and Engineering IOP. 2015, Vol. 81, No 1 doi10.1088/1757-899X/81/1/012098

Bemš, J., Starý, O., Macaš, M., Žegklitz, J., Pošík, P. Innovative default prediction approach. Expert Systems with Applications, 2015, Vol. 42, No 17-18, pp. 6277-6285. doi: 10.1016/j.eswa.2015.04.053

Kerrouche K., Mezouar E., Boumediene A., et al. Modeling and Lyapunov-Designed based on Adaptive Gain Sliding Mode Control for Wind Turbines. Journal of Power Technologies, 2016, Vol. 96, No.2, pp.124–136.

Barbosa de Alencar D., De Mattos Affonso C., Limão de Oliveira R.C., et al. Different Models for Forecasting Wind Power Generation: Case Study. Energies, 2017, Vol. 10, No. 1976, pp. 1 – 27.

Sarsikeev Y, Lukutin B.V, Lyapunov D.Y., Surkov M.A., Obuhov S.G. Dynamic model of wind speed longitudinal component. Advanced Materials Research, 2014, Vol. 953-954, pp. 529-532.

Abo-Khalil A.G., Alyami S., Sayed K., Alhejji A. Dynamic Modeling of Wind Turbines Based on Estimated Wind Speed under Turbulent Conditions. Energies, 2019, Vol. 12, No. 1907, pp. 1–25.

Yunus K., Thiringer T., Chen P. ARIMA-Based Frequency-Decomposed Modeling of Wind Speed Time Series. IEEE Transactions on Power System, 2016, Vol. 31, pp. 2546–2556.

Smilden E., Sørensen A., Eliassen L. Wind Model for Simulation of Thrust Variations on a Wind Turbine. Energy Procedia, 2016, Vol. 94, pp. 306 – 318.

IEC 61400-1: 2005 Wind Turbines – Part 1: Design requirements. Available at: https://webstore.ansi.org /Standards/IEC/IEC61400AmdEd2010?msclkid

Kirpichnikova I.M., Matveyenko O.V. Computer simulation of wind pulsation depending on time. International Scientific Journal for Alternative Energy and Ecology, 2010, Vol. 4, No. 81, pp. 54–59.

Neammanee B., Sirisumrannukul S., Chatratana S. Development of a Wind Turbine Simulator for Wind Generator Testing. International Energy Journal, 2007, Vol. 8, pp. 21 – 28.

Gavrilin A., Moyzes B., Kuvshinov K., Vedyashkin M., Surzhikova О. Determination of optimal milling modes by means of shock-vibration load reduction on tool and peak-factor equipment. Materials Science Forum, 2019, Vol. 942, pp. 87 – 96. doi:10.4028/www.scientific.net/MSF.942.87

Hao H., Gu B., Yan R., Hui H. Simulation and Analysis of Direct-driven Wind Turbine. International Journal of Online and Biomedical Engineering, 2015, Vol. 11, No. 5, pp. 17 – 23.

Sakipova S.E., Tanasheva N.K. Modeling aerodynamics of the wind turbine with rotating cylinders. Eurasian Physical Technical Journal. 2019, Vol.16, No. 1(31), pp. 88 – 93. DOI: 10.31489/2019No1/88-93

Králík T., Bemš, J., Starý, O. Electricity markets integrations - What is the current status and future outlook of bidding zones reconfiguration? Proc. of the 9th Intern. Scient.Symposium on Electrical Power Engineering, ELEKTROENERGETIKA 2017, 237 – 240.

Erich Hau Wind Turbines: Fundamentals, Technologies, Application, Economics. 2-nd edition. Springer – Verlag Berlin Heidelberg. 2006, 783 p.

"

Downloads

How to Cite

Obukhov, . S., Plotnikov, . I., & Masolov, . V. (2020). DYNAMIC WIND SPEED MODEL FOR SOLVING WIND POWER PROBLEMS. Eurasian Physical Technical Journal, 17(1(33), 77–84. https://doi.org/10.31489/2020No1/77-84

Issue

Section

Energy
Loading...