Wind Array Performance Evaluation Model for Large Wind Farms and Wind Farm Layout Optimization

Download or read book Wind Array Performance Evaluation Model for Large Wind Farms and Wind Farm Layout Optimization written by Simeng Li and published by . This book was released on 2014 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: The grouping of wind turbines in arrays introduces two major issues: (1) reduced power production caused by wake wind speed deficits and (2) increased dynamic loads on the blades caused by higher turbulence levels. Depending on the layout and local wind conditions, the drop in power production of downstream turbines can easily reach 40% of the upstream turbines in fully developed wake conditions. These power drops across arrays arise due to wake wind speed deficits. Even when averaged over different wind directions, drops in power production of 8% (onshore arrays), and 12% (offshore arrays) have been recorded. In this dissertation, a large wind array performance evaluation model (LWAP) to evaluate wake effects in large wind farms is developed. The model accounts for multiple wake interactions and the effect on the vertical wind profile in the atmosphere boundary layer by the wind farm itself. The model predicts wind speed deficits at each turbine and for specific turbine power curves and assesses power for individual turbines and for the entire wind farm. The calculation method converges within seconds for a large wind farm evaluation. To assess the efficacy of the wake model, measured wind speed deficits and turbine power deficits along two wind directions and wind turbine rows in the Horns Rev wind farm were compared with deficits calculated using the model. The mean absolute percentage error is around 2% on average in wind speed evaluation and around 4% on average in wind turbine power evaluation. Case studies predicting row-wise power deficits of turbines arrays in Horns Rev and Nysted wind farms on multiple wind directions were compared to observations. LWAP exhibits the same accuracy on power deficit evaluation as with the CFD based models such as WindFarmer, WakeFarm and NTUA and performs better than the WAsP Park model. The computing time to process an entire full wind farm (e.g., Horns Rev) is on the order of a few seconds, significantly less than the CFD based models. In addition, a wind array layout optimization model (WALOM) is proposed to simulate, evaluate and optimize wind array performance for real wind farm site. Results of optimized wind array layouts are obtained and analyzed on case studies of multiple wind distributions conditions and site conditions. It is found that the optimized results are affected by factors such as wind distribution, wind data resolution, wake model and wind farm site conditions.