DOE-ANOVA to optimize hydrokinetic turbines for low velocity conditions

The need of reducing the dependence of fossil fuels and CO2 emissions have motivated the diversification of energy matrix. Among the Renewables, the hydropower shows better characteristics compared to solar, wind, biomass and geothermal, because its low CO2 emissions, higher density and others technical factors. Within the Hydropower, the Hydrokinetic turbines (HT) are considered as a promising technology because can provide electricity during low flow velocity conditions (< 2 m/s) and is able to operate in shallow waters < 8 m and in secluded areas without access to the energy network. In this sense, the present study incentivizes the research in Hydropower and proposes and new application of DOE-ANOVA combined with Computational Fluid Dynamics (CFD) modelling for the HT design and optimization. Accordingly, this work evaluated the performance of a HT with 1.9 m of rotor diameter operating in a water flow of 1.5 m/s through a 23 factorial design with 9 modelling cases (MC). The results showed that the increment of outlet diameters increased the downstream velocity and the hydrodynamic pressure over the HT, and the reduction of the blade tip edge distance generated an increment of the response of the HT hydraulic and mechanical properties.

• Autores: Rueda-Bayona, Juan Gabriel; Paez, Natalia; Cabello Eras, Juan José; Sagastume Gutierrez, Alexis
• Tipo de recurso: Article of investigation
• Fecha de publicación: 2022
• Institución: Corporación Universidad de la Costa
• Repositorio: REDICUC - Repositorio CUC
• Idioma: eng
• OAI Identifier: oai:repositorio.cuc.edu.co:11323/10764
• Acceso en línea: https://hdl.handle.net/11323/10764; https://repositorio.cuc.edu.co/
• Palabra clave: CFD; DOE-ANOVA; Hydrokinetic microturbine; Multiple regression; Optimization
• Rights: openAccess
• License: Atribución 4.0 Internacional (CC BY 4.0)