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On the impact of uncertainties on wind resource and power generation forecasts

L.R. Gainullina, H.F. Alhajj

Vestnik IGEU, 2024 issue 3, pp. 55—63

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Abstract in English: 

Background. The annual power generation of a wind farm is one of the most important indicators determining the profitability of a wind power project. The methods used to estimate the annual power generation of a wind farm have to consider uncertainties at all stages of the project life cycle. When developing a financial model of a wind power project, it is required to consider information about uncertainties to reduce the error and increase the reliability of the project. Specialists of various countries are improving the efficiency of wind power plants, studying wind energy resources, as well as assessing the efficiency of their use. However, special studies do not pay due attention to the problem of assessing the impact of various uncertainties on the forecasts of wind resource and power generation.

Materials and methods. Two methods are proposed to calculate uncertainties. They are a deterministic method based on the assumption of independence of various uncertainties, and a Monte Carlo method that simulates the behavior of a physical system many times.

Results. The paper considers the uncertainties to be considered during the design of a wind farm and presents the variation ranges. The authors have presented the plots of power generation with various levels of probability of being reached or exceeded the total uncertainty for three variants. It is shown that considering the various uncertainties allows a power generation forecast to be made with increased accuracy.

Conclusions. The results obtained are necessary to develop a wind measurement data processing model that allows us to forecast electricity generation by existing wind power plants with increased accuracy.

References in English: 

1. Vladimirova, L.V., Ovsyannikov, D.A., Rubtsova, I.D. Metody Monte-Karlo v prikladnykh zadachakh [Monte Carlo methods in applied problems]. Saint-Petersburg: Izdatel'stvo VVM, 2015. 166 p.

2. Kashnikova, A.P. Metod Monte-Karlo v zadachakh modelirovaniya protsessov i system [Monte Carlo method in the problems of modeling processes and systems]. Modern Science, 2021, no. 1-2, pp. 358–362.

3. Jorge, B., Rolando, F.B., Carlo, A.B., Nora, N. The renewable energy policy Paradox. Renewable and Sustainable Energy Reviews, 2018, vol. 82 (Part 1), pp. 1–5. https://doi.org/10.1016/ j.rser.2017.09.002.

4. Alhajj Hassan, F., Sidorov, A. Study of power system stability: Matlab program processing data from Zahrani power plant (Beirut, Lebanon). E3S Web of Conferences, 2019, vol. 1, no. 2, pp. 60–70. DOI: 10.28991/HEF-2020-01-02-02.

5. Almohammed, O., Philippova, F., Alhajj Hassan, F., Timerbaev, N., Fomin, A. Practical study on heat pump enhancement by the solar energy. E3S Web of Conferences, 2021, issue 288. https://doi.org/10.1051/e3sconf/202128801069.

6. Mestnikov, N., Hassan, F.A., Alzakkar, A. Study of operation of combined power supply system based on renewable energy in territory of far east of Russia. International conference on industrial engineering, applications and manufacturing (ICIEAM), 2021, pp. 114–118. https://doi.org/10.1109/ICIEAM51226.2021.9446439.

7. Filippova, T.A., Rusina, A.G., Dronova, Yu.V. Modeli i metody prognozirovaniya elektroenergii i moshchnosti pri upravlenii rezhimami elektroenergeticheskikh sistem [Models and methods for forecasting electricity and power in the control of modes of electric power systems]. Novosibirsk: Izdatel'stvo NGTU, 2009. 368 p.

8. Alkhadzh Khassan, F., Alali, Sh., Gaynullina, L.R. Povyshenie effektivnosti vetrovykh elektrostantsiy [Increasing the efficiency of wind power plants]. Vestnik Irkutskogo gosudarstvennogo tekhnicheskogo universiteta, 2022, no. 26(2), pp. 217–227. https://doi.org/10.21285/1814-3520-2022-2-217-227.

9. Coquilla, R.V., Obermeier, J. Calibration Uncertainty Comparisons Between Various Anemometers. In American Wind Energy Association AWEA, 2008.

10. Ismaiel, A., Yoshida, S. Aeroelastic analysis for side-booms of a coplanar twin-rotor wind turbine. International Review of Aerospace Engineering, 2020, vol. 13(4), pp. 135–140. https://doi.org/10.15866/irease. v13i4.18355

11. Alhajj Hassan, F. Multi-criteria Approach and Wind Farm Site Selection Analysis for Improving Power Efficiency. Journal of Human, Earth, and Future, 2020, vol. 1(2), pp. 60–70. DOI: 10.28991/HEF-2020-01-02-02.

12. Alhajj Hassan, F., Mahmoud, M., Almohammed, O.A.M. Analysis of the Generated Output Energy by Different Types of Wind Turbines. Journal of Human, Earth, and Future, 2020, vol. 1(4), pp. 181–187. DOI: 10.28991/HEF-2020-01-04-03.

13. Samokhvalov, D.V., Jaber, A.I., Almahturi, F.S. Maximum Power Point Tracking of a Wind-Energy Conversion System by Vector Control of a Permanent Magnet Synchronous Generator. Russ. Electr. Engin., 2021, vol. 92, pp. 163–168.

14. Il'ichev, V.Yu., Shevelev, D.V. Raschet kharakteristik moshchnosti vetryanykh turbogeneratorov s primeneniem programmnogo modulya Windpowerlib [The calculation of power characteristics of wind turbine generators using the software module Windpowerlib]. Izvestiya MGTU «MAMI», 2021, no. 1(47), pp. 23–31.

15. Vozobnovlyaemye istochniki energii i smyagchenie vozdeystviy na izmenenie klimata [Renewable Energy and Climate Change Mitigation]. Spetsial'nyy doklad mezhpravitel'stvennoy gruppy ekspertov po izmeneniyu klimata [Special Report of the Intergovernmental Panel on Climate Change]. Zheneva, 2011. 215 p.

 

Key words in Russian: 
ветроэнергетика, ветровые электростанции, расчет неопределенностей, метод Монте-Карло, ветроизмерения
Key words in English: 
wind power, wind farms, calculation of uncertainties, Monte Carlo method, wind measurements
The DOI index: 
10.17588/2072-2672.2024.3.055-063
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