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MODELING AND SIMULATION OF WIND TURBINE HEAT RECYCLING SYSTEM

ABSTRACT
The paper aims to discuss the power supply and heat supply system of wind turbine, promote the development of wind energy in heat recycling, and expand the application of renewable energy resources in replacing fossil energy. Starting from the construction of wind power heat storage system model, first, molten salt was selected as the fluid heat storage material. Based on the realization process of two-pot molten salt electrothermal transformation, the model of two-pot molten salt heat storage (MSHS) system was established. Second, based on the model of heat storage system, the high temperature MSHS wind power heating system was simulated by using the numerical simulation analysis method. The results showed that the simulation results of the thermal storage system model were highly consistent with the actual results, and the model was accurate and reliable, which was suitable for the simulation analysis of the thermal storage system. After a day of operation, the utilization rate of wind energy of the MSHS wind power heating system could reach more than 94%. The combination of the MSHS wind power system and regional heating had obvious effect on absorbing wind power, saving resources, and solving the problems of wind curtailment. In the MSHS wind power supply heating system, the configuration of MSHS significantly improved the utilization ratio of wind energy in the wind power generation system, even up to 100% at maximum. To sum up, the configuration of MSHS can absorb most of the wind energy generated on that day, thus improving the energy utilization ratio of the wind power generation system.
KEYWORDS
PAPER SUBMITTED: 2019-11-02
PAPER REVISED: 2019-12-06
PAPER ACCEPTED: 2020-01-09
PUBLISHED ONLINE: 2020-02-29
DOI REFERENCE: https://doi.org/10.2298/TSCI191102084M
CITATION EXPORT: view in browser or download as text file
THERMAL SCIENCE YEAR 2020, VOLUME 24, ISSUE 5, PAGES [3099 - 3107]
REFERENCES
  1. Kusiak, A., Renewables: Share Data on Wind Energy, Nature, 529 (2016), 7584, pp. 19-21.
  2. Shaofei Wu. Study and evaluation of clustering algorithm for solubility and thermodynamic data of glycerol derivatives, Thermal Science, 23(2019), 5, pp.2867-2875
  3. Shematovich, V. I., Suprathermal oxygen atoms in the Martian upper atmosphere: Contribution of the proton and hydrogen atom precipitation, Solar System Research, 51 (2017), 4, pp. 249-257.
  4. Gigović, L, et al., Application of the GIS-DANP-MABAC multi-criteria model for selecting the location of wind farms: A case study of Vojvodina, Serbia, Renewable Energy, 103 (2017) pp. 501-521.
  5. Hamzaoui, I., et al., Advanced control for wind energy conversion systems with flywheel storage dedicated to improving the quality of energy, International Journal of Hydrogen Energy, 41 (2016), 45, pp. 20832-20846.
  6. Tian, D., et al., Optimized operation of energy storage systems of wind power based on demand response and cost model, Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering, 34 (2018), 15, pp. 200-206.
  7. Shaofei Wu,A Traffic Motion Object Extraction Algorithm,International Journal of Bifurcation and Chaos, 25(2015),14,Article Number 1540039
  8. Ontiveros, L. J., et al., A Novel Power Conditioning System coupled with a Flow Battery for Wind Energy Applications: Modelling and Control Design, Iet Renewable Power Generation, 11 (2017), 7, pp. 987-995.
  9. Yang, Y., et al., Battery energy storage system size determination in renewable energy systems: A review, Renewable & Sustainable Energy Reviews, 91 (2018), 2018, pp. 109-125.
  10. Rahman, O., et al., High Temperature Superconducting Devices and Renewable Energy Resources in Future Power Grids: A Case Study, IEEE Transactions on Applied Superconductivity, 29 (2019), 2, pp. 1-4.
  11. Anastasovski, A., Design of Heat Storage Units for use in repeatable Time Slices, Applied Thermal Engineering, 112 (2017), pp. 1590-1600.
  12. Zhou, T., et al., Thermal conductivity measurement of phase-change material near melting point based on perturbation method, Journal of Central South University, 49 (2018), 4, pp. 979-986.
  13. Amin, M., et al., Thermal properties of beeswax/graphene phase change material as energy storage for building applications, Applied Thermal Engineering, 112 (2016), pp. 273-280.
  14. Babar O. A., et al., Selection of phase change material for solar thermal storage application: a comparative study, Journal of the Brazilian Society of Mechanical Sciences and Engineering, 41 (2019), 9, pp. 355.
  15. Shaofei Wu. Construction of visual 3-d fabric reinforced composite thermal performance prediction system, Thermal Science, 23(2019), 5, pp.2857-2865

© 2020 Society of Thermal Engineers of Serbia. Published by the Vinča Institute of Nuclear Sciences, Belgrade, Serbia. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International licence