Methodology for Optimal Micrositing of Building Mounted Wind Turbines using Computational Fluid Dynamics and Genetic Algorithms

Christian V. Rodriguez, Alberto Ríos, Jaime E. Luyo

Abstract


Building Mounted Wind Turbines (BMWTs) are installed on building rooftops to exploit the wind velocity amplification found there. Optimal positioning of BMWTs (micrositing problem) can increase the energy gathered from the wind and reduce the total energy cost. Although micrositing methodologies have been extensively studied for wind farms, a gap in knowledge exists regarding the micrositing of BMWTs. The main objective of this work was to propose a methodology for optimal micrositing of BMWTs using Computational Fluid Dynamics (CFD) and Genetic Algorithms (GA). Thus, a site assessment was initially performed. Wind data treatment was carried out to determine those wind velocities and directions to be used in the next stages. These wind velocities and directions were simulated within an urban environment via CFD. The selection of a BMWT was then carried out. Furthermore, the zones with low wind speeds and high turbulence levels restricted the search space used in the GA-based micrositing optimization. Finally, a sensitivity analysis employing the building reinforcement factor (F) was performed. The results showed that the energy produced yearly by the BMWT is the key parameter in reducing the Cost of Energy (CoE), which achieved a value of 3.05146 $/kWh.

Keywords


Micrositing; Building mounted wind turbines; Computational fluid dynamics; Genetic algorithms

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References


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DOI (PDF): https://doi.org/10.20508/ijrer.v16i2.15299.g9215

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