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dc.creatoramelec, viloria
dc.creatorNuñez Lobo, Hugo
dc.creatorPineda, Omar
dc.date.accessioned2021-03-08T19:13:02Z
dc.date.available2021-03-08T19:13:02Z
dc.date.issued2020-09-15
dc.identifier.issn17578981
dc.identifier.issn1757899X
dc.identifier.urihttps://hdl.handle.net/11323/7967
dc.descriptionRetractedspa
dc.description.abstractRenewable energies have become a topic of great interest in recent years because the natural sources used for the generation of these energies are inexhaustible and non-polluting. In fact, environmental sustainability requires a considerable reduction in the use of fossil fuels, which are highly polluting and unsustainable [1]. In addition, serious environmental pollution is threatening human health, and many public concerns have been raised [2]. As a result, many countries have proposed ambitious plans for the production of green energy, including wind power, and consequently, the market for wind energy is expanding rapidly worldwide [3]. In this research, an evolutionary metaheuristic is implemented, specifically genetic algorithms.spa
dc.format.mimetypeapplication/pdfspa
dc.language.isoengspa
dc.publisherCorporación Universidad de la Costaspa
dc.rightsCC0 1.0 Universal*
dc.rights.urihttp://creativecommons.org/publicdomain/zero/1.0/*
dc.sourceIOP Conference Series: Materials Science and Engineeringspa
dc.subjectWind Turbinesspa
dc.subjectWind Fieldsspa
dc.subjectWake Effectspa
dc.subjectCombinatorial Optimizationspa
dc.subjectGenetic Algorithmsspa
dc.titleSolving the problem of optimizing wind farm design using genetic algorithmsspa
dc.typearticlespa
dcterms.references[1] Mittal, P., & Mitra, K. (2020). Efficient Wind Farm Micro-siting using Novel Optimization Approaches (Doctoral dissertation, Indian Institute of Technology Hyderabad).spa
dcterms.references[2] Viloria, A., & Gaitan-Angulo, M. (2016). Statistical Adjustment Module Advanced Optimizer Planner and SAP Generated the Case of a Food Production Company. Indian Journal Of Science And Technology, 9(47). doi:10.17485/ijst/2016/v9i47/107371spa
dcterms.references[3] Ryerkerk, M. L., Averill, R. C., Deb, K., & Goodman, E. D. (2017). Solving metameric variable-length optimization problems using genetic algorithms. Genetic Programming and Evolvable Machines, 18(2), 247-277spa
dcterms.references[4] Moreno-Carbonell, S., Sánchez-Úbeda, E. F., & Muñoz, A. (2020). Rethinking weather station selection for electric load forecasting using genetic algorithms. International Journal of Forecasting, 36(2), 695-712.spa
dcterms.references[5] Li, Q. S., Liu, D. K., Fang, J. Q., & Tam, C. M. (2000). Multi-level optimal design of buildings with active control under winds using genetic algorithms. Journal of Wind Engineering and Industrial Aerodynamics, 86(1), 65-86spa
dcterms.references[6] Rinaldi, G., Pillai, A. C., Thies, P. R., & Johanning, L. (2019). Multi-objective optimization of the operation and maintenance assets of an offshore wind farm using genetic algorithms. Wind Engineering, 0309524X19849826spa
dcterms.references[7] Sanchez, L., Vásquez, C., & Viloria, A. (2018, June). Conglomerates of Latin American countries and public policies for the sustainable development of the electric power generation sector. In International Conference on Data Mining and Big data (pp. 759- 766). Springer, Chamspa
dcterms.references[8] Diveux, T., Sebastian, P., Bernard, D., Puiggali, J. R., & Grandidier, J. Y. (2001). Horizontal axis wind turbine systems: optimization using genetic algorithms. Wind Energy: An International Journal for Progress and Applications in Wind Power Conversion Technology, 4(4), 151-171spa
dcterms.references[9] Garcia, J., Khosravi, A., Poley, R., Assad, M., & Machado, L. (2019, March). Multiobjective optimization of air conditioning system with the low GWP refrigerant R1234yf using genetic algorithm. In 2019 Advances in Science and Engineering Technology International Conferences (ASET) (pp. 1-7). IEEEspa
dcterms.references[10] Abdelsalam, A. M., & El-Shorbagy, M. A. (2018). Optimization of wind turbines siting in a wind farm using genetic algorithm based local search. Renewable Energy, 123, 748- 755.spa
dcterms.references[11] Thejaswini, R., & Raju, H. P. (2018, February). Optimizing Wind Turbine-Generator Design Using Genetic Algorithm. In 2018 Second International Conference on Advances in Electronics, Computers and Communications (ICAECC) (pp. 1-5). IEEEspa
dcterms.references[12] Guerrero, M., Montoya, F. G., Baños, R., Alcayde, A., & Gil, C. (2018). Community detection in national-scale high voltage transmission networks using genetic algorithms. Advanced Engineering Informatics, 38, 232-241.spa
dcterms.references[13] Tao, S., Xu, Q., Feijoo, A., Hou, P., & Zheng, G. (2020). Bi-hierarchy optimization of a wind farm considering environmental impact. IEEE Transactions on Sustainable Energy.spa
dcterms.references[14] Wan, C., Wang, J., Yang, G., & Zhang, X. (2010, June). Optimal micro-siting of wind farms by particle swarm optimization. In International Conference in Swarm Intelligence (pp. 198-205). Springer, Berlin, Heidelbergspa
dcterms.references[15] Daneshfar, F., & Bevrani, H. (2012). Multiobjective design of load frequency control using genetic algorithms. International Journal of Electrical Power & Energy Systems, 42(1), 257-263.spa
dcterms.references[16] Song, M., Chen, K., & Wang, J. (2020). A two-level approach for three-dimensional micro-siting optimization of large-scale wind farms. Energy, 190, 116340spa
dc.source.urlhttps://iopscience.iop.org/article/10.1088/1757-899X/872/1/012194spa
dc.rights.accessrightsinfo:eu-repo/semantics/openAccessspa
dc.identifier.doihttps://doi.org/10.1088/1757-899X/872/1/012029
dc.type.hasversioninfo:eu-repo/semantics/publishedVersionspa


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