Combining economic and fluid dynamic models to determine optimal spacing in very large wind-farms
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Now that wind-farms are becoming increasingly larger, the economics and physics of wind farms become intrinsically coupled and important when designing large wind farms. It is important to develop wind farm models in which economic considerations can be combined with physical considerations in a transparent and intuitive way. For smaller wind-farms the majority of the turbines can be placed such that physical wake effects are relatively limited and thus physical effects may be less important. However, for large wind farms (e.g. with hundreds or thousands of turbines) it is important to consider the influence of wake effects on the optimal turbine spacing. For the design of wind-farms the industry uses site-specific, detailed optimization calculations for wind-turbine placement based on wake models (1; 2; 3; 4; 5; 6). Such calculations aim to place the turbines such that wake effects are limited with respect to the prevailing incoming wind-directions at the site under consideration. There are also academic studies that use wake models to optimize turbine placement using Monte Carlo simulations (7), genetic algorithms (8), or evolutionary algorithms (9; 10). In this work we will combine economic and fluid dynamic models to determine the main parameters that are important for the design of very large wind-farms.