Wind Farm Layout Optimization Considering Commercial Turbine Selection and Hub Height Variation

Date
2017
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Abstract
New aspects were added to the wind farm layout optimization problem; commercial turbine selection, generic realistic representation for the thrust coefficient, investigating the power-cost of energy trade-off range, and introducing the wind farm layout upgrade optimization problem. A range of commercial turbines was selected and the manufacturers’ power curves were used to evaluate the power developed by each turbine using the effective wind speed. The classical Jensen’s wake model was implemented to simulate the wake and wake interference within the farm in an analytic and accurate way. A simple field-based cost model was developed to evaluate the cost of any layout in terms of the turbine rated power and hub height. For the upgrade cases, the cost model included an area factor to account the upgraded area to the original farm area. A Genetic Algorithm was used for optimization throughout this dissertation. A technique called Random Independent Multi-Population Genetic Algorithm was used in some cases to accelerate the optimization. The results showed that co-operative optimization is superior over the selfish one. The turbine aerodynamic efficiency was found to magnify the difference between the two optimization strategies. A wide range of commercial turbines was selected and a useful range of power-cost of energy trade-off was obtained. The optimization was found to be more efficient in offshore cases because of the low entrainment coefficient in the wake model. The Random Independent Multi-Population technique caused a significant reduction in the speed of the optimization. It is likely that most farms can be efficiently and practically upgraded with a wide range of power-cost of energy trade-offs, using the proposed upgrade layout and the optimization objective.
Description
Keywords
Energy, Engineering, Engineering--Mechanical
Citation
Abdulrahman, M. A. (2017). Wind Farm Layout Optimization Considering Commercial Turbine Selection and Hub Height Variation (Doctoral thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/28711