基于改进粒子群算法的风力机选型应用研究

摘要

The wind turbine selection that influences the wind farm construction cost,the power production, and the cost of operation and maintenance during service is important for wind farms construction. Considering the capacity factor and actual power generation,choosing wind turbine performance index as a selection criterion, adopting improved particle swarm algorithm different from the conventional method, the optimal wind turbine parameters are obtained. In order to select the best wind turbines, the weighted standard deviation of wind speed is calculated to match the suitable wind turbine for the specific site. It is an effective and feasible method for the wind turbine selection.%风力机的选型是风电场建设的重要内容,它对风电场建设造价、投产后的发电量以及运行维护成本等有直接影响.文章在给定风资源的情况下,综合考虑风电场的容量系数和实际发电量,以风力机性能指数作为选型的依据,针对采用常规方法进行风力机参数线性化求解的缺陷,采用智能化的改进粒子群算法对风力机参数进行寻优.与常规计算方法相比,该方法寻得的风力机性能指数更优.结合具体实例计算候选机型的风速加权标准差,选出最优风力机.该研究结果为风电场的风力机选型提供了一种有效可行的方法,具有一定的应用参考价值.