Wind Turbine with Configurable Feedback Scheme for Minimal Environmental Impact and Maximum Efficiency
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Keywords

wind turbines
dinamic optimization
reconfigurable systems
environmental regeneration

How to Cite

Sandoval RuizC. E. (2022). Wind Turbine with Configurable Feedback Scheme for Minimal Environmental Impact and Maximum Efficiency. Universidad Ciencia Y Tecnología, 26(113), 123-136. https://doi.org/10.47460/uct.v26i113.578

Abstract

This work consists of a study of wind turbine configurations, analyzing their efficiency, and proposing optimization stages for wind energy conversion technologies. This has made it possible to establish a reconfigurable model of adaptive turbines, under the criteria of minimum environmental impact
on fauna, maximum energy efficiency, and dynamic updating to new technologies. The method consisted of the identification of the parameters of the wind system, its analysis, and the generalization of the architecture. A set of optimization variables was obtained, which allowed proposing of innovative techniques for adapting the configurable model of the system. The developed model provides a basis for the identification of parameters, online diagnosis, configurable optimization stages on the installed wind turbines, improves efficiency, environmental remediation and regeneration of the flow pattern conditions and optimal environmental variables of the system, as well as recycling. programmed in the technological update stage.

Keywords: Wind turbines, dynamic optimization, reconfigurable systems, environmental regeneration.

 

https://doi.org/10.47460/uct.v26i113.578
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References

[1]WindEurope Sustainability – Cefic – EuCIA. “Accelerating Wind Turbine Blade Circularity”. 2020
[2]C.Psomopoulos, K. Kalkanis, S. Kaminaris, G. Ioannidis, & P. Pachos. “A Review of the Potential for the Recovery of Wind Turbine Blade Waste Materials”.
Recycling, vol. 4, no. 1, pp. 7. 2019 https://www.mdpi.com/2313-4321/4/1/7
[3]C. Sandoval-Ruiz, “LFSR Optimization Model based on the Adaptive Coefficients method for ERNC Reconfigurable Systems”. Ingeniare, vol. 29, no. 4, pp.743-766, 202.
[4]B. Bossoufi, M., Lagrioui, et. al. “Observer backstepping control of DFIG-Generators for wind turbines variable-speed: FPGA-based implementation”. Renewable
Energy, vol. 81, pp. 903-917. 2015.
[5]H. Sun, C. Qiu, L. Lu, X. Gao, J. Chen, & H. Yang. “Wind turbine power modeling and optimization using artificial neural network with wind field experimental data”. Applied Energy, vol. 280, 115880. 2020.
[6]C. Sandoval-Ruiz. “Fractal Mathematical over Extended Finite Fields Fp[x]/(f(x))”. Proyecciones Journal of Mathematics, vol. 40, no. 3, pp. 731-742. 2021. doi.
org/10.22199/isnn.0717-6279-4322.
[7]C. Sandoval-Ruiz “LFSR-Fractal ANN Model applied in R-IEDs for Smart Energy”. IEEE Latin America Transactions, vol. 18, no. 4, pp. 677-686. 2020. https://
doi.org/10.1109/TLA.2020.9082210
[8]C. Sandoval-Ruiz, “Quantum architecture: Osciladores acoplados, dinámica y ERNC”, Perspectiva, vol.1, no. 19, pp. 86-99. 2022. Disponible en [on line] https://
www.produccioncientificaluz.org/index.php/perspectiva/article/view/38184
[9]K. Prasad, V. Kumar, G. Swaminathan, & G. Loganathan.“Computational investigation and design optimization of a duct augmented wind turbine (DAWT)”.
Materials Today: Proceedings, vol. 22, pp. 1186-1191.
2020. https://doi.org/10.1016/j.matpr.2019.12.116
[10]H. Jang, D. Kim, Y. Hwang, I. Paek, S. Kim, & J. Baek. “Analysis of Archimedes Spiral Wind Turbine Performance by Simulation and Field Test”. Energies,
vol. 12, no. 24, pp. 4624. 2019. https:// dx.doi.org/10.3390/en12244624
[11]N. Keramat, G.Najafi, T. Tavakkoli, B. Ghobadian & E. Mahmoodi. “Mathematical modeling of a horizontal axis shrouded wind turbine”. Renewable Energy, vol.
146, pp. 856–866. 2020. https://dx.doi.org/10.1016/j.renene.2019.07.022
[12]G. Richmond-Navarro, P. Casanova-Treto, & F. Hernández-Castro. “Efecto de un difusor tipo wind lens en flujo turbulento”. Uniciencia, 35(2), 1-18. 2021.
[13] Universidad de Chile. “Explorador Eólico”. 2021.http://ernc.dgf.uchile.cl:48080/inicio.[14]C. Sandoval-Ruiz. “Smart systems for the protection
of ecosystems, flora and fauna”. Universidad Ciencia y Tecnología, vol. 25, no. 110, pp, 138-154. 2021.
[15]C. Sandoval-Ruiz. “Arreglos Fotovoltaicos Inteligentes con Modelo LFSR-Reconfigurable”. Revista Ingeniería, vol. 30, no. 2, pp. 32-61. 2020. https://doi.
org/10.15517/ri.v30i2.39484.
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