A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Lifetime performance of wind turbines and wind farms
Wind energy is rapidly expanding as the demand for a low-emissions electricity grid increases. Acknowledging this, and the intermittent nature of the wind resource, both short-term (circa hours) and long-term (circa years) planning must be implemented. To do this accurately, the performance degradation of wind farms must be quantified and accounted for in electricity systems and financial models. This thesis is concerned with quantifying aerodynamic performance decline of wind turbines and wind farms to better understand changes in lifetime performance and more accurately predict wind farm power output. Wind turbine aerodynamic performance losses are investigated by analysing the effect of roughness on airfoil performance (lift and drag). One of the challenges in quantifying wind turbine performance decline due to roughness is the lack of roughness airfoil data available. A ‘roughness evolution parameter’ is therefore parameterised based on publicly available roughened airfoil experimental tables, which enables roughened airfoil data to be estimated from clean airfoil data. The calculation of the parameter is proposed as a framework, with room for further refinement when more experimental data comes available. Blade element momentum theory is used to analyse the impact of blade roughness on wind turbine performance. Exemplar wind turbine rotors are designed and the impact of roughness on annual energy production is quantified to be in the range of 2.9–8.6% for realistic levels of roughness. A novel control method is proposed to mitigate losses due to roughness and 0.1–1.0% of annual energy production is recovered. To account for the long-term variability in wind speed, wind farm performance decline is quantified using long-term corrected capacity factor data from wind farms in the UK, US and Australia – 0.26, 0.72 and 0.43 capacity factor percentage points per year respectively. To do so, power output data is combined with reanalysis wind speed data to correct for variability and biases in the data, allowing the ...
Lifetime performance of wind turbines and wind farms
Wind energy is rapidly expanding as the demand for a low-emissions electricity grid increases. Acknowledging this, and the intermittent nature of the wind resource, both short-term (circa hours) and long-term (circa years) planning must be implemented. To do this accurately, the performance degradation of wind farms must be quantified and accounted for in electricity systems and financial models. This thesis is concerned with quantifying aerodynamic performance decline of wind turbines and wind farms to better understand changes in lifetime performance and more accurately predict wind farm power output. Wind turbine aerodynamic performance losses are investigated by analysing the effect of roughness on airfoil performance (lift and drag). One of the challenges in quantifying wind turbine performance decline due to roughness is the lack of roughness airfoil data available. A ‘roughness evolution parameter’ is therefore parameterised based on publicly available roughened airfoil experimental tables, which enables roughened airfoil data to be estimated from clean airfoil data. The calculation of the parameter is proposed as a framework, with room for further refinement when more experimental data comes available. Blade element momentum theory is used to analyse the impact of blade roughness on wind turbine performance. Exemplar wind turbine rotors are designed and the impact of roughness on annual energy production is quantified to be in the range of 2.9–8.6% for realistic levels of roughness. A novel control method is proposed to mitigate losses due to roughness and 0.1–1.0% of annual energy production is recovered. To account for the long-term variability in wind speed, wind farm performance decline is quantified using long-term corrected capacity factor data from wind farms in the UK, US and Australia – 0.26, 0.72 and 0.43 capacity factor percentage points per year respectively. To do so, power output data is combined with reanalysis wind speed data to correct for variability and biases in the data, allowing the ...
Lifetime performance of wind turbines and wind farms
Kelly, J (author) / Willden, R / Vogel, C
2023-05-24
Theses
Electronic Resource
English
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