基于边界适应和风电场间影响的海上风电场微观选址优化研究

Micro-siting optimization of offshore wind farms based on boundary adaptation and inter-wind farm impacts

海上风电场用海面积有限,同时湍流低、尾流恢复慢,风力机的优化排布是增加收益的有效手段和关键技术之一。针对现有排布方法难以充分利用海上风电场规划区域,同时海上风电场集中开发,风电场之间往往相互影响等问题,文章利用基于边界适应和风电场间影响的海上风电场微观选址优化方法,结合实际算例进行分析。分析结果表明:周边风电场对目标风电场的影响程度较大,使得目标风电场的全场年净发电量比不考虑周边风电场影响时减少了1.08%;而采用边界适应优化方法后,相对于优化前遗传算法优化网格参数得到的规则排布,使得目标风电场的全场年净发电量提升了1.04%。表明该方法具有一定的应用价值,可以为风电场微观选址提供参考。

With limited sea area for offshore wind farms,as well as low turbulence and slow wake recovery,achieving optimal wind turbine scheduling is an effective means and one of the key technologies to increase revenue.In view of the existing scheduling optimization methods,it is difficult to make full use of the planning area of offshore wind farms,while offshore wind farms are developed centrally,and wind farms often affect each other,etc.Using the microscopic siting optimization method based on boundary adaptation and the influence of wind farms,combined with the analysis of practical examples,it is concluded that the existing wind farms in the surrounding area have a greater degree of influence on the target wind farm,making the target wind farm’s full annual net the proposed boundary-adaptive optimization method,when compared with the pre-optimized grid parameters of the genetic algorithm,results in a 1.04%increase in the annual net power generation of the target wind farm.