Search

The actuator disc (AD) model combined with the Reynolds-averaged Navier-Stokes (RANS) model has been demonstrated as the most effective approach for simulating wind farm wakes due to its computational efficiency and acceptable accuracy. However, challenges remain in defining the reference inflow wind speed for the AD model and identifying a robust turbulence model for the RANS method. To solve these issues, two strategies for establishing the AD model (AD- up1D model and AD- local model), along with four turbulence models (standard k - ε , SST k - ω , linear pressure-strain RSM and modified RSM), are comprehensively validated here to predict multiple wakes within two representative wind farms. The temporal variability of multiple turbines' power output and the significant impact of wind direction on the power is particularly emphasized. Overall, this study indicates that the proposed AD- local /Mod RSM method facilitates a realistic wake recovery in the cumulated wake flow and agrees well with the field measurements. It consistently performs well, never ranking last in any test cases, with percentage deviations ranging from 1.8% to 9.0%. Most importantly, this study evaluates the strengths and weaknesses of each AD/RANS method and provides recommendations for wind farm design purposes. • Two typical wind farms featuring regular and irregular layouts are investigated. • A systematic evaluation of the AD/RANS method setting approaches are conducted. • The proposed AD- local /Mod RSM method facilitates a realistic cumulated wake effect. • Identify an effective AD/RANS model for predicting multiple wake interactions. • The quality of each turbulence model is highly related to the wind sector angle. [ABSTRACT FROM AUTHOR]

Citizens may experience discomfort from the feeling of being surrounded by wind power turbines in their municipalities. This effect, usually called "encirclement", should be prevented during any wind farm planning process. Therefore, there need to be reliable rules for how much encirclement is tolerable and how much is too much. In addition to rules, it is necessary to be able to quantify encirclement accurately. While there is a method to do so currently at hand, that method has several shortcomings. We provide an updated approach that helps drawing a more realistic picture of the actual encirclement situation. In this article, we introduce our GIS (Geographic Information System) procedure. Essentially, the basic idea is to evaluate the sight of wind turbines from points-of-view along a path around the perimeter of a given municipality. We then evaluate the algorithm with some real-world data to also compare our method to the former approach and find that our approach distinguishes between "encircled" or not in a somewhat more strict fashion than the former method does. • We describe the problem of municipal encirclement by wind turbines. • Encirclement may become a significant obstacle for wind power. • A former encirclement quantification method is refined and improved. • We apply both methods to a real world example data set. [ABSTRACT FROM AUTHOR]

A novel hybrid method is proposed for wind farm layout optimization in complex terrain. Firstly, an elliptical modeling method is presented with the Witoszynski-shaped transition curve in the computational fluid dynamics (CFD) simulations. Wind resources in complex terrain are estimated by combining CFD simulations with measured wind data, and an inverse distance weighting method is introduced. Then, an improved genetic algorithm (IGA) is presented to optimize the wind farm layout, which can significantly improve efficiency and avoid falling into local optima. Finally, to overcome the grid limitation of IGA, a particle swarm optimization (PSO) method is introduced for further optimization, i.e., IGA-PSO. The proposed method is used to optimize the wind farm layout in the complex terrain of Qianjiang, China. Various wake models and cost models are considered in the optimization, where wake models include Jensen, Gaussian wake model (GWM), double Gaussian wake model (DGWM) and cost models include annual energy production (AEP) and net annual value (NAV). The results show that the proposed method outperforms other three algorithms in providing a more favorable wind farm layout in complex terrain. • Hybrid approach for wind farm layout optimization in complex terrain consisting of CFD and IGA-PSO. • An elliptic domain modeling method based on Witoszynski transition curves in CFD simulations. • An inverse distance weighting method combining CFD simulations with measured wind data. • Improved Genetic algorithm for wind farm layout optimization considering the AEH. • Detailed analysis of the performance of the proposed IGA-PSO for wind farm layout optimization in complex terrain. [ABSTRACT FROM AUTHOR]